# Assessment of Long

- Term, System

- Wide Potential for

Demand

- Side and Other Supplemental Resources

, 2013

- 2032 Volume I FINAL REPORT

March 2013

Prepared for:

PacifiCorp Prepared by:

The Cadmus Group, Inc. / Energy Services 720 SW Washington Street, Suite 400 Portland, OR 97205

503.228.2992

In collaboration with Nexant, Inc.

### Pr incipal Investigators : Tina Jayaweera, Ph.D. Hossein Haeri, Ph.D.

Jessica Aiona

Travis Walker Aquila Velonis

Brian Hedman
Shawn Shaw

Lauren Mattison The Cadmus Group Inc.

Patrick Burns Tyler Hammer Mary Hall Johnson Nexant, Inc.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division 

# TABLE OF CONTENTS: V OLUME I

DEFINITION OF TERMS

................................ ................................ ................................ ix

ACKNOWLEDGEMENTS

................................ ................................ ............................... xi

EXECUTIVE SUMMARY

................................ ................................ ................................ . 1

Overview

................................ ................................ ................................ ............................... 1
Summary of the Results

................................ ................................ ................................ ........ 2
Capacity

- Focused (Class 1 and Class 3) DSM Resources

................................ .................... 4
Energy

- Focused (Class 2 Energy Efficiency) DSM Resources

................................ .............. 4
Supplemental Resources

................................ ................................ ................................ ...... 5
Comparison to 2011 Assessment

................................ ................................ .......................... 5

Class 1 and 3 DSM

................................ ................................ ................................ .......... 6

Class 2 DSM

................................ ................................ ................................ ................... 6
Supplemental Resources

................................ ................................ ................................ . 7



### INTRODUCTION

................................ ................................ ................................ ............. 8

Background

................................ ................................ ................................ ........................... 8
Study Objectives and Scope

................................ ................................ ................................ . 8
Class 1 and Class 3 DSM (Capacity

- Focused) Resources

................................ .................. 10
Class 2 DSM (Energy

- Efficiency) Resources

................................ ................................ ....... 10
Supplemental Resources

................................ ................................ ................................ .... 11

Resource Interactions

................................ ................................ ................................ ......... 11

Interactions within Class 2 DSM

................................ ................................ .................... 11

Interactions Between Class 1 and 3 DSM Resources

................................ .................... 12
Interactions Between Energy

- Focused and Capacity

- Focused Resources

.................... 12
Incorporating Recent or Pending Codes and Standards

................................ ...................... 12

Cross

- Resource Assumptions

................................ ................................ ............................. 15
Report Organization

................................ ................................ ................................ ............ 15 

### CLASS 1 AND CLASS 3 DSM (CAPACITY

- FOCUSED) RESOURCES

....................... 17

Scope of Analysis

................................ ................................ ................................ ................ 17
Assessment Methodology

................................ ................................ ................................ ... 18

Genera l Approach

................................ ................................ ................................ ......... 18

DLC

................................ ................................ ................................ ............................... 21
Current Programs and Product Offerings

................................ ................................ ............ 22

Class 1 DSM

................................ ................................ ................................ ................. 22

Class 3 DSM

................................ ................................ ................................ ................. 22

Class 1 and 3 Resource Potential

................................ ................................ ....................... 29
Resource Costs and Supply Curves

................................ ................................ .................... 31
Class 1 DSM Resource Results by Program Option

................................ ............................ 33

Residential and Small Commercial DLC

................................ ................................ ........ 33PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division Irrigation Load Control

................................ ................................ ................................ ... 38

Nonresidential Load Curtailment

................................ ................................ .................... 40
Class 3 DSM Resource Results by Program Option

................................ ............................ 41

Residential Time

- of

- Use Rates

................................ ................................ ...................... 41
Irrigation TOU Rates

................................ ................................ ................................ ...... 42

Nonresidential CPP

................................ ................................ ................................ ....... 44
Demand Buyback

................................ ................................ ................................ .......... 46 

### CLASS 2 DSM (ENERGY

- EFFICIENCY) RESOURCES

................................ .............. 48

Scope of Analysis

................................ ................................ ................................ ................ 48
Assessment Methodology

................................ ................................ ................................ ... 52
General Approach

................................ ................................ ................................ ......... 52

Overview

................................ ................................ ................................ ....................... 54

Data Sources

................................ ................................ ................................ ................. 54

Baseline Forecasts

................................ ................................ ................................ ........ 56

Derivation of End

- Use Consumption Estimates

................................ ............................. 57
Energy

- Efficiency Measures

................................ ................................ .......................... 58
Measure Impacts

................................ ................................ ................................ ........... 61

About Technical Potential

................................ ................................ .............................. 62

About Achievable Technical Potential

................................ ................................ ............ 63
About Levelized Costs of Conserved Energy

................................ ................................ . 71
Summary of Resource Potentials

................................ ................................ ........................ 73

Class 2 DSM Detailed Resource Potential

................................ ................................ .......... 77

Residential Sector

................................ ................................ ................................ ......... 77

Commercial Sector

................................ ................................ ................................ ........ 80

Industrial Sector

................................ ................................ ................................ ............ 83
Irrigation Sector

................................ ................................ ................................ ............. 85
Street Lighting

................................ ................................ ................................ ............... 86
Comparison of Results with the 2011 Assessment

................................ .............................. 87



### SUPPLEMENTAL RESOURCES

................................ ................................ .................. 92

Scope of Analysis

................................ ................................ ................................ ................ 92
Methodology Overview

................................ ................................ ................................ ........ 92

CHP

................................ ................................ ................................ ................................ .... 93
Technologies Assessed

................................ ................................ ................................ . 93

Data Sources

................................ ................................ ................................ ................. 94
Inputs

................................ ................................ ................................ ............................ 95
Levelized Cost of Energy

................................ ................................ ............................... 98

Technical Potential

................................ ................................ ................................ ........ 98

Market Potential

................................ ................................ ................................ ............ 99

Solar PV

................................ ................................ ................................ ............................ 100

Technical Potential

................................ ................................ ................................ ...... 100PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division Market Poten tial

................................ ................................ ................................ .......... 102
Levelized Cost of Energy

................................ ................................ ............................. 106
Solar Water Heating

................................ ................................ ................................ .......... 111

Technical and Market Potential

................................ ................................ ................... 111
Levelized Cost of Energy

................................ ................................ ............................. 113

Summar y of Results

................................ ................................ ................................ .......... 116

Technical Potential

................................ ................................ ................................ ...... 116

Market Potential

................................ ................................ ................................ .......... 116PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division 

# LIST OF TABLES

Table 1. Enacted or Pending Standards

................................ ................................ .................... 13 Table 2. Impact of Efficiency Standards on Baseline Forecast in 2032

................................ ..... 14 Table 3. State Energy Codes

................................ ................................ ................................ .... 15
Table 4. Line Loss Assumptions by State

................................ ................................ .................. 15 Table 5. Capacity

- Focused Analysis of Customer Sectors and Segments

................................ 19 Table 6. Estimated Impacts of Existing Residential Class 3 DSM Resources

............................ 26 Table 7. Estimated Impacts of Existing Commercial and Industrial Class 3 DSM Resources

.... 28
Table 8. Summary of Impacts of Existing Class 3 DSM Resources

................................ ........... 29 Table 9. Class 1 and 3 DSM Market Potential (MW in 2032) by Program*

................................ 30 Table 10. Market Potential (MW in 2032) by Sector*

................................ ................................ . 30 Table 11. Class 1 DSM: Market Potential by State (MW in 2032)

................................ .............. 32
Table 12. Class 1 DSM: Levelized Costs by State ($/kW

- year)

................................ ................. 32 Table 13. Class 3 DSM: Market Potential by State (MW in 2032)

................................ .............. 33 Table 14. Class 3 DSM: Levelized Costs by State ($/kW

- year)

................................ ................. 33 Table 15. Residential and Small Commercial DLC Air Conditioning: Market Potential (MW in 2032) and Levelized Cost by State ($/kW

- yr)

................................ .................... 35 Table 16. Residential and Small Commercial DLC Air Conditioning: Program Basics

............... 36 Table 17. Residential and Small Commercial DLC Air Conditioning: Planning Assumptions

..... 36 Table 18. Residential and Small Commercial DLC Water Heating: Levelized Cost by State ($/kW)

................................ ................................ ................................ .................. 37 Table 19. Residential and Small Commercial DLC Water Heating: Program Basics

................. 37
Table 20. Residential and Small Commercial DLC Water Heat Planning Assumptions

............. 38 Table 21. Irrigation Load Control: Market Potential (MW in 2032) and Levelized Cos t by State ($/kW

- yr)

................................ ................................ ................................ .............. 3 9 Table 22. Irrigation Load Control: Program Basics

................................ ................................ .... 39 Table 23. Irrigation Load Control: Planning Assumptions

................................ .......................... 39 Table 24. Nonresidential Load Curtailment: Market Potential (MW in 2032) and Levelized Cost by State ($/kW

- yr)

................................ ................................ ................. 40
Table 25. Nonres idential Load Curtailment: Program Basics

................................ ..................... 40 Table 26. Load Curtailment: Planning Assumptions

................................ ................................ .. 41 Table 27. Residential TOU: Market Potential (MW in 2032) and Levelized Cost by State ($/kW

- yr)

................................ ................................ ................................ .............. 41 Table 28. Residential TOU: Program Basics

................................ ................................ ............. 42 Table 29. Residential TOU: Planning Assumptions

................................ ................................ ... 42 Table 30. Irrigation TOU: Market Potential (MW in 2032) and Levelized Cost by State ($/kW

- yr)

................................ ................................ ................................ .............. 43 Table 31. Irrigati on TOU: Program Basics

................................ ................................ ................. 43 Table 32. Irrigation TOU: Planning Assumptions

................................ ................................ ....... 43 Table 33. Nonresidential CPP: Market Potential (MW in 2032) and Levelized Cost by State ($/kW

- yr)

................................ ................................ ................................ .............. 44
Table 34. Nonres idential CPP: Program Basics

................................ ................................ ........ 45 Table 35. Nonresidential CPP: Planning Assumptions

................................ .............................. 45 Table 36. Demand Buyback: Market Potential (MW in 2032) and Levelized Cost by State ($/kW

- yr)

................................ ................................ ................................ .............. 46 Table 37. Demand Buyback: Program Basics

................................ ................................ ........... 46 Table 38. Demand Buyback: Planning Assumptions

................................ ................................ . 47 Table 39. Residential Sector Dwelling Types and End Uses

................................ ..................... 49PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division Table 40. Commercial Sector Customer Segments and End Uses

................................ ............ 50 Table 41. Industrial Sector Customer Segments and End Uses

................................ ................ 51
Table 42. Class 2 DSM Measure Counts*

................................ ................................ ................. 51 Table 43. PacifiCorp Data Sources Used in Class 2 DSM Analysis

................................ ........... 55
Table 44. Class 2 DSM Pacific Northwest Data Sources

................................ ........................... 56 Table 45. Residential Energy

- Efficiency Measures Types

................................ ......................... 59 Table 46. Commercial Energy

- Efficiency Measures Types

................................ ........................ 60 Table 47. Industrial Energy

- Efficiency Measures Type s

................................ ............................ 61 Table 48. Example of Lost Opportunity Treatment: 10

- Year EUL Measure on a

10

- Year Ramp Rate

................................ ................................ ................................ ....... 68 Table 49. Levelized Cost Components by State

................................ ................................ ........ 71 Table 50. Baseline Sales, Technical and Achievable Technical Class 2 DSM Potential (Cumulative aMW in 2032) by Sector

................................ ................................ ............ 74
Table 51. Technical and Achievable Technical Class 2 DSM Potential (Cumulative Coincident Peak MW in 2032) by Sector

................................ ................................ ....... 74
Table 52. Baseline Sales, Technical and Achievable Technical Class 2 DSM Potential (Cumulative aMW in 2032) by State

................................ ................................ .............. 75
Table 53. Technica l and Achievable Technical Class 2 DSM Potential (Cumulative Coincident Peak MW in 2032) by State

................................ ................................ ......... 75
Table 54. Technical and Achiev able Technical Class 2 DSM Potential (Cumulative aMW in 2032) by Sector and Resource Type

................................ ................................ 76
Table 55. Residential Sector Class 2 DSM Potential by State (aMW in 2032)

........................... 77 Table 56. Residential Sector Class 2 DSM Potential by End Use (Cumulative aMW in 2032)

... 79 Table 57. Commercial Sector Class 2 DSM Potential by State (Cumulative aMW in 2032)

....... 80 Table 58. Commercial Sector Class 2 DSM Potential by End Use (Cumulative aMW in 2032)

................................ ................................ ................................ ................ 81 Table 59. Industrial Sector Class 2 DSM Potential by State (Cumulative aMW in 2032)

........... 83 Table 60. Industrial Sector Class 2 DSM Potential by End Use (Cumulative aMW in 2032)

...... 84 Table 61. Irrigation Sector Class 2 DSM Potential by State (Cumulative aMW in 2032)

............ 86 Table 62. Street Lighting Sector Class 2 DSM Potential by State (Cumulative aMW in 2032)

... 86 Table 63. Street Lighting Sector Class 2 DSM Achievable Technical Potential by State and Fixture Ownership (Cumulative aMW 2032)

................................ .................. 87 Table 64. Comparing Clas s 2 DSM Achievable Technical Potential in 2011 and
Current Assessments

................................ ................................ ................................ .... 88 Table 65. Comparison of 2011 and Current Assessment Commercial Class 2 DSM Achievable Technical by End Use Group (Cumulative aMW in Year 20)

....................... 90 Table 66. Comparison of 2011 and Current Assessment Residential Class 2 DSM Achievable Technical by End Use Group (Cumulative aMW in Year 20)

....................... 91 Table 67. References for CHP Analysis

................................ ................................ .................... 95 Table 68. Inputs for Natural Gas Fuel Cells

................................ ................................ ............... 96 Table 69. Inputs for Natural Gas

- Fired Gas Turbines

................................ ................................ 96 Table 70. Inputs for Natural Gas

- Fired Microturbines

................................ ................................ 96 Table 71. Inputs for Natural Gas

- Fired Reciprocating Engines

................................ .................. 97 Table 72. Inputs for Industrial Biomass Steam Turbine Systems

................................ ............... 97 Table 73. Inputs for Biogas Systems

................................ ................................ ......................... 97 Table 74. CHP Cost Adjustments by State

................................ ................................ ................ 97 Table 75. 2013 Levelized Cost by Configuration and State

................................ ....................... 98 Table 76. CHP Technical Potential by State and Technology (Cumulative MW in 2032)

........... 99 Table 77.CHP Market Potential by State (Cumulative in 2032)

................................ ............... 100
Table 78. CHP Mark et Potential by Fuel (Cumulative in 2032)

................................ ................ 100PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division Table 79. Data Sources Used in Solar PV Technical Potential Calculations

............................ 101 Table 80. Installed Solar PV Capacity by State and Sector 2010

– 2012

................................ .. 103 Table 81. Data Sources and Assumptions for Solar PV Market Potential

................................ 104
Table 82. Solar PV Annual Market Penetration Rates Used in the 2011 and 2013 IRPs

......... 105
Table 83. Solar PV Technical and Mar ket Potential (Cumulative MW in 2032)

........................ 105 Table 84. Solar PV Technical and Market Penetration (Cumulative aMW in 2032)*

................ 105 Table 85. Data Sources Used for the Solar PV LCOE Analysis

................................ ............... 106 Table 86. Comparison of Installed Costs for Solar PV Systems in the U.S.

............................. 108 Table 87. Solar PV Residential Single

- Family Assumptions

................................ .................... 109 Table 88. Solar PV Multifamily, Commercial, and Industrial Assumptions

............................... 110 Table 89. Solar PV Levelized Cost of Energy Summary Results and Capacity Factors

........... 111 Table 90. SWH Technical and Market Potential by State and Sector (Cumulative aMW in 2032)

................................ ................................ ................................ .............. 112 Table 91. Comparison of Installed Costs for U.S. Residential Single

- Family SWH Systems

... 114 Table 92. Solar Water Heating Residential Assumptions

................................ ........................ 114 Table 93. Solar Water Heating Multifamily and Commercial Assumptions

............................... 115 Table 94. SWH Levelized Cost of Energy Before and After the ITC Expiration

........................ 116 Table 95. Supplemental Resources Technical Potential by Territory and Resource Category (Cumulative aMW in 2032)

................................ ................................ .......................... 116 Table 96. Market Potential for Supplemental Resources by Territory and Resource Category (Cumulative aMW in 2032)

................................ ................................ .......................... 116PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division 

# LIST OF FIGURES

Figure 1. Reliability and Customer Choice Considerations in DSM Resources

........................... 9 Figure 2. General Methodology for Assessment of Class 2 DSM Resource Potential

............... 52 Figure 3. Existing Equipment Turnover for Varying RULs

................................ ......................... 65 Figure 4. Examples of Lost O pportunity Measure Ramp Rates

................................ ................. 66 Figure 5. Example of Combined Effects of Technical Resource Availability and Measure Ramping Based on 10

- Year EUL

................................ ................................ ................... 67 Figure 6. Examples of Discretionary Measure Ramp Rates

................................ ...................... 69 Figure 7. Market Ramp Rates by State

................................ ................................ ..................... 70 Figure 8. Example of Market Ramp Rate Impacts for Wyoming

................................ ................ 71 Figure 9. Illustration of Capital and Reinstallation Cost Treatmen t

................................ ............ 72 Figure 10. Acquisition Schedule for Achievable Technical Potential by Year and Sector

........... 76 Figure 11. Residential Sector Class 2 DSM Achievable Technical Potential by Segment (Cumulative in 2032)

................................ ................................ ................................ ..... 78 Figure 12. Residential Sector Class 2 DSM Achievable Technical Potential by
End Use in 2032

................................ ................................ ................................ ............ 80 Figure 13. Commercial Sector Class 2 DSM Achievable Technical Potential by Segment in 2032

................................ ................................ ................................ ........... 81 Figure 14. Commercial Sector Class 2 DSM Achievable Technical Potential by

End Use in 2032

................................ ................................ ................................ ............ 82 Figure 15. Industrial Sector Class 2 DSM Achievable Technical Potential by Segment in (Cumulative in 2032)

................................ ................................ ................................ ..... 84 Figure 16. Industrial Sector Class 2 DSM Achievable Technical Potential by End Use (Cumulative in 2032)

................................ ................................ ................................ ..... 85 Figure 17. Calculation Steps for Technical Potential

................................ ............................... 101 Figure 18. PacifiCorp Solar PV Technical Poten tial by State and Sector in 2032

.................... 102 Figure 19. Solar PV Ramp Rates

................................ ................................ ............................ 104PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division 

# TABLE OF CONTENTS: V OLUME II

Appendix A. Technical Supplements: Capacity

- Focused Resource Materials

Appendix A

- 1

. Secondary Sources

Appendix A

- 2 . Supply Curves
Appendix A

- 3

. Residential and Small Commercial DLC Program Assumptions and
Calculations
Appendix A

- 4 . Program Calculations

Appendix A

- 5 . Interactive Effects 

### Appendix B. Technical Supplements: Energy Efficiency Resources

Appendix B

- 1. Residential Measure Descriptions
Appendix B

- 2. Commercial Measure Descriptions

Appendix B

- 3. Industrial, Irrigation, and Street Lighting Measure Descriptions
Appendix B

- 4. Administrative Cost Benchmarking 

### Appendix C. Technical Supplements: Energy Efficiency Resources

Appendix C

- 1. Market Se gmentation
Appendix C

- 2. Measure Inputs
Appendix C

- 3. Baseline Sales
Appendix C

- 4. Achievable Technical Potentials
Appendix C

- 5. Comparison of Measure Input Assumpti ons to Energy Trust of Oregon Resource Assessment
Appendix C

- 6. Washington Measures Compared to the C ouncil’s 6 th Plan and the Regional Technical Forum 

### Appendix D. Technical Supplements: Supplemental Resources

Appendix D

- 1. Combined Heat and Power
Appendix D

- 2. On

- Site SolarPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division 

# DEFINITION OF TERMS

aMW Average Megawatt

AC Air Conditioning

C&I Commercial and Industrial

CBECS Commercial Building Energy Consumption Survey

CBSA Commercial Building Stock Assessment

CHP Combined Heat and Power

Council Northwest Power and Conservation Council

CPP Critical P eak P ricing

CSI California Solar Initiative

DBB Deman d Buyback

DEER Database of Energy Efficien t Resources

DLC Direct Load Control

DSM Demand

- side Management

EIA Energy Information Administration

EISA Energy Independence and Security Act of 2007

EPA Environmental Protection Agency

EUIs End

- use Intensit ies

EUL Effective Useful Life

FC Fuel Cell

GT Gas Turbine

HVAC Heating Ventilation and Air Conditioning

IRP Integrated Resource Pl an

ITC Investment Tax Credit (federal)

LCOE Levelized Cost of Energy

LMOP Landfill Methane Outreach Program

MT Microturbine

MW Megawatt

NEEA Northwest Energy Efficiency Alliance

O&M Operations and Maintenance

PV Photovoltaic

RE Reciprocating Engine

RECS Residential Energy Consumption Survey

RTF Regional Technical Forum

RTP Real

- time Pricing

RUL Remaining U seful Life

SEEM Simple Energy and Enthalpy Model

SGIP Self

- Generation Incentive Program

SWH Solar Water Heat ingPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division 

### TES Thermal Energy Storage

TOU/TOD Time of Use/Time of Day

TRC Total Resource Cost

UCT Utility Cost Test

UEC Unit Energy Consumption

WH Wa ter Heating

WHP Waste Heat

- to

- Power

WWTF Waste w ater Treatment FacilityPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The C admus Group, Inc. / Energy Services Division 

# ACKNOWLEDGEMENTS

This study required compilation of a large amount of data from various sources, including

several departments at PacifiCorp. It would be difficult to overstate the importance of the

contributions PacifiCorp’s staff made to this effort. The authors thank all of them for their

assistance.

For their guidance and support, w e also thank : Jeff Bumgarner, Director of Demand Side Management Planning and Development ; Don Jo nes, Jr., Senior Program Manager ; and Eli Morris, Program Manager. They offered invaluable insight and direction throughout the study’s
course, while allowing us to exercise our independent judgment and to maintain our objectivity.

We thank Pete Warnken

, Manager of Integrated Resource Planning, for his support in developing the supply curves for the 2013 IRP

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 1 

# EXECUTIVE SUMMARY

Overview

Since 1989, PacifiCorp has developed biennial Integrated Resource Plans (IRPs) to identify an optimal mix of resources that balanc e consideration s of cost, risk, unce rtainty, supply reliability/deliverability, and long

- run public policy goals . The optimization process accounts for capital, energy, and ongoing operation costs as well as the risk profile s of various resource alternatives, including : traditional generation and market purchases , renewable generation, and

demand

- side management (DSM) resources such as energy efficiency, and demand response or capacity

- focused resources. Since the 2008 IRP, DSM resources have compete d directly against

su pply

- side options, allowing the IRP model to guide decisions regarding resource mix es
, based

on cost and risk.

This study , conducted by the Cadmus Group, Inc. (Cadmus), in collaboration with Nexant , Inc. (Nexant), primarily seeks to develop reliable estim ates of the magnitude, timing, and cost s of

DSM resources likely available to PacifiCorp over a 20

- year planning horizon

, beginn ing in

2013

. The study focuses on resources realistically achievable during the planning horizon, given normal market dynamics t hat may hinder resource acquisition. Study results will be incorporated into PacifiCorp’s 2013 IRP and subsequent DSM planning and program design efforts

. This study serves as an update of similar studies completed in 20 07 and 20 11

. 1



### For resource planning purposes, PacifiCorp classifies DSM resources into four categories, differentiated by two primary characteristics: reliability and customer choice. These resources

can be defined as: Class 1 DSM (firm, capacity focused), Class 2 DSM (energy efficiency), Cl ass 3 DSM (non

- firm, capacity focused), and Class 4 DSM (educational).

From a system

- planning perspective, Class 1 DSM resources can be considered the most reliable

, as they can be dispatched by the utility. In contrast, behavioral changes, resulting from voluntary educational programs included in Class 4 DSM, tend to be the least reliable. With respect to customer choice, Class 1 DSM and Class 2 DSM resources should be considered involuntary in that, once equipment and systems have been put in place, savi ngs can be expected to flow. Class

3 and Class 4 DSM activities involve greater customer choice and control

. This assessment estimates potential from Class 1, 2, and 3 DSM.

In addition to the three DSM resource classifications, this study also estimate s potential from supplemental resources , which fall outside PacifiCorp’s classification of DSM and include

renewable and nonrenewable customer

- sited generation. For this study, s upplemental resources

include : combined heat and power (CHP), solar photovoltai cs (PV)

, and solar water heaters (SWH).

This study excludes an assessment of Oregon’s Class 2 DSM (energy

- efficiency) potential and supplemental resource potential for SWHs , as this potential has been captured in assessment

1 Both studies can be found at: http://www.pacificorp.com/es/dsm.htmlPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 2 

### work conducted by the Energy Tru st of Oregon (Energy Trust)

, which provides energy

efficiency potential in Oregon to PacifiCorp for resource planning purposes.



## Summary of the Results

The study includes two distinct types of energy

- focused resources: Class 2 DSM (energy

efficiency) ; and supplemental (customer

- sited generation)

.

The Cadmus team estimates a cumulative, system

- wide, technical potential for Class 2 DSM savings of 819 average megawatts (aMW) 2 

### over the 20

- year planning horizon : 2013 to 2032 ( as shown in Table ES

- 1). Collectively , 884 aMW (excluding Oregon) of energy

- focused resource potential can be assumed to be reasonably achievable

, once normal market and program delivery

constraints are accounted for

.

For Class 2 DSM resources, this potential is called achievable technical potential, though also known as market potential for supplemental resources (including on

- site solar and CHP). 3



### Achievable technical Class 2 DSM resources account for 73 % ( 648 aMW) of the energy

- focused resource potential

, and the market potenti al of supplemental resources (including on

- site solar

and CHP ) account for the remaining 27 % ( 2 36 aMW). These results represent avoided utility generation, rather than savings at the customer meter, and therefore account for appropriate

transmission and distribution losses.

Table ES

- 1 . Energy

- Focused Resource Potential (aMW in 203 2 ):

Technical and Achievable Technical /Market by Resource and Service Territory

Resource Class/Service Territory Technical

Potential Achievable Technical

or Market Potential **
Rocky Mountain Power

Class 2 DSM Resource 707 560
Supplemental Resource 4,094 1 68
Rocky Mountain Power Subtotal 4,801 728

Pacific Power

Class 2 DSM Resource* 112 88
Supplemental Resource * 1,885 6 8

Pacific Power Subtotal 1,997 156
PacifiCorp System Total 6,797 884 * Excludes Oregon for Class 2 DSM and solar water heaters (supplemental resource)

. ** Class 2 DSM resource potential is stated as achievable technical potential; supplemental resource potential is stated as market potential. Note: Individual results may not sum to the total due to rounding.

2 Average megawatt (aMW), a unit of energy used for planning purposes in the Pacific Northwest, is calculated as the ratio of energy (MWh) and the nu mber of hours in the year (8760). One aMW equals 8,760 MWh.

3 Achievable technical potential uses an estimate of potential, based on a theoretical maximum adoption. Market potential is based on actual adoption rates.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 3 

### Table ES

- 2 shows e stimate s of coincident peak demand impacts from the identified resources

. 4



### T hese impacts have not been adjusted to account for resource competition and/or interaction s and

, therefore

, cannot be considered additive in nature.

For example, i f all Class 2 DSM (energy

- efficiency) resources were acquired , they would reduce

the load basis from which Class 1 and 3 DSM (capacity

- focused resource s ) impacts could be calculated. In addition, Class 1 and 3 DSM programs are not mutually exclusive; thus, the overall peak impact from capacity or demand

- focused programs would be less if account ing for all

interactions.

Again, achievable technical potential is used to represent the quantity of Class 2 DSM resources that can reasonably be acquired through any means within the planning period , while market potential is used to represent the quanti ty of Class 1 and 3 DSM and supplemental resource technical potential deemed reasonably achievable through utility programmatic activity

. The projected potential for Class 1 DSM products includes PacifiCorp’s current program offerings, as

the load forecast did not account for these programs’ impacts. However, the load forecast reflects

the impacts of existing Class 3 DSM offerings ; therefore

, this report’s market potential results

should be considered incremental to the impacts from PacifiCorp’s existing Class 3 DSM offerings.

Table ES

- 2

. Peak Demand Reduction Potential (MW in 203 2 ):

Technical and Achievable Technical /Market by Resource and Service Territory
Resource Class/Service Territory Technical Potential ** Achievable Techn ical or Market Potential *
Rocky Mountain Power

Class 1 DSM Resource N/A 48 8

Class 2 DSM Resource 1,339 1,078

Class 3 DSM Resource N/A 4 5
Supplemental Resource 10,023 367
Rocky Mountain Power Subtotal N/A 1,9 78

Pacific Power

Class 1 DSM Resource N/A 116

Class 2 DSM Resource* * * 200 163

Class 3 DSM Resource N/A 20
Supplemental Resource 5,012 1 49

Pacific Power Subtotal N/A 44 8
PacifiCorp System T otal N/A 2,4 26

* Class 2 DSM resource potential is stated a s achievable technical potential; supplemental resource potential is stated as Market

Potential. ** Technical potential was not calculated for Class 1 and 3 DSM resources

.

* * * Excludes Oregon.

4 Coincident peak impacts are determi ned based on savings during the top 40 system hours for Class 2 DSM and supplemental resources. Class 1 and 3 impacts, defined by assumed program operation hours, are not truly

additive.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 4 

## Capacity

- Focused (Class 1 and Class 3) DSM Resources

M arket potential results from the Class 1 and 3 DSM resources

, provided in Table ES

- 2 and

Table ES

- 3 ( below )

, break down by resource c lass

, sector

, and territory

. They represent an assessment of load management opportunities/products within PacifiCorp’s service t erritories

within each resource class

. As noted

, totals are not additive

, as the programs have a lower overall peak impact when accounting for all interactions . Additionally, Class 1 DSM resources include impacts that are already captured/managed through c urrent program offerings, while Class 3

DSM results are incremental to current time

- varying rate program offering s

.

Table ES

- 3. Class 1 and Class 3 (Capacity

- focused) DSM Resource Market Potential by

Customer Sector and Service Territory (MW in 203 2 )

Rocky Mountain Power Pacific Power PacifiCorp System

Class 1 DSM

— "Firm"

Residential 15 1 4 1 19 2

Small Commercial 1 1 2 Large Commercial 55 4 2 97

Industrial 70 2 2 9 2 Irrigation 210 11 221

Subtotal 488 116 604

Class 3 DSM

— ― Non

- Firm ‖

Residential 19 7 26

Small Commercial 0 0 0 Large Commercial 5 4 8

Industrial 1 2 2 1 4 Irrigation 1 1 7 1 8

Subtotal 45 20 66

Total 533 137 670



### The i rrigation sector accounts for 37% of total Class 1 market potential

, and the r esidential sector

contributes another 32%. Currently

, PacifiCorp operates residential direct load control ( DLC ) air

condit ioning and irrigation DLC program s in Rocky Mountain Power ’s service territory

.

Based on research by the Cadmus team into similar programs’ participation, t hese existing

progr ams in Rocky Mountain Power’s service territory appear to be fully subscribed

, and future

incremental market potential realized through these programs will likely be driven by load growth

, rather than increases in existing customer participation. Th ough system

- wide

, 66 MW of

Class 3 DSM market potential is much lower than that available for Class 1 resources, the potential for Class 3 DSM products is incremental to sa v ings achieved by PacifiCorp’s current

time

- varying rate program s

. Chapter 2 discusse s cu rrent Class 3 DSM program impacts in

greater detail.



## Energy

- Focused ( Class 2 Energy Efficiency) DSM Resources

As shown in Table ES

- 4

, system

- wide achievable technical potential for Class 2 DSM ( energy

efficiency ) resources has been estimated at 648 aMW

, r epresenting 79% of identified technical potential for this resource in five of PacifiCorp’s six state service areas (excludes Oregon)

.PacifiCorp Assessment of Long

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- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 5 

### Table ES

- 4. Class 2 DSM (Energy

- Efficiency) Resource Achievable Technical Potential by

Customer Sector and Service Territory ( Cumulative aMW in 2032 )

Sector Rocky Mountain Power Pacific Power* PacifiCorp

System * As Percent of 203 2

Baseline Sector Sales*

Residential 151 39 190 15%

Commercial 200 34 234 15%

Industrial 195 12 207 9%
Irrigation 10 3 13 10%
Street Lighting 3 0 4 30%

Total 560 88 648 12% * Potential and baseline sales do not include Oregon

. Note: Individual results may not sum to the total due to rounding.



### The commercial sector accounts for the largest share of achievable energy

- efficiency savings at

234 aMW

, followed by the industrial sector at 207 aMW. Projections indicate a n additional

207 aMW of electricity savings available in the residential , irrigation, and street lighting sectors.

Resource opportunitie s , however, may differ in terms of value (when screened for economic potential in the c ompany’s integrated resource planning process) . For instance, street lighting savings occur during off

- peak periods

, and these may have less value than other efficiency

measures

. Discretionary resources (i.e., retrofit opportunities) account for 488 aMW ( 75 % ) of

energy

- efficiency achievable technical potential across all sectors. The r emaining potential is

associated with lost opportunity resources, namely new constructio n and replacement of existing equipment at the end of its normal life cycle

. 

## Supplemental Resources

Table ES

- 5 provides s upplemental resource potential , with an estimated 2 36 aMW of market potential across PacifiCorp’s system. Resources considered include CHP, s olar PV, and SWH. Market adoption rates have been based on recent adoption rates for the technologies included

.

Table ES

- 5. Supplemental Resource Market Potential by Technology and

Service Territory ( Cumulative aMW in 20 32 )

Market Potential Rocky Mountain Power Pacific Power PacifiCorp System

CHP 123 45 168

Solar: PV 43 23 65

Solar Water Heating * 2.6 0.7 3.3

Total 1 68 6 8 236 Note: Individual results may not sum to the total due to rounding. * Potential does not include Oregon in Pacific Power territory (th ose data are provided to the c ompany by the Energy Trust )

.



## Comparison to 2011 Assessment

As noted , this assessment builds upon stud ies completed in 2007 and 2011 . This section review s key differences between the current study findings and those presented in the 2011 A ssessment

.PacifiCorp Assessment of Long

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The Cadmus Group, I nc. / Energy Services Division 6 

## Class 1 and 3 DSM
This study considered a set of eight Class 1 and Class 3 program options , while the 2011

A ssessment analyzed two additional resources : real

- time pricing ( RTP ), and thermal energy storage (TES). This study did not conduct additional analyses of these resource options, as RTP is considered a competing, less common, alternative to other price

- based options

, and little ( or

no ) change has been made to TES technologies (a relatively high

- cost program option) 5 

### since the 2011 Assessment was completed. For resources assessed in this study, basic assumptions underlying potential and per

- unit cost calculations were updated to reflect more recent market

da ta, information on similar programs offered by other utilities, and PacifiCorp’s experience with

its currently operating programs. Additionally, in the 2011 Assessment

, winter potential was

assessed

, while this study focuses only on reducing system load du ring summer hours.

This study’s analysis of capacity

- focused resources identified 670 MW of market potential during system summer peak periods , compared with 1,137 MW estimated in the 2011

Assessment (which included both summer and winter peak periods)

. Th e current study indicated

t he market potential for Class 1 DSM to be 604 MW

, comparable to the 6 23 MW of market potential identified in the 2011 Assessment . Class 3 potential dropped from 514 MW to 66 MW

, driven by a drop of nearly 290 MW in potential for the irrigation time

- of

- use (TOU ) option, approximately 114 fewer MW of potential for critical

- peak pricing (CPP)

, and 21 fewer MW for demand buy back (DBB)

. The large difference in irrigation TOU market potential was a result of assuming voluntary, rather than mandatory, participation, while l ower CPP and DBB potential primarily resulted from decreases in estimated program participation and is consistent with

recent actual program experience

.

In an effort to better understand the potential contributions fr om Class 3 DSM resource offerings (existing and new) t he current study includes an assessment of impacts from PacifiCorp’s existing time

- varying rate structures

, such as the mandatory residential block rates and

nonresidential TOU tariffs. A review of seco ndary literature on customer response s to changes in price indicated a range of elasticities, making it difficult to determine a point estimate for impacts of existing rate structures. However, analysis results indicated these price structures

reduc e Pacif

iCorp’s peak system load by 69 MW to 250 MW annually

. Because these impacts are embedded in current loads, Class 3 potentials identified in this study are incremental to impacts of existing price structures.



## Class 2 DSM

For the Class 2 DSM analysis , the following items served as key drivers of changes :

A ccounting for new ly enacted codes and standards , even if not yet in effect;

A djusting for PacifiCorp’s actual and projected DSM program accomplishments from 2010 through 2012;

I ncorporating adjustme nts to measure savings

, based on recent evaluation results, including data available from the Regional Technical Forum (RTF) ;

5 The 2011 Assessment found TES costs to be over $250/kW

- yr.PacifiCorp Assessment of Long

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The Cadmus Group, I nc. / Energy Services Division 7 

### A pplying 2011 customer information to determine segmentation ; and

U tilizing 2012 load and customer forecasts.

T ogether, these ch anges decrease d total , system

- wide, 20

- year
, Class 2 DSM achievable technical potential from 1,156 aMW to 648 aMW, or 44 %. Chapter 3 provides f urther details on

th e primary contributors to the decrease in Class 2 DSM achievable technical potential

.


## Supplem ental Resources
For supplemental resources, system

- wide 20

- year market potential increased by 58 aMW, from

178 aMW to 2 36 aMW , or a 33% decrease

. S olar PV primarily drove this increase

, rising from 8

aMW in the 2011 Assessment to 65 aMW in the current study based on a change in the assumed penetration rate

. T he 2011 Assessment assumed at most 0.02% of solar PV technical potential

was achievable in any year for all states, an estimate also used in the current study for states not
currentl y offering programs. For states where programs are offered , this percentage is 0.14% for

the residential sector and 0.08% for the commercial sector , based on experience in California and Oregon

. CHP market potential also increased from 146 aMW to 168 aMW. In the current study, the estimate of market potential was refined to focus on installations in PacifiCorp’s service territory rather than on adoption rates from other jurisdictions (used in the 2011 Assessment)

.

Conversely, 20

- year market potential for so lar water heaters decreased by 19 aMW relative to

the 2011 Assessment largely due to using programmatic data to estimate market potential, rather

than m aximum achievability estimates from the Northwest Power and Conservation Council’s (the Council’s) 6 th 

### Power Plan

. This dropped market potential as a percent of technical potential

from 85 % to 15%.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 8 

# INTRODUCTION

Background

Since 1989, PacifiCorp has developed biennial Integrated Resource Plans (IRPs) to identify an optimal mix of resources, balanc ing cons ideration s of cost, risk, uncertainty, supply reliability/deliverability, and long

- run public policy goals . The optimization process accounts for capital, energy, and ongoing operation costs as well as the risk profiles of various resource alternatives, in cluding: traditional generation and market purchases, renewable generation, and

demand

- side management (DSM) resources such as energy efficiency and demand response or capacity

- focused resources. Since the 2008 IRP, demand

- side management ( DSM ) resources h ave compete d directly against supply

- side options, allowing the IRP model to make decisions regarding the resource mix based on cost and risk. Thus, this study does not assess

cost

- effectiveness

. 

## Study Objectives and Scope

This study primarily seeks to de velop reliable estimates of the magnitude, timing, and cost s of

DSM resources likely available to PacifiCorp over a 20

- year planning horizon

, beginn ing in

2013

. The study focus es on resources realistically achievable during the planning horizon, given normal market dynamics that may hinder acquisition of these resources. Study results will be incorporated into PacifiCorp’s 2013 IRP and subsequent planning efforts and into its DSM program design efforts

.

For resource planning purposes , PacifiCorp classifie s DSM resources into four categories, differentiated by two primary characteristics: reliability and customer choice (see Figure 1 )

. These resources are captured through programmatic efforts promot ing efficient electricity use through various intervention strategies

, aimed at changing : energy use peak level s (load curtailment), timing (price re sponse and load shifting), energy intensity ( energy efficiency ), or

behavior s (education and information).

From a system

- planning perspective, Class 1 DSM ( firm ) resources ( particularly controlled capacity

- focused programs ) can be considered the most reliable

, as these can be dispatched by the utility. In contrast, behavioral changes

, resulting from voluntary educational programs

included in Class 4 DSM

, tend to be the least reliable. With respect to customer choice, Class 1 DSM and Class 2 DSM (energy

- efficiency ) resources should be considered involuntary in that, once equipment and systems have been put in place, savings can be expected to flow. Class 3

and Class 4 DSM activities involve greater customer choice and control

.PacifiCorp Assessment of Long

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The Cadmus Group, I nc. / Energy Services Division 9 

### Supplemental resources, co nsisting mainly of small

- scale, dispersed generation 6 

### on the facility side of the meter, tend to be less firm, either due to uncertainties associated with their availability (solar) or to the extent customers control their operation (CHP).

Figure 1

. Reliability and Customer Choice Considerations in DSM Resources

PacifiCorp commissioned this study to reassess the potential for Class 1 and 3 DSM (capacity

focused)

, Class 2 DSM (energy

- efficiency) , and other supplemental resources within its service territory

. Study results will inform the IRP process and assist PacifiCorp in revising designs of existing programs and in developing new programs. The study did not include assessment s of

Class 4 DSM resources.

T h is study, th e third com prehensive assessment commissioned by PacifiCorp

, build s upon prior

assessments

, which were completed in 2007 and 2011. The study updates the 2011 Assessment of Long

- Term System

- Wide Potential for Demand

- Side and Other Supplemental Resources 7 

### ( the

2011 Ass essment )

. The study also refers to the prior study

, the 2007 Assessment.

The study’s scope encompasses multisector assessments of long

- term potential for DSM and other supplemental resources in PacifiCorp’s Pacific Power ( California, Oregon, and Washingto n) and Rocky Mountain Power (Idaho, Utah, and Wyoming) service territories. All results presented in the report represent savings at generation; that is, savings at the customer meter have been grossed up to account for line losses.

6 Often, the terms ―distributed‖ or ―dispersed‖ generation are used interchangeably. This study refers to ―dispersed‖ generation to describe decentralized power generation at customer facilities. ―Distributed‖ generation generally refers to generating units owned and operated by the utility.

7 http://www.pacificorp.com/es/dsm.htmlPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 10 

### The Energy Trust of Ore gon (E nergy Trust ) , however, takes responsibility for identif ying and

deliver ing energy

- efficiency resources in Oregon ; thus the study does not assess Class 2 DSM potential for Oregon. The state’s Class 2 DSM potential

, included in PacifiCorp’s 2013 IRP

, will

be based on the Energy Trust’s 2012 Resource Assessment Update

. 8 

### Appendix C

- 5 includes a comparison of measures assessed in the Cadmus team’s and Energy Trust’s assessments.



## Class 1 and Class 3 DSM (Capacity

- Focused ) Resources

Capacity

- focused (or d emand

- response) resources encompass Class 1 and Class 3 DSM. Class 1

and Class 3 DSM resources principally can be differentiated in terms of their reliability during periods of system peak or during emergencies (dispatchability). For this study, capacity

- f ocused

resources have been defined based on PacifiCorp’s characterization of two distinct classes of

firm ( dispatchable ) and non

- firm ( non

- dispatchable ) resource options:

Class 1 (Firm Capacity

- Focused ) DSM Resource

. This resource class allows controlled

or scheduled interruption s, or cycling

, of electrical equipment and appliances

, such as central air conditioners and irrigation pumps

. Examples include PacifiCorp’s Cool Keeper residential and small commercial air conditioner direct load control (DLC)

prog ram in Utah and irrigation load control programs in Utah and Idaho. While program participation is voluntary, once participating

, event participation becomes mandatory.

Class 3 (Non

- Firm Capacity Focused ) DSM Resources

. This r esource class seek s to
achieve peak demand savings from actions taken by customers voluntarily, based on a

financial incentive or time

- specific price signal. Program options in this class include demand buyback (PacifiCorp’s Energy Exchange tariff s ) and more traditional pric ing products, such as TOU ( currently offered to various customer segments in all PacifiCorp’s states) and critical

- peak pricing ( CPP ) programs

. Both program participation and event participation are voluntary.



## Class 2 DSM ( Energy

- Efficiency ) Resources

Th i s resource class consist s of technologies and measures

, such as high

- efficiency equipment and appliances, building shell improvements

, and controls

, that reduce energy consumption at

the end

- use level. Such resources may further be categorized as discretionary (retrofit s in existing construction) or lost opportunit ies (e quipment replacement and efficiency improvements

in new construction ). Class 2 DSM resources can be acquired through various market

intervention mecha nisms

, such as : equipment incentives ; direct installation ; process and activity optimization lead ing to sustained changes in energy use ; or advancement of codes and standards. The type and intensity of market intervention strategies, prevailing retail rate s, and availability of capital in a given market can affect the amount and cost of Class 2 DSM resource s

. Once

installed

, savings are assumed to persist ( remain firm) over the 20

- year study period (customers will reinvest in ―equal to‖ or greater efficienc y at the end of the measure ’ s useful life).

8 http://energytrust.org/library/reports/121114_2012_ResourceAssessment.pdfPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 11 

## Supplemental Resource s

For this study, supplemental resources represent small

- scale

, 9 

### dispersed power generation technologies. T his assessment considered two options:

1. CHP

, as the simultaneous generation of energy and heat, with waste heat captured and

used within a steam turbine or for industrial process heating, space heating, and/or

domestic hot water . CHP generation technologies include: reciprocating engines, microturbines, fuel cells, gas turbines, and steam turbines.

2. On

- Site Sola r

, which include s small

- scale photovoltaic s (PV) and SWHs

. 10



### The Cadmus team estimated technical and market potentials for these resources. The technical potential, as with other resource types

, results as a measure of total savings, assuming all resources are installed in all technically feasible applications. Market potential, on the other hand, is an estimate of what will likely be installed, given market constraints, and is based on historical activity w ithin PacifiCorp ’s territory.



## Resource Interactions

In assessments involving diverse DSM resource s ( such as the present one )

, one must acknowledge technical interactions occurring both within a resource class ( i.e.

, among various program options and end

- use measures) and between them (i.e.

, interaction s between similarly

focused resource classes

, such as Class 1 and 3 DSM ). T hese effects must be carefully

considered to avoid double

- counting available potential. This study explicitly estimates intra

class and resource type (energy or capacity) interactions, but it does not account for interactions between energy

- focused and capacity

- focused resources.



## Interactions within Class 2 DSM

Several interactions have bee n accounted for in the Class 2 DSM analysis. First, a ―stacking

effect‖ occurs when complementary retrofit measures

— such as wall, ceiling, and floor

insulation

— appl y to a single end use. As measure savings are always calculated in terms of

reductions in en d

- use consumption, installation of one measure reduces the savings potential of subsequently installed measures. That is, the combined effect of installing two measures affecting the same end use tend s to be less than the sum of their individual impacts.

A similar effect occurs when equipment and non

- equipment (retrofit) measures within Class 2 DSM compete for the same end

- use resource, such as space conditioning (e.g., a high

- efficiency central air conditioner and high

- efficiency windows). As with the stac king effect, if non

equipment measures can be captured first, replacement of existing equipment with high

efficiency equipment can be expected to have smaller impact s on end

- use consumption than if replacement had taken place first.

9 Resources with nameplate capacities of less than 10 MW generally are considered ―small scale.‖

10 The 2011 Assessment included solar attic fans, which this study excluded due to the very high costs per kWh.PacifiCorp Assessment of Long

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The Cadmus Group, I nc. / Energy Services Division 12 

### The analysis also acco unts for t echnical interactions among measures
, such as lighting retrofit s and weather

- sensitive loads; depending on the season, heat loss from efficient lighting may increase (in winter) or decrease (in summer) HVAC power consumption.



## Interactions Between Class 1 and 3 DSM Resources
For PacifiCorp’s IRP modeling (resource supply curve construction)

, the Cadmus team

accounted for i nteractions within and between Class 1 and Class 3 DSM resources

. The numbers in this report represent the full potential

, without interactions ; Appendix A

- 5 provides the potential estimates with interactions . Resources were prioritized within each customer sector by

the firmness of the resource and then by cost

. The following logic allowed potential adjustments

to account f

or these interactions :

Residential: The Cadmus team assumed participation in the DLC air conditioning and water heating programs would take precedence over TOU rates

. Customers already enrolled in the DLC program would not opt out to participate in the TOU program

.

Small Commercial: As small commercial only had one product, the study did not

consider interactive effects.

Large Commercial and Industrial: The Cadmus team assumed all available potential would likely be captured by the nonresidential l oad c urtailment program and no remaining potential would be available for Demand Buyback ( DBB ) or CPP where load

c urtailment i s offered

. Irrigation: The Cadmus team ’ s analysis indicated current programs in Idaho and Utah

have exhausted the market potential in this sector for those states ; therefore

, no potential

remains for the TOU program. For the remainder of the states, the Cadmus team adjusted TOU program participation to account for interactions with the irrigation DLC opportunities

.



## In teractions Between Energy

- Focused and Capacity

- Focused

Resources

I nteractions also exist between Class 2 and Class 1 and 3 DSM resources as well as with supplemental resources. P rimarily, because implementation of energy

- efficiency or supplemental

resources measures lowers peak demand, it reduc es technical and market potential for Class 1

and 3 DSM resources. Th ough an important factor to recognize, thi s study did not attempt to quantif y such interactions due to uncertainties regardi ng resources likely to be found economic

and pursued

. 

## Incorporati ng Recent or Pending Codes and Standards

While the Cadmus team ’ s analysis does not predict how energy codes and standards may change

over time

, the study incorporate s estimates of enacted leg islation ’s impacts , even if the legislation will not take effect for several years. The most notable, recent efficiency regulation

has been the Energy Independence and Security Act of 2007 (EISA), which set new standards for general service lighting, motor s, and other end

- use equipment. C aptur ing effects from this legislation has been particularly important

, as residential lighting has played a large role inPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 13 

### PacifiCorp’s energy

- efficiency programs over the past several years. In addition to enacted

federal legislation, several states in PacifiCorp’s service territory have updated and revised their state energy code s

. Table 1 provides a list of the efficiency standards explicitly accounted for in the development of the current study

.

Table 1 . Enacted or Pending Standards

Equipment Type Sector Year Effective *

Appliances

Clothes Washer (1.76 MEF top loading, 2.2 MEF front loading ) Commercial /Residential 2016

Clothes Washer (2.0 MEF top loading ) Commercial /Residential 2018

Commercial Refrigeration Equipment

- (Semivertical and Vertical Cases) Commercial 2012

Cooking Oven Residential 2012

Dehumidifier Residential 2013

Dishwasher (307 kWh/year) Commercial /Residential 2014
Dryer Residential 2015

Freezer Commercial /Residential 2015

Ice Maker Commercial 2013
Refrigerator Commercial /Residential 2015
Vending Machines Commercial 2012

Motors

Small Electric Motors Commercial /Industrial 2015

Water Heaters

Water Heater > 55 gallons (EF ≥ 2.0,

var yin g by size) Commercial /Residential 2015

Water Heater ≤ 55 gallons (e.g. EF = 0.948 for 40 gal lon ) Commercial /Residential 2015

HVAC

Central Air Conditioner (SEER 14) Residential

– C alifornia only 2015
Heat Pump

- Air Source (14 SEER/ 8.2 HSPF) Residential 2015

Room A ir C onditioner (10.9 CEER) Residential 2015
Lighting
Lighting General Service Fluorescent Lamp

– EISA Commercial /Industrial 2012

Lighting General Service Lamp

- EISA Commercial /Industrial/Residential 2013, 2014 **
Lighting General Service Lamp

- EISA Backstop Provision Commercial /Industrial/Residential 2020 **

Lighting Specialty Lamp

- EISA Incandescent Reflector Lamps Residential 2012

*Standards tak ing effect mid

- year are assumed to begin on January 1 of the following year

. ** California standards take effect one year prior to federal standards.



### To capture impact s of upcoming equipment standards in estimati ng C lass 2 DSM resource potential, the Cadmus team incorporated these standards into the baseline forecast. Table 2

show s estimated impact s of changes in equipment efficiency standards on forecasted baselinePacifiCorp Assessment of Long

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The Cadmus Group, I nc. / Energy Services Division 14 

### residential and commercial loads in 2032 , respectively. 11 

### Overall, new equipment standards lead

to d ecreases in 2032 baseline sales of 7.4% and 1.3% in the residential and commercial sectors, respectively. A large portion of the difference in residential resulted from the impact of EISA standards on lighting. 12



### Table 2 . Impact of Efficiency Standards on Baseline Forecast in 2032

Sector State 2032 Forecast

Without Standards (aMW) 2032 Forecast

With Standards (aMW) * Effect of Standards

( Percent Reduction

in 2032 Forecasted
Sales )

Residential California 49 46 5.7%

Idaho 113 106 5.8%

Utah 896 820 8.5%

Washington 204 196 4.1%

Wyoming 136 127 6.7%

Subtotal 1,398 1,295 7.4%

Commercial California 33 33 1.4%

Idaho 62 61 1.1%

Utah 1,076 1,062 1.3%

Washington 164 162 0.9%

Wyoming 205 202 1.4%

Subtotal 1,540 1,520 1.3%

Total 2,938 2,815 4.2%
* Used as baseline for Class 2 DSM potentials analysis



### E nd

- use consumption for new construction buildings accounted for state building codes , but it did not incorporate future changes to codes over the planning horizon. 13 

### No attempt was made to quantify impacts of recently updated building codes due to the difficulty in determining an appropriate baseline from which to claim savings. Table 3 provides energy codes in place at the time of this study.

11 The study did not quantify the impacts of standards in the industrial sector, as these were anticipated to

be small.

12 Screw base lighting mak es up a much larger share of total sales in the residential sector compared to commercial, which explains why lighting standards have a larger impact on residential sales.

13 State energy codes typically update on a three

- year cycle, but this study did not attempt to predict future code changes.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 15 

### Table 3 . State Energy Codes

State Energy Code Used

Residential Nonresidential
Washington 14 Energy Code 2009 Edition, Chapter 51

- 11 WAC Energy Code 2009 Edition, Chapter 51

- 11 WAC

Idaho 2009 IECC 2009 IECC

Utah 2006 IECC 2009 IECC with references to ASHRAE 90.1

- 2007

California 15 2008 Building Energy Efficiency Standards

,

Title 24 2008 Building Energy Efficiency Standards

, Title 24
Wyoming 2003 IECC * 2003 IECC * IECC = International Energy Conservation Code

.

* As Wyoming does not have a statewide residential energy code

, 2003 IECC ( Z one 16) was used as a proxy

.



## Cross

- Resource Assumptions

S everal assumptions applied to all resources : discount rate, inflation rate, and line losses

. Consistent with PacifiCorp’s 2013 IRP assumptions , this study used a nominal discount rate of

6.88% , with an inflation rate of 1.9%. Table 4 provides l ine losses

.

Table 4

. Line Loss Assumptions by State

Sector Washington Idaho California Wyoming Utah Oregon

Residential 9.7% 11.5% 11.4% 9.5% 9.3% 10.0%

Commercial 9.5% 10.7% 11.1% 8.9% 8.7% 9.6%

Industrial 8.2% 4.9% 9.9% 5.6% 5.4% 7.1%
Irrigation 9.7% 11.4% 11.4% 9.3% 9.2% 9.9%

Street Lighting 9.7% 11.5% 11.4% 9.% 9.3% 10%



### All baselines and potentials presented in this report include these line losses and thus represent

sa les and savings at the generator.



## Report Organization

This report is divide d in to two volumes , with t he present document (Volume I) organized into

five sections. The three sections following the Executive Summary and I ntroduction sections

address analys e s of various resource options, primarily :

Class 1 and Class 3 DSM (capacity

- focused) resources;

Class 2 DSM (energy

- efficiency) resources; and

S upplemental r esources.

The DSM resource section s begin by describing the scope of the analysis , followed by a discussion of methodolog ies

, then summarize the resource potential, and finish with detailed

14 Washington State Energy Code 2009 Edition: http://apps.leg.wa.gov/wac/default.aspx?cite=51

- 11

15 California’s 2008 Code of Regulations Title 24: http://www.energy.ca.gov/2008publications/CEC

- 400

- 2008

- 001/CEC

- 400

- 2008

- 001

- CMF.PDFPacifiCorp Assessment of Long

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- Wide Potential March 2013

The Cadmus Group, I nc. / Energy Services Division 16 

### results. The supplemental resource chapter takes a somewhat different form to account for the

wide variation in resources considered. Volume II of this report presents a dditional technical information, assumptions, data, and other relevant details for both DSM and s upplemental

resources

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 17 

# CLASS 1 AND CLASS 3 DSM (CAPACITY

- FOCUSED)
RESOURCES

Scope of Analysis

This DSM resource class consist s of products and programmatic options designed to :

H elp reduce peak demand during system emergencies or periods of extreme market prices ;

P romote imp roved system reliability ; and

I n some cases, balanc e variable

- load resources , particularly wind energy

.

B enefits from Class 1 and 3 DSM resources accrue by providing incentives for customers to curtail loads during utility

- specified events ( e.g.
, D LC and DBB) or by offering pricing

structures to induce participants to shift load away from peak periods ( e.g.
, TOU and CPP programs). T his study defined capacity

- focused resources using PacifiCorp’s characterization of

two distinct classes of firm (Class 1 DSM) and non

- firm (Class 3 DSM) resource options.

Class 1 (Firm Capacity

- Focused ) DSM Resources . This class of capacity

- focused resources offers the most reliable resource to the utility. Strategies in this category allow for total or partial interruption of electric loads for equipment and appliances, such as central air conditioners, irrigation pumps, and process loads. Load interruptions may be achieved through direct control by the utility (or a third

- party under contract to the utility), on a scheduled ba sis, or through coordination with energy

- management systems at the end

- user’s facility

. From a planning perspective, Class 1 resources generally are considered ―firm‖ as the utility’s control over the resources gives them a relatively high level of reliability

. This study analyzed three primary program options identified by system opportunity :

Residential and small commercial DLC programs allow PacifiCorp to remotely interrupt or cycle electrical equipment and appliances at the customer’s facility. T his study analyzed DLC program potential for residential and small commercial central electric cooling and electric water heating.

Irrigation DLC allows PacifiCorp to directly control irrigation pumps during periods of high demand

.

Nonresidential Load C urtailment programs target larger commercial and industrial ( C&I )

customers with sh iftable loads and/or on

- site standby generation assets that can be called upon by the utility

, as needed. These customers

, enter ing into curtailment agreements

with the util ity or an aggregator

, receive financial incentives for their participation and willingness to provide resources when needed.

Class 3 (Non

- Firm Capacity

- Focused ) DSM Resources . These program options prove less

reliable than those in Class 1 DSM as they are not ―dispatchable‖ by the utility . Event participation is voluntary

, thus variable

, and impacts cannot be ascertained until after the fact.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 18 

### Class 3 DSM resources include time

- varying prices and the DBB program. Participants receive

i ncentives either through rates (time

- varying prices) or per

- event payments (DBB). This study analyzed three specific program options in this DSM resource class:

T OU and Time

- of

- Day (TOD) programs generally operate based on two

- or three

- tiered,

time

- differentiated tariff s tructures , which charge fixed prices for usage during different blocks of time (typically on

- and off

- peak prices by season). TOU rate design seeks to more closely reflect marginal cost s of generating and delivering power . The Cadmus

team analyzed the pote ntial for using TOU rates in the residential and irrigation sector s ; in most cases, C&I time

- variant rates have already been in place within the c ompany’s

service area ; hence, the study did not further assess additional incremental opportunit ies

.

C PP, or e xtreme time

- of

- day pricing, refers to programs seeking to reduce system demand by encouraging customers to reduce loads for a limited number of hours during the year. During such events, customers may curtail their usage or pay substantially higher

- than

- st andard retail rates. T his program targets large C&I customers as a n addition al component to existing TOU rate structures

.

DBB or Demand Bidding programs (such as PacifiCorp’s Energy Exchange Program) are arrangements where a utility offers payments to customers for voluntarily reducing their demand when requested by the utility. B id amount s generally depend on market prices

, published by the utility ahead of the event, coupled with the customer’s ability to curtail use during the hours requested. R eduction level s achieved can be verified using an agreed

- upon baseline usage level

, specific to the participating customer. T his program

targets large C&I customers.

T he 2007 and 2011 A ssessments analyzed two additional resources : re al

- time pricing ( RT P ) and thermal energy storage (TES)

. The current study did not conduct additional analyses of these resource options for two reasons :

RTP is considered a competing , less common, alternative to other price

- based options

, such as CPP

, and thus is not expected to incrementally contribute to overall potential.

P reliminary research indicated that there has been little or no change in TES technologies

since the 2011 Assessment

, and the option continues to be a high

- cost resource

. 16



## Assessment Methodology

General Approach
The study based its methodology for estimating Class 1 and 3 DSM resource potentials on a hybrid top

- down and bottom

- up approach. T he approach began with utility system loads, disaggregated into sector, segment, and applicabl e end uses. For each Class 1 and 3 DSM program (or program component) studied , potential impacts were first assessed at the end

- use level. E nd

- use load impacts were then aggregated to obtain estimates of technical potentials. Market factors, such as likely program and event participation levels, could then be applied to

16 The 2011 Assessment found TES costs to be over $250/kW per year.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 19 

### technical potentials to obtain estimates of market potentials. G eneral analytic steps involved in estimating market potential ( excepti ng the r esidential and small commercial DLC program)

fol low below.

1. Define customer sectors, market segments, and applicable end uses . The first step in estimating the load basis was to d efine customer sectors, customer segments, and applicable end uses , similar to the energy

- efficiency study (described in the next section)

. System lo ads were disaggregated into four sectors: residential, commercial, industrial,

and irrigation . Each sector was further broken down by state, market segment ( see Table 5 ), and end use ( such as cooking, cooling, heating, heat pumps, HVAC, lighting, plug load, refrigeration, space heat

, and hot water heating). 17



### Table 5 . Capacity

- Focused An alysis of Customer Sectors and Segments

Residential Commercial Industrial Irrigation
Single

- Family Grocery Agriculture (non

- irrigation) Irrigation

Manufactured Health Chemical Manufacturing
Multifamily Large Office Electronic Equipment Manufacturing

Large Retail Food Manufacturing
Lodging Industrial Machinery

Miscellaneous Lumber Wood Products

Restaurant Mining

School Miscellaneous Manufacturing

Small Office Paper Manufacturing

Small Retail Petroleum Refining

Warehouse Primary Metal Manufacturing

Stone Clay Glass Products
Transportation Equipment Manufacturing

Wastewater

Water



### 2. Compile utility

- specific sector/end

- use loads

. Reliable estimates of Class 1 and 3 DSM resource potentials depend on the correct characterization of sector, segment, and end

- use loads. Load profiles were developed for each end use, and contributions to system peak

of each end use was determined based o n end

- use load shapes.

3. Screen customer segments for eligibility. This step involved screening customer
segments for applicability of specific Class 1 and 3 DSM resource strategies. For example, only customers with maximum monthly demand of at least 1,000 kW were assumed eligible for the critical

- peak pricing program.

17 End

- use segmentation was based on the Class 2 DSM analysis. As the scope of the Class 2 DSM assessment did not include Oregon, Cadmus used California’s end

- use segmen tation, adjusted for Oregon’s equipment saturation, as a proxy. Equipment saturation data derived from PacifiCorp’s Energy Decisions Surveys in Oregon. Oregon

- specific data was used for segmentation within each sector.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 20 

### 4. Estimate impacts of current programs

. Class 1 load impacts were derived from PacifiCorp’s evaluation reports. Class 3 impacts were estim ated by analyzing likely effects on electricity consumption from changes in rate structure, obtained from secondary sources, described below.

5. Estimate technical potential

. Technical potential for each Class 1 and 3 DSM resource program is assumed to be a function of customer eligibility in each class, affected end uses in that class, and the expected strategy impact on targeted end uses. Analytically, technical potential ( TP ) for each demand

- response program option ( p) wa s calculated as the sum of impacts at the end

- use level ( e )

, generated in customer sector ( s ) by :

and

where,

LE

ps 

### (load eligibility) represents the portion of customer sector ( s ) loads (MW) applicable for program option ( p ), referenced as ―Eligi ble Load‖ in the program assumptions.

LI pes 

### (load impact) is the percentage reduction in end

- use load ( e ) for each sector ( s ) resulting from the program ( p ), referenced as ―Technical Potential as % of

Load Basis‖ in the program assumptions.

6. Estimate market potential

. Market potential account s for customers’ ability and willingness to participate in capacity

- focused programs

, subject to their unique business

or household priorities, operating requirements, and economic (price) considerations.

M arket po tential estimates derived from adjusting the technical potential by two factors: expected program participation rates (the percentage of customers likely to enroll in the program) and expected event participation rates (the percent age of customers who will participate in a demand response event

— appl icable to programs such as the i rrigation DLC program

, where customers can opt out of events)

. Market potential for the program option ( M P p 

### ) was calculated as the product of technical potent ial for the customer sector ( s ), program participation (sign

- up) rates ( PP ps 

### ), and expected event participation ( EP ps 

### ) rates:

For each capacity

- focused program
, projected sign

- up rates for all customer segments

were informed by sec ondary research , described in the program assumptions

, as well as

on PacifiCorp ’s past program experience. 18

18 Appendix A

- 1 provides a list of s econdary sources used in this analysis.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 21 

### P rojected potential for Class 1 DSM products inclu ded PacifiCorp’s current program offerings, as the load forecast did not account for these programs ’ impacts. E xisting

Class 3 DSM offering impacts , however, reflected in the load forecast ; therefore

, market potential results in this report should be considered incremental to those PacifiCorp currently has under contract. The next section detai ls the methodology for estimating impacts of existing Class 3 DSM offerings.

7. Estimat e c osts and develop s upply c urves

. The levelized cost ($/kW

- year) of each program option was calculated using estimates of program development, technology, incentive, ongoi ng maintenance, administration, and communications costs. Administrative costs for all programs were based on the assumption that a f ully loaded FTE costs $150,000 per year ($72/hour). For nonresidential load curtailment and DBB

programs, costs wer e calculated at the system (rather than state) level

, as suming events

would be called system

- wide

. R emaining programs , on the other hand, were assume d to be implemented at the state level.



## DLC

Residential and small commercial DLC proves unique in that, unlik e other demand response options, it affects specific end uses and equipment (e.g.

, air conditioner s )

. T herefore

, market potential may be quantified more directly as the product of four variables:

1. N umber of customers

.

2. Expected per unit (kW) impact s.

3. E quipm ent saturation rate

.

4. E xpected participation

.

Derivation of Per

- Unit Impacts

De spite the large number of DLC programs currently in operation

, and the relatively large number of evaluation studies of these programs, estimates of end

- use impacts tend to vary a great
deal

. DLC impacts depend on a number of program design parameters

, such as : typical equipment size/ capacity, cycling strategy, event time and duration

, local climate , and measurement and verification protocols . A recent ESource survey of 22 DLC air conditioning

programs found average per

- unit load impacts rang ing from 0.75 kW (Alliant Energy) to over 1.5 kW ( Commonwealth Edison). 19



### P ac ifiCorp already operates a large DLC program in its Utah service area. Measurement of

program impacts has shown a n average reduction of 1 kW per unit. Indexing per

- unit impacts to

Utah allowed estimation of p er

- unit impacts for other PacifiCorp service jur isdictions using the following procedure

.

As PacifiCorp system peaks correlate highly to Utah weather, t he average temperature for a representative location in each state was calculated for Utah’s 50 hottest hours

, based on TMY3

19 E Source. Hot or Not? DLC Program Benchmarking

. Focus Report EDRP

- F

- 41.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 22 

### (typical mete o rological year) hourly data

. Manual J , the protocol used to size air conditionin g equipment, was used to derive equipment design temperatures ( the top 1%) for each state and equipment capacities derived from the Simple Energy Enthalpy Model ( SEEM ) runs com pleted

for the Class 2 DSM analysis

. The study adjusted t he 1 kW impact per switch used in Utah by

the ratio of system peak to design temperature and air conditioner capacity ; per switch kW impact s for the other five states were estimated

. Appendix A

- 3 provides a summary of assumptions and savings per switch by st ate

.

Equipment Saturation Rates Equipment saturation represents the percentage of customers who were eligible for participati on in the program (i.e., to participate in the air conditioning DLC program, a customer had to have a central air conditioner or heat pump) . PacifiCorp’s most recent Energy Decisions S urveys provided information on equipment saturation levels in each jurisdiction

. 20



### Expected Participation The study based e xpected program participation rates on PacifiCorp’s experience, utility reports

, and national sources, particularly A National Assessment of Demand Response Potential and its updated results for states in the Western Area Coordinating Council (WECC). 21 

### Table 17 provides d etails on DLC program participation rates

. 

## Current Programs and Product Offerings

Class 1 DSM
PacifiCorp currently offers Class 1 DSM programs in b oth Utah and Idaho. The Cool Keeper Program, in Utah, serves as one of the country’s most successful residential and small

commercial DLC A ir C onditioning (DLC AC) programs, with up to 121 MW under management (temperature dependent) . The Irrigation Load Control Program, offered in both Utah and Idaho,

also has seen very successful participation levels in both states. Currently, PacifiCorp has up to
171 MW and 38 MW (realized load at dispatch) in Idaho and Utah, respectively. As discussed in

the meth odology section, the market potential assessment results for the DLC programs include current program impacts identified in this study

.



## Class 3 DSM
PacifiCorp currently offers several rate structures to help manage customer usage. These include : inverted b lock structures for residential customers and TOU structures for residential and C&I

customers. 22 

### As these programs ’ impacts have been captured in PacifiCorp’s actual and

20 The most recent Energy Decisions Survey were conducted in 2006 with residential customers and 2007 with

commercial customers.

21 See A Nat ional Assessment of Demand Response Potential , Staff Report, Federal Energy Regulatory Commission, June 2009. See Also WECC 20

- Year Demand Response Forecast , Prepared by the Brattle Group for Lawrence Berkeley National Laboratory, June 2012.

22 Program off

erings vary by state. In some cases, participation is mandatory.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 23 

### forecasted sales, identified potential resulting from analyses of Class 3 DSM products is

incremental to that achieved through existing rate structures.

R esidential inverted block structures increase the rate ($/kWh) for energy as usage increases. These rates are mandatory for all residential customers in all six of PacifiCorp’s s tate s . The pricing structure varies by jurisdiction

, with increasing prices starting at 400 kWh per month in Utah to 1,000 kWh per month in Oregon. Utah has a second price threshold

, start ing at 1,000 kWh per month

, while California’s incremental tier varies by season, county

, and whether the

customer uses electric heat.

The incremental price of each usage tier also varies by jurisdiction. In California, the highest block price is approximately 14 % higher than the base price

, while

, in Wyoming

, the highest

block price is more than 100% higher than the base price. O ther jurisdictions ’ top block price s range from 22 % to 5 6 % higher than the base price. C ombin ing the incremental price difference and the amount of consumption in the top tier drives the overall impact of the block rate structure

on usage.

Residential TOU rates have predominately seen subscri ption s in Idaho, with limited participation in Oregon and Utah. TOU rates vary by season in Oregon and Idaho. In Utah

, TOU rates apply only in summer months.

C&I TOU rates combin e voluntary and mandatory rates

, depending on the jurisdiction and the

customer’s size, as defined by maximum monthly demand. R ates also vary in complexity. Some

rates vary by time of use, while others add a demand surcharge for on

- peak use. R ates also vary by season.

Methodology

Rate impacts on usage can be estimated using price elasticity. Price elasticity measures either the

reduction in use due to a price increase (own

- price elasticity) or a shift in usage from peak to off

peak usage

, due t o different prices at different periods (cross

- price elasticity). E xisting literature

estimat ing price elasticities has drawn from TOU programs with a relatively short on

- peak period, generally four to six hours. PacifiCorp’s on

- peak period tends to be muc h longer, up to

15 to 16 hours for many schedules

, from early morning to late evening. The on

- peak period in rate design impacts participants’ opportunit ies to shift usage to off

- peak periods. As on

- peak periods reviewed in the current literature typically average shorter than PacifiCorp’s current design, elasticity estimated by the studies will likely overestimate impact s of PacifiCorp’s programs. Further, as elasticity estimates vary between studies

, and can change over time due to technology shifts and economic conditions

, a range of potential impacts follows

.

For this analysis, the Cadmus team relied on several recent energy price elasticity research papers. The 2006 National Ren ewable Energy Labora tory (NREL) study Regional Differences in

the Price

- Elasticity of Demand for Energy examine d own

- price elasticity across various regions

of the U nited States

. In 2008

, the Brattle Group prepared a study for the Edison Electric Institute (EEI) : Quantifying the Benefits Of Dynamic Pricing In the Mass Market

. In 2012

, Freeman,

Sullivan & Co

. evaluat ed PG&E’s TOU rates for nonresidential customers

. These latter two studies calculated the elasticity of substitution between on

- peak and off

- peak usage.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 24 

### For estimating residential impacts

, the Cadmus team relied on conventional economic theory

, which stat es consumption tends to fall as price rises. The NREL paper measured the effect of rising prices on consumption. If the percentage change in consumption falls below the percentage change in price, the good consumed is considered inelastic. Energy consumption typically falls into this category, at least in the short run. In the long run

, consumers may shift technologies, such as changing their heating fuel s , which can lead to an elastic response wherein consumption falls by an amount greater than the percentage change in price.

The NREL study found a small relationship between consumption and price. That is, demand

remains relatively inelastic with respect t o price. Further, t he study found

, in the past 20 years, this relationship has not changed significantly; analyses performed in the 1980s showed approximately the same results. These findings might imply consumers have few available options in response to changes in energy price s , and demand respond s little to changes in price

. The study used data from 1979 through 2004 and acknowledge d that energy prices declin ed (in real dollars) during this period

, which may have resulted in a tendency to reduce the elas ticity impact of price increases.

As the NREL study found regional differences in elasticity , the study applied NREL regional high and low

, own

- price

, long

- run elasticity findings of

- 0.101 to

- 0.407 for the Pacific region to PacifiCorp’s Pacific Power jur isdictions and from

- 0 .172 to

- 0 .362 for the Mountain region to PacifiCorp’s Rocky Mountain Power jurisdictions. 23 

### Although relatively minor differences emerged, the more negative low er bound for the Mountain region elasticit y reflect ed a slightly higher expected response to price

- based programs.

The Brattle Group study sought to broadly measure impacts of TOU, real

- time pricing

, and

critical

- peak pricing as a guide to deployment of advanced metering infrastructure ( AMI ) technologies. I t found a residential TOU elasticity of substitution of 0.079 to 0.090. Notably, the study analyzed a TOU program

, with an educational component and the potential for a critical peak event. Other studies have shown response s to critical

- peak pricing greate r than response s for TOU

- only programs.

The Freeman, Sullivan & Co. report focused on small to medium nonresidential customers on
PG&E’s TOU rate. The study sought to estimate TOU rate impacts on usage ; it also reviewed

current literature on TOU elasticities of substitution , finding a range for nonresidential impacts

of 0 to 0.21. Elasticities of substitution measure the usage amount shifted from one good to a substituted good due to price. In analyzing TOU rates

, off

- peak usage substitute s for

o n

- peak usage.

The Freeman, Sullivan & Co. report also analy zed PG&E’s rates for voluntary participation of

small non residential and agricultural pumping TOU customers. While the study caution ed it was

23 An elasticity value indicates the percentage change in consumption resulting from a percentage change in price. For example, an own

- price elasticity value of

- 0.10 indicates a 100% increa se in price results in a 10% decrease in consumption (100% *

- 0.10). A substitution elasticity of 0.10 indicates a 100% relative price difference between options (on

- peak and off

- peak) results in a 10% shift from the higher price option to the lower price option.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013 March 2013

The Cadmus Group, Inc. / Energy Services Division 25 

### hampered by a lack of pre

- enrollment data and control groups constructed after the fact

, the findings remained consistent with the literature ; elasticities ranged from 0.09 to 0.32 for agricultural usage and from 0.10 to 0.24 for small commercial.

T his analysis used a range from 0.03, observed for health care facilities

, to 0.17 observed for manufacturing as the elasticity of substitution for nonresidential , non

- agricultural rates

, and 0.09 to 0.32 as the elasticity of substitution for agricultural pumping.

Estimated Load Impacts

Table 6 presents results of residential TOU and block rate analysis , with TOU impacts estimated using the cross

- price elasticity applied to on

- peak usage. The block rate impacts were estimated by a pplying the own

- price elasticity estimate to the percentage price differential between the base block rate and the higher block rate

, multiplied by usage in the higher block. 24 

### In instances where multiple inclining blocks or seasonal rates occurred , the ela sticity estimate was applied to usage in each block or season individually. As discussed in the methodology section, market potential assessment results for Class 3 DSM programs are incremental to current program impacts

, as shown below.

C oincident MW impact is derived from estimated MWh impacts of residential TOU and inclining block rates

, using the same whole

- house hourly load shapes and peak coincidence

factor s used in the rest of the Class 1 and 3 DSM potential analysis

. R esults suggest ed existing

i nverted block and TOU rates lowered on

- peak usage from 1. 6 % to 4. 0 % on average across PacifiCorp’s six jurisdictions, resulting in 4 7 MW to 1 25 MW of reduc ed demand during system peak periods

.

Based on the methodology, Idaho proved to be the jurisdiction with the highest percentage of

usage on

- peak, exhibit ing the highest elasticity response for TOU rates. Jurisdictions with the largest differential between base price and incremental block price or lower block cutoffs exhibited the largest percentage load reduction. For example, Wyoming’s higher

- priced tier begins at 500 kWh

, priced more than 100% higher than the base ti er. Similarly, Washington’s higher

- priced tier begins at 600 kWh

, priced 58% higher than the base tier. At the other end of the spectrum, Oregon, California

, and Utah have highest

- priced tiers beginning at 1,000 kWh

, with relatively lower differentials.

24 Usage includes line losses.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 26 

### Table 6

. Estimated Impacts of Existing Residential Class 3 DSM Resources

Description State Participating
Customers * Enrolled

Loads (MWh) * * MWh Shifted o r Saved

Due t o Rate Coincident Peak k W Impact Percent of Estimated

Baseline Consumption
Shifted or Saved

Low High Low High Low High

T OU (optional) Utah 335 262 12 14 3 3 4. 5 % 5. 1 %

Oregon 1,281 3,898 311 355 58 66 7.4 % 8.3 %

Idaho 14,290 130,294 16,849 19,195 1,896 2,160 11.5 % 12.8 %

Subtotal 15,906 134,454 17,172 19,564 1,957 2,229 11.3% 12.7%

Inverted rat e pricing (mandatory) Utah 706,948 7,314,347 61,289 128,992 12,940 27,235 0. 8 % 1. 7 %

Wyoming 110,089 1,181,202 114,093 240,127 17,054 35,893 8.8 % 16.9 %

Oregon 474,810 6,025,556 18,518 74,622 3,420 13,780 0.3% 1. 2 %

Washington 104,004 1,789,050 57,658 232,347 10,647 42,905 3. 1 % 11.5 %

California 35,681 440,299 2,243 9,037 252 1,015 0. 5 % 2. 0 %

Idaho 43,198 487,948 9,755 20,532 1,098 2,311 2. 0 % 4. 0 %

Subtotal 1,474,720 17,238, 402 263,557 705,657 45,411 123,138 1.5% 3.9%

Total System 1,490,636 17,372,855 280,730 725,221 47,367 125,367 1.6% 4.0%

* As of December 31, 2011

* * Residual on

- peak portions of TOU loads and actual Inverted Rate Pricing loads after impacts o f respective pricing structures , calendar year 2011

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 27 

### Table 7 presents the results of the nonresidential TOU rate analysis. I mpacts were estimated by multiplying the substitution elasticity estimate by the percentage difference between the on

- peak

and o ff

- peak rates and by the on

- peak load yielding a gross estimate of the loads shifted. This

estimate was further adjusted by the percentage of the TOU rate that was variable. The on

- peak proportion of load and variable portion of the TOU rate was determined using billing determinants provided by PacifiCorp.

As in the residential sector, t he coincident MW impact was calculated from the estimated MWh impacts

, using the peak coincidence factors used in the rest of the Class 1 and 3 DSM potential analysis

. Our analysis suggests 2.0 % to 10.2 % of the eligible MWh was reduced due to the TOU

rates

, resulting in a reduction between 2 5 MW and 1 40 MW in coincident peak demand.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 28



### Table 7

. Estimated Impacts of Existing C ommercial and I ndustrial Class 3 DSM Resources

Rate Class Schedule (M

- Mandatory,

V

- Voluntary) Participating

Customers* Enrolled

Loads (MWh) ** MWh Shifted or

Reduced Due to

Rate Coincident kW

Impact Percent of Estimated

Baseline Consumption Shifted
or Saved

Low High Low High Low High

General Service

- Large, ≥ 1,000 kW Washington (Sch.47T)

- M 1 1,403 9 51 2 10 0.6% 3.5%

General Service

- Large, ≥ 1,000 kW Washington (Sch,48T)

- M 59 141,345 955 5,409 192 1,088 0.7% 3.7%

General Service

- Large >= 500 kW California (Sch. AT48)

- M 19 55,429 161 910 23 131 0.3% 1.6%

General Service

- Distribution Voltage, < 15,000 kW (35A = farm) Idaho (Sch. 35/35A)

- V 3 62 1 5 0 1 1.3% 7.1%

General Service

– Large, Partial Requirements, ≥ 1,000 kW Wyoming (Sch.33)

- M 9 324,737 1,063 6,024 214 1,212 0.3% 1.8%

General Service

– Large, >= 1,000 kW Wyoming (Sch.46)

- M 81 328,746 1,972 11,176 397 2,249 0.6% 3.3%

General Service

– Large, Transmission Delivery, ≥ 1,000 kW Wyoming (Sch.48T)

- M 26 592,518 4,288 24,299 863 4,889 0.7% 3.9%

General Service

- < 1,000 kW Utah (Sch. 6A )

- V 2,195 163,251 7,559 42,832 1,085 6,149 4.4% 20.8%

General Service

- < 1,000 kW Utah (Sch. 6B)

- V 2,195 137,737 2,663 15,089 382 2,166 1.9% 9.9%

General Service

- Large, ≥ 1,000 kW Utah (Sch. 8)

- M 274 881,718 25,507 144,539 5,132 29,083 2.8% 14.1%

General Service

- High Voltage Utah (Sch. 9 / 9A)

- M 158 1,734,206 60,338 341,915 12,141 68,798 3.4% 16.5%

Agricultural Pumping Utah (Sch. 10/ TOD [1]option)

- V 251 13,960 3,289 11,695 969 3,444 19.1% 45.6%

Back

- Up, Maintenance, and Supplementary Power Utah (Sch. 31)

- M 4 38,146 1,153 6,532 232 1,314 2.9% 14.6%

General Service

- Small Nonresidential Oregon (Sch. 23 / 210)

- V 274 1,278 175 990 25 142 12.0% 43.7%

Agricultural Pumping Oregon (Sch. 41 / 210)

- V 58 431 54 190 16 56 11.0% 30.6%

General Service

- Large, ≥ 1,000 kW Oregon (Sch. 47)

- M 5 95,765 959 5,432 193 1,093 1.0% 5.4%

General Service

- Large, ≥ 1,000 kW Oregon (Sch. 48)

- M 211 1,748,675 16,087 91,161 3,237 18,343 0.9% 5.0%

Total 5,823 6,259,407 126,230 708,249 25,102 140,169 2.0% 10.2%

* As of December 31, 2011

** Residual on

- peak portion of TOU loads after impacts of TOU pricing

, calendar year 2011

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 29 

### Table 8 summarizes the estimated impact of existing residential and commercial TOU and block rates. The estimate is presented as a range due to the variability in the underlying assumptions

, includin g the own

- price and cross

- price elasticities and the coincidence factor. These impacts are embedded in current customer usage and range from a low estimate of 72 MW to a high estimate

of 2 66 MW

. As discussed in the methodology section, results of the marke t potential assessment for the Class 3 programs are incremental to the current program impacts

,

as shown below

.

Table 8

. Summary of Impacts of Existing Class 3 DSM Resources

Description Enrolled

Loads (MWh) * MWh S hifted or

R educed D ue to R ate Coincident k W Impact Percent of Estimated

Baseline Consumption
Shifted or Saved

Low High Low High Low High

Res idential 17,372,855 280,730 725,221 47,367 125,367 1.6% 4.0%

C&I 6,245,016 122,888 696,364 24,118 136,669 1.9% 10.0% Irrigation 14,391 3,343 11,885 984 3,500 18.8% 45.2%

Total 23,632,263 406,960 1,433,470 72,470 265,536 1.7% 5.7%

* Residual on

- peak portion of TOU loads and actual Inverted Rate Pricing loads, after the impacts of the respective pricing

structures , calendar year 2011

.



## Class 1 and 3 Resource Potential

Table 9 shows the estimated market potential ( at the generat or) during system peak hours for

each of the Class 1 and 3 DSM program s

. Table 10 show s the estimated potential by sector (residential, commercial, industrial, and irrigation ) for each of the two territories and the entire

system

. Class 1 DSM products include current program impacts

, while Class 3 produc ts are
incremental opportunities above PacifiCorp’s current offerings.

Based on PacifiCorp’s peak demand forecast in 2032, the Rocky Mountain Power service territory will account for approximately 70% of the system peak demand. Thus , the Pacific

Power ser vice territory has a substantially lower market potential (136 MW) than the Rocky

Mountain Power service territory ( 53 3 MW )

. Additional factors c ontributing to the lower potential in the Pacific Power service territory include : lower temperatur e s during system peak ; lower saturation s of cooling equipment (affecting the DLC AC program) ; and smaller i rrigation pumps (affec ting the i rrigation DLC program).PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 30 

### Table 9

. Class 1 and 3 DSM Market Potential (MW in 203 2 ) by Program *

Resource Class Program Market Potential Rocky Mountain

Power Pacific Power PacifiCorp System

Class 1 DSM DLC Air Conditioning 144 28 172

DLC Water Heat ing 8 14 22 Irrigation Load Control 210 11 221

Load Curtailment 125 64 189

Subtotal 488 116 604

Class 3 DSM Demand Buyback 14 5 19

Residential TOU 19 7 25 Irrigation TOU 11 7 18

CPP 2 1 3

Subtotal 45 20 66

Class 1 and Class 3 DSM Total 533 137 670

* Hours vary by program and may not reflect actual available reduction s during system peak

.



### The residential and irrigation sectors exhibit the highest e stimated market potential for Class 1

and 3 DSM resources

. T he majority of this potential , however, already is under contract through PacifiCorp’s Cool Keep er (Utah) an d Irrigation Load Control (Idaho and Utah) programs (12 1 MW and 209 MW, respectively)

. The n onresidential load c urtailment program, which applies to both the C&I sectors, has the most remaining potential ( 189 MW ) of any Class 1 DSM

resource

. As c oincident peak impacts are based on avera ge impacts of individual programs during peak hours , as defined by the program, the Class 1 and Class 3 DSM program potentials are not truly additive.

Table 10

. Market Potential (MW in 2032) by Sector *

Resource Class Program Market Potential Rocky Mountain

Power Pacific

Power PacifiCorp

System

Class 1 DSM Residential 151 41 192

Small Commercial 1 1 2
Large Commercial 55 42 97
Irrigation 210 11 221

Industrial 70 22 92

Subtotal 488 116 604

Class 3 DSM Residential 19 7 25

Small Commercial

- - - Large Commercial 5 4 8
Irrigation 11 7 18

Industrial 12 2 14

Subtotal 45 20 66

Class 1 and Class 3 DSM Total 533 137 670

* Hours vary by program and may not reflect actual available reduction s during system peak

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 31 

## Resource Costs and Supply Curves

Resource acquisition costs fall into several categories

, including:

Infrastructure

Administratio n
Maintenance

D ata acquisition

Hardware costs Marketing expenses
Incentives 25



### Estimates for each type of expense categor y withi n each program were developed using PacifiCorp’s program data and experience and using secondary sources
, such as reports on similar programs offered by other utilities

. 26 

### In developing estimates of levelized costs, program expenses were allocated annually over the expected program life cycle and then discoun ted by PacifiCorp’s cost of capital (6.88 % )

. 27 

### The ratio of this value and the discounted kW reduction produced the levelized per

- kW cost for each resource in each state

.

Table 11 and Table 12 display the Class 1 DSM market potentia l and per

- unit ($/kW

- year) costs

for each program in each state

. T he i rrigation DLC program is e xpected to be the least expensive

program option, with levelized cost s ranging from $5 1 /kW

- year to $6 4 /kW

- year

. Per

- u nit

resource costs for the nonresidential l oad c urt a i l ment p rogram are estimated at $ 69 /kW

- year for

both service territories ( as events are assumed to be called on a system

- wide basis )

. The

r esidential DLC AC program exhibit s levelized cost s ranging from $ 72 /kW

- year in Utah to $1 6 4 /kW

- year in Idaho

. The assumed per

- switch kW impact drives t his variation in cost , with these impacts highest in Utah (1 kW) and the lowest in Idaho (0.43 kW). 28 

### Both the small

commercial and water heating DLC programs would rely on the existence of the residential DLC

program ; therefore

, program costs must be considered in addition to residential DLC costs.

25 As i ncentives for Class 1 and Class 3 DSM are treated as resource acquisition costs (rather than transfer

payment s), they are included in the levelized cost calculations.

26 A single full

- time equivalent (FTE) emp loyee was assumed to cost $150,000 per year. All costs based on a specific number of FTE or set amount of staff time were calculated using this assumption.

27 Class 1 resources were assumed to have a 10

- year program life, based on the average length of imp lementation contracts, while Class 3 resources were assumed to have a 20

- year program life, based on the expected useful

life of an interval meter.

28 See Appendix A

- 3 for details.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 32



### Table 11 . Class 1 DSM: Market Potential by State (MW in 203 2 )

State DLC AC

-

Residential DLC Water

Heat

- Residential DLC AC

-

Small
Commercial DLC Water

Heat

- Small
Commercial Irrigation

DLC Nonresidential

Load
Curtailment Total

Pacific Power

California 1 0.5 0.03 0.02 4 2 8
Oregon 18 10 1 0.2 3 46 78
Washington 8 3 0.1 0.04 4 16 31

Subtotal 27 13 1 0.3 11 64 116
Rocky Mountain Power

Idaho 1 0.3 0.03 0.01 172 9 183

Utah 139 7 1 0.1 38 91 276
Wyoming 3 1 0.2 0.02 0 25 29

Subtotal 143 8 1 0.1 210 125 488

Total 170 21 2 0.4 221 189 604



### Table 12 . Class 1 DSM: Levelized Costs by State ($/kW

- year)

State DLC AC

-

Residential DLC Water

Heat

- Residential DLC AC

-

Small
Commercial DLC Water

Heat

- Small
Commercial Irrigation

DLC Nonresidential

Load
Curtailment

Pacific Power

California $94 $63 $75 $63 $64 $69
Oregon $123 $64 $99 $64 $61 $69
Washington $94 $64 $75 $64 $64 $69

Subtotal* $114 $64 $93 $64 $63 $69
Rocky Mountain Power

Idaho $164 $63 $131 $63 $51 $69

Utah $72 $64 $57 $64 $51 $69
Wyoming $85 $64 $68 $64 $64 $69

Subtotal* $72 $64 $61 $64 $51 $69

Total* $79 $64 $73 $64 $52 $69

* Subtotals and total s are weighted by market potential

.



### For Class 3 DSM resources, programs for C&I and irrigation customers are estimated to be less expensive than for residential customers

. Due to the eligibility criteria, customers participating in C&I programs already would have interval meters in place, while residential customers would

need to have interval meters installed

, thereby incurring an additional c ost to the residential

programs

. Critical

- peak p ricing ( ranging from $9 /kW

- year in Oregon and Utah to $96 /kW

- year in California ) is the least expensive pricing program

, as it does not require incentives or meter

costs. Irrigation TOU is slightly more expensive ( rangi ng from $20/kW

- year in Idaho to $97 /kW

- year in Washington and Wyoming )

, as interval meters must be installed for all new participants

. Demand B uyback, at $26/kW

- year for all states ( assuming events would be called

system

- wide) , also offers a relatively low

- cost option.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 33 

### The residential TOU program costs more due to the small load reductions compared to the installed technology (meters) and to ongoing program maintenance costs (communications and administration).

Table 13

. Class 3 DSM: Market Potential by State (MW in 203 2 )

State Residential

TOU Irrigation

TOU DBB CPP Total

Pacific Power

California 0.3 2 0.1 0.03 2 Oregon 4 4 4 1 13 Washington 2 2 1 0.2 5

Subtotal 7 7 5 1 20 Rocky Mountain Power

Idaho

- 9 0.4 0.1 10

Utah 17 1 9 1 28 Wyoming 2 0.3 4 1 7

Subtotal 19 11 14 2 45

Total 25 18 19 3 66



### Table 14 . Class 3 DSM: Levelized Costs by State ($/kW

- year)

State Residential

TOU Irrigation

TOU DBB CPP

Pacific Power

California $347 $40 $26 $96 Oregon $286 $62 $26 $9 Washington $117 $97 $26 $25

Subtotal * $231 $66 $26 $14 Rocky Mountain Power

Idaho N/A $20 $26 $38

Utah $124 $58 $26 $9 Wyoming $195 $97 $26 $10

Subtotal * $130 $25 $26 $11

Total * $157 $41 $26 $12
* Subtotals and totals are weighted by market potential.



### Appendix A

- 2 provides s upply curves for Class 1 and Class 3 DSM , which represent the quantity of each resource (cumulative MW) that can be achieved at or below the estimated per

- unit cost at any point.



## Class 1 DSM Resource Results by Program Option

Residential and Small Commercial DLC

The DLC resource assessed in this study would allow PacifiCorp to manage cooling and water heating loads during peak periods. Customers enroll ing in the program have a switch installed on their cooling equipment (either a central air conditioner or a heat pump) ; this cycles the unit on and off during a program event. Utility staff call e vents , which may last up to four hours. The utility compensates participating c ustomers with an incentive ; both residential and small

commercial customers may qualify for the program.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 34 

### Currently, PacifiCorp has approximate ly 121 MW of load under contract from its Cool Keeper

air conditioner Progra m in Utah. Based on the Cadmus team’s research on similar programs offered by other utilities, PacifiCorp may have saturated the existing market ; additional potential may derive from load growth over the 20

- year period and not from an increase in the participation rate . The Cadmus team estimates a total of 143 MW of potential in the Rocky Mountain Power territory, including that currently under contract in Utah, and 27 MW in the Pacific Power territory.

Table 15 displays state

- specific total and incremental market potentials (total potential less impacts of current programs, w h ere offered) . As shown

, Utah has the largest amount of poten tial

in 2032. Overall, the small commercial sector offers limited savings

, though costs will likely be

lower than in the residential sector due to small commercial customers

, with larger cooling units,

realiz ing 25% higher per

- switch impacts

.PacifiC orp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 35 

### Table 15

. Residential and Small Commercial DLC Air Conditioning: Market Potential (MW in 2032) and Levelized Cost by State ($/kW

- yr )

Territory State Residential Small Commercial

Total

Market

Potential (MW) Existing

Program Impact (MW) Incremental

Market

Potential (MW) Levelized Cost

($/kW

- yr ) * Total

Market

Potential (MW) Under

Contract (MW) Incremental

Market

Potential (MW) Levelized

Cost ($/kW

yr ) *

Pacific

Power California 0.9

- 0.9 $94 0.0

- 0.0 $75

Oregon 18.4

- 18.4 $123 0.5

- 0.5 $99 Washington 7.9

- 7.9 $94 0.1

- 0.1 $75

Subt otal 27.2

- 27.2 $114 0.7

- 0.7 $93

Rocky

Mountain

Power Idaho 0.8

- 0.8 $164 0.0

- 0.0 $131

Utah 138.9 120.0 18.9 $72 0.9 0.7 0.2 $57 Wyoming 3.4

- 3.4 $85 0.2

- 0.2 $68

Subt otal 143.1 120.0 23.1 $72 1.1 0.7 0.4 $61

Total 170 120 50 $79 1.7 0.7 1.1 $73

* Subtotals and total s are weighted by market potential

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 36 

### Table 16 and Table 17 present d etailed assumptions about program cost s , participation rates

, and

other variables used in the analysis

.

Table 16

. Residential and Small Commercial DLC Air Conditioning: Program Basics

Program Element Assumption Customer sectors eligible All residential and small commercial market segments.

End uses eligible for program Central cooling, including heat pumps. Customer size requirements Residential and small commercial customers Applicable hours Top 50 summer system hours



### Table 17 . Residential and Small Commercial DLC Air Conditioning :

Planning Assumptions

Inputs Value Source(s) or Rationale

Annual attrition 7% Based on actual program experience; provided by Rocky

Mountain Power. Annual utility administrative costs $300,000 Assumes two FTE to run the program system

- wide.

Technology c ost (per new participant) $60 per switch

, and $80 for

installation

labor Based on vendor bids, research, and informal communication

with vendors.

Marketing c ost (per new participant) $36 Assumes 1/2 hour of staff time.

Annual v endor c osts (%) 15% Vendor administration of the program is expected to be 15%

of all the utility’s non

- administrative costs (technology, marketing, communication, incentives)

. This assumption is
based on research of vendor bids and informal

communication with vendors. The cost includes maintenance, administrative labor, and dispatch software.

Communication (annual costs per participant) $7 Accounts for monthly per

- customer communications of a one

way transmission system. Assumed to be one

- half of the costs experienced by the PacifiCorp Idaho Irrigation system,

which utilizes a two

- way system.

Incentives (annual costs per participant) $20 The Utah Cool Keeper Program incentive amount of $20 is consistent with other programs across the country

.

Saving s per switch Varies by state

and sector Savings per switch var y by state due to differing loads and

climatic conditions. Utah saves approximately 1 kW per switch, as reported in the 2011 Cool Keeper Program Impact

Evaluation. Other states are indexed to Utah

, adjusted by design temperatures during the top 50 hours. Assumes

commercial customers save 25% more per switch due to larger units

. Savings per residential switch by st ate can be found in Appendix A

- 3

.

Program p articipation Residential: 26% UT, 12.5% CA, ID OR, WA, WY
Small

Commercial:
3.5% all states Participation is assumed to be 12.5% of all eligible customers

for all states except Utah, which is expected to have a 26% particip ation rate among eligible customers (The Brattle Group, WECC 20

- year Demand Response Forecast 2012).

F indings from ESource and FERC support this

, with participation found to be generally between 5% and 25% of total customers, before adjusting for eligibility. Participation
for small commercial customers is assumed to be 3.5% for all states, as supported by ESource findings, which show program participation rang ing fro m 1.4% to 28%

.

Event p articipation 100% Event participation is assumed at 100%

, as it is captured in average per unit impacts.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 37 

### The study analyzed a water heating component as an addition to the DLC AC program. Though

this option is available to residential and small commercial customers, customers must have air

conditioner s enrolled in the program and have electric water heat to qualify for participat i on

. I n conjunction with the DLC AC program

, this option would add an estimated

8 MW and 14 MW of market potential in Rocky Mountain Power ’s and Pacific Power ’s service

territor ies , respectively , as shown in Table 18

.

Utah and Oregon offer the highest potent ial due to their large customer base s, compared to the

other four states

. The levelized cost remains the same across the residential and small

commercial customer classes

, given each DLC switch save s an assumed 0.5 kW

, regardless of

the customer class or s tate. Reported levelized costs remain relatively low, as the air conditioning component bears much of the DLC program costs. Levelized costs for a standalone water heating DLC program would be considerably higher.

Table 18

. Residential and Small Commercial DLC Water Heating :

Levelized Cost by State ($/kW)

Territory State Residential Small Commercial

Total Market Potential (MW) Levelized Cost

($/kW

- yr ) * Total Market

Potential (MW) Levelized Cost

($/kW

- yr ) *

Pacific Power California 0.5 $63 0.02 $63

Oregon 9.6 $64 0.21 $64 Washington 3.4 $64 0.04 $64

Subt ota l 13.5 $64 0.27 $64

Rocky Mountain

Power Idaho 0.3 $63 0.01 $63

Utah 6.9 $64 0.08 $64 Wyoming 0.5 $64 0.02 $64

Subt otal 7.8 $64 0.11 $64

Total 21.2 $64 0.38 $64 *Subtotals and totals are weighted by market potential.



### Table 19 and Table 20 show d etailed assumptions about programs cost s , participation rates

, and

other variables

.

Table 19 . Residential and Small Commercial DLC Water Heat ing : Program Basics
Program Element Assumption Customer sectors eligible All residential and small commercial market segments

. End uses eligible for program Electric hot water heating, exclud ing heat pump water heaters. Program run s in conjunction with the DLC AC program.

Cu stomer size requirements Residential and small commercial customers

. Applicable hours Top 50 summer system hours

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 38 

### Table 20 . Residential and Small Commercial DLC Water Heat Planning Assumptions

Inputs Value Source(s) or Rationale

Annual attrition 7% Based on actual program experience; provided by Rocky

Mountain Power for AC DLC

. Annual utility administrative costs $0 FTE costs are covered by the DLC AC program.

Technology cost (per new participant) $60 per switch plus $40 for

installation

labor An additional control for each water heater is consistent with

best practices ; 50% additional labor is required for

installation.

Marketing cost (per new participant) $9 Assumes 1/8 hour of staff time

.

Annual vendor administrative costs (%) 5% Vendor administration of the program is expected at 5% of all

non

- utility administrative costs. This assumption derives from

research of vendor bids and informal communication s with vendors. The cost includes maintenance, administrative labor, and dispatch software. Communication (annual costs per participant) $0 Communication is covered by the DLC AC program.

Incentives (annual costs pe r participant) $10 Consistent with other programs offered across the country ( e.g.

, Kentucky's Touchstone Energy Cooperatives provides an additional $10 credit for water heat )

. Savings per switch 0.5 kW Assumes an average annual impact of 0.5 kW per switch

, based on BPA evaluation of the summer WH DLC pilot.

Program participation (%) Residential: 26% UT, 12.5% CA, ID OR, WA, WY
Small
Commercial:
3.5% all states Water heating program participation is assumed at the same

rate of program sign

- up for the DLC AC program, but

accounts for saturation s of electric hot water heating for
customers with central AC. It is calculated as the product of the percent of customers with electric water heating and central cooling and the AC DLC participation rate.
Sa turations of electric hot water heating can be found in Appendix A

- 3

. Event participation 100% Event participation is assumed to be 100% as it is captured in the average per

- unit impacts.



## Irrigation Load Control

Pacifi Corp’s Irrigation Load Control p rogram s in Idaho and Utah include a scheduled

component

, where customers subscribe in advance for specific days and numbers of hours their irrigation systems may be turned off, along with a dispatchable component, such as the residential DLC program, where irrigation pumps are controlled for a four

- hour period during

each event . Under the current program, PacifiCorp can achieve 38 MW of savings in Utah and 171 MW of savings in Idaho . Although a scheduled program option remains in place, most participants ha ve transitioned to the dispatchable program option; therefore, for estimating potential, the irrigation DLC program is considered to be 100 % dispatchable, with out participants on a predetermined schedule.

Table 21 shows a market potential estimate of 11 MW for Pacific Power. For Rocky Mountain
Power, 210 MW is considered achievable (this estimate includes 209 MW available through the

current programs )

. As the program has extremely high participation rates, and recent recruitment efforts in Idaho and Utah have not produced additional participation , the additional potential

identified in these states would derive from new customers who have been acquired o ver the 20

- year period. Given its high irrigation load , the majority of the market potential (78 % ) appearsPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 39 

### available from Idaho. Despite agriculture in other states , smaller pumps are typically used and

the shorter irrigation season s offer much lower poten tial. Additionally, compared to other states, the program’s maturity in Idaho and Utah, the concentration of agricultural pumping loads

, and larger pump sizes result in lower program costs (on a per

- kW basis)

.

Table 21 . Irrigation L oad Control: Market Potential (MW in 2032) and

Levelized Cost by State ($/kW

- yr )

Territory State Total Market Potential (MW) Under Contract

(MW) Incremental Market

Potential (MW) Levelized Cost

($/kW

- yr ) *

Pacific Power California 4.5

- 4.5 $64

Oregon 2.8

- 2.8 $61 Washington 3.8

- 3.8 $64

Subt otal 11.1

- 11.1 $63

Rocky Mountain

Power Idaho 172.0 171 1.0 $51

Utah 38.2 38 0.2 $51 Wyoming 0.2

- 0.2 $64

Subt otal 210.4 209 1.4 $51

Total 222 209 12.5 $52

* Subtotals and total s are weighted by market potential

.



### Table 22 and Table 23 provides d etailed assumptions for the Irrigation Load Control program.

Table 22 . Irrigation Load Control: Program Basics
Program Name Irrigation DLC Customer sectors eligible Irrigation customers

. End uses eligible for

program Irrigation pumps

.
Cu stomer size requirements All customers with at least 25 horsepower irrigation pump ( 92% of sales CA, 100% of sales ID,
78% of sales OR, 100% of sales UT, 75% of sales WA, 82% of sales WY )

. Applicable hours Top 50 summer system hours

.



### Table 23 . Irrigation Load Control: Planning Assumptions

Inputs Value Source(s) or Rationale

Incentive

costs $23/kW Assumption based on PacifiCorp’s experience and a review of similar programs

Delivery

costs $10 ID, $10 UT

$16 OR, $18 CA, $18 WA, $18 WY Delivery costs include all administration and communication s for the program. Costs are

based on PacifiCorp's current experience and on the geographical makeup of each state. States with higher concentrations of irrigation sites have lower delivery costs.

Load class eligibility 50% CA, 100%

ID, 25% OR, 100% UT, 50% WA, 25% WY Cooler temperatures, heavy rainfall, easy access to surface water and variations in crop

type s cause a lower level of load class eligibility for Oregon, Wyoming, California

, and Washington. Additionally, irrigators are more geographically di spersed in Oregon and Wyoming

, making program delivery more difficult.

Program participation (%) 25% CA, 78% ID,

15% OR, 78% UT, 25% WA, 15%

WY Given the high share of load already under contract, the Cadmus team assumes Utah and

Idaho have hit maximum participation levels

. A more conservative participation estimate of 25%, in line with the 30% achieved by Idaho Power , was assumed for Washington and
California . Both Wyoming and Oregon have smaller pumps, different pumping configurations, better access to surface water

, and are expected to have lower participation

rates

.

Event participation (%) 94% Event participation equals the number of customers, on average, choos ing to participate in an event. Event participation was calculated by dividing the average number of opt

- outs from PacifiCorp’s 2010 Irrigation Load Control Program in Idaho by the number of participating customers.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 40 

## Nonresidential Load Curtailment
Load curtailment programs consist of contractual arrangements between a utilit y ( or a contractor working on its behalf

) and its C&I customers, which agree to curtail or interrupt their operations, in whole or part, for a predetermined period

, when requested by the utility. T his study assumed

C&I customers with a maximum monthly demand of at least 150 kW would qualify for such a

program . Currently, PacifiCorp has a rate structure in place for its largest industrial accounts that allows curtailment during utility events ; this analysis excludes such ―special contract ‖

a rrangements. However, customers w it h installed standby generation capability are considered eligible for this program

.

Rocky Mountain Power ’s service territory has an estimated 12 5 MW of nonresidential curtailment market potential, with an additional 64 MW in Pacific Power ’s service territory. Both territories have higher market potential than that estimated in the 2011 Assessment due to higher assumed program participation rates ( consistent with current national trends for similar programs administered by third

- party curtailment aggr egators and service providers )

. Table 24

shows levelized costs and market potential by state. As the study assumed the program would be implemented sy stem

- wide, the system

- level $/kW

- y ea r has been applied to all states

.

Table 24

. Nonresidential Load Curtailment: Market Potential (MW in 2032) and

Levelized Cost by State ($/kW

- yr )

Territory State Market Potential (MW) Levelized Cost ($/kW

- yr ) *

Pacific Power California 2 $69

Oregon 46 $69 Washington 16 $69

Subt otal 64 $69

Rocky Mountain Power Idaho 9 $69

Utah 91 $69 Wyoming 25 $69

Subt otal 125 $69

Total 189 $69

* Subtotals and total s are weighted by market potential

.



### Table 25 and Table 26 show d etailed assumptions for the Nonresidential L oad C urtailment

program

.

Table 25

. Nonresidential Load Curtailment: Program Basics

Program Element Assumption Customer sectors eligible All industrial and commercial market segments

. End uses eligible for program All

. Custom er size requirements 150 kW or greater

. Applicable hours Top 6 0 system hours

. *

* A 30

- hour option focusing on a narrower system peak was considered for IRP modeling. Because this curtailment would last fewer hours, the incentive per peak kW subscribed would be reduced, translating to a reduction in levelized cost of roughly 5% compared to the 60

- hour option

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 41



### Table 26 . Load Curtailment: Planning Assumptions

Inputs Value Source(s) or Rationale

Annual administrative

costs $225,000 Assumes 1 .5 FTE to run the program system

- wide

. Technology cost (per new participant) $0 Assumes customers meet ing the eligibility requirements for the program will already have interval meters in place. Marketing cost (per participant) $576/year (first year costs) $576/year (ongoing costs) Assumes 8 hours of effort by staff for initial marketing and an additional 8 hours each year for ongoing customer service.

Incentives (annual costs per participating k W ) $60/kW Based on a review of several programs

, including PG&E's Business Energy Coalition Program of $50/kW, MidAmerican of $41.6/kW, and CenterPoint Energy of $40/kW.

Overhead: first costs $150,000 Assumes 1 FTE to start up the program

.

Technical potential as %
of load basis 30% Customers shed 26.9% to 34% of load for day

- of and day

- ahead events, respectively (2010 and 2011 Statewide Aggregator

Demand Response Programs: Final Report, Christensen Associates)

.

Program participation (%) Ranges from 10%

- 30% Programs across the country experienc e participation rates from

4 .5 % (MidAmerican Energy ) to 30% (Georgia Power and Indiana Michigan Power Company)

. S ee Appendix A

- 4 for participation by

state.

Event participation (%) 95% Event participation in PJM and MidAm erican programs ranged
from 90 % to 95%

. 

## Class 3 DSM Resource Results by Program Option

Residential Time

- of

- Use Rates
Currently, PacifiCorp offers residential TOU rates in Oregon, Utah

, and Idaho. As with other Class 3 DSM products assessed in this study, the market potential the Cadmus team estimated is incremental to the impacts of the existing rates

. Approxima tel y 25% of residential customers in

I da ho are currently on the TOU rate. As the Cadmus team did not find other utilities with participation at these levels, the study assumed maximum participation has been reached . The

Cadmus team estimated a total of 19 MW of incremental market potential in the Roc ky Mountain Power territory and 7 MW of incremental market potential in the Pacific Power territory. Table 27 display s the market potential and levelized per

- unit costs by state. Costs higher than in the 2011 A ssessment reflect increases in PacifiCorp ’s meter hardware and

installation cost s

.

Table 27 . Residential TOU: Market Potential (MW in 2032) and

Levelized Cost by S tate ($/kW

- yr )

Territory State Market Potential (MW) Levelized Cost ($/kW

- yr ) *

Pacific Power California 0.3 $347

Oregon 4.3 $286 Washington 2.3 $117

Subt otal 6.9 $231

Rocky Mountain Power Idaho

- $0

Utah 17.0 $124 Wyoming 1.6 $195

Subt otal 18.6 $130

Total 25.5 $157

* Subtotals and total s are weighted by market potential

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 42 

### Table 28 and Table 29 show d etailed assumptions for the R esidential TOU program

.

Table 28

. Residential TOU: Program Basics
Program Element Assumption Customer sectors eligible All residential market segments

. End uses eligible for program All

. *

Cu stomer size requirements None

. Applicable hours S ix hours on

- peak period each summer weekday

. Rate structure Assumes a two

- tier rate structure

, with the peak rate 3 times greater than the off

- peak rate.

* T he TOU rate structure likely will not affect the c onsumption of some end uses (e.g., refrigerators)

. ―Technical Potential as % of

Load Basis‖ accounts for this.



### Table 29 . Residential TOU: Planning Assumptions

Inputs Value Source(s) or Rationale

Annual administrative

costs $15,000 Assumes the program will require 1/10 FTE for annual

administration. Technology cost (per new participant) $426 Meter costs for PacifiCorp are $133, with $293 additional

installation cost. Marketing cost (per new participant) $36 /year (first year costs) $3.6/ year (ongoing costs) Assumes 1/2 hour of staff time per year. An additional 1/20 hour per year is assumed for ongoing marketing and customer support.

Overhead: first costs $150,000 Assumes 1 FTE to design and launch the program.

Technical potential as %
of load basis 9% for OR and CA and 16% for WY, UT, ID, WA PG&E's residential pricing program shows about 16% average peak demand reduction in summer months for customers in warmer climates and 9% for those in cooler climates (Freeman, Sullivan & Co., 2011 and 2012). Additi onally, a 2005 evaluation of Pacific

Power ’ s TOU program in Oregon shows an average reduction of 8% in the summer months (Quantec LLC, Analysis of the Load Impacts and Economic Benefits of the TOU Rate Option ).

Incremental program participation (%) 0% in Idaho, 5% in all other

states Even among the top 10 IOU programs with the highest enrollment (according to FERC), more than one

- half have single

- digit participation rates. A 5% participation rate can be expected if a

reasonable effort is made. This m arket penetration rate is assumed

to be incremental to current participation in states where TOU tariff s remain in effect

, except Idaho

, where no additional participation is expected ( as previously discuss ed regarding the current Idaho program)

. Event p articipation (%) 100% Event participation is captured in the average load impact.



## Irrigation TOU Rates

A n irrigation sector TOU program is assumed to function similarly to the r esidential TOU program, where rates have been tiered to reflect high prices during system peak periods. The potential presented in this report is incremental to the impacts of PacifiCorp’s existing irrigation TOU rates in Oregon and Utah. This analysis assumes the program would be voluntary, in

contr ast to the mandatory structure analyzed in the 2011 Assessment.

Table 30 shows an estimate d market potential of 11 MW in the Rocky Mountain Power service territory, w ith an additional 7 MW in the Pacific Power territory. Though most identified potential occurs in Idaho, these numbers notably do not account for interactions with the irrigation DLC program. As discussed in Section 1, this potential decreases significantl y whenPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 43 

### considered in conjunction with an irrigation DLC program. Idaho also has the lowest implementation cost s, with costs highest in Washington and Wyoming , driven by estimated per

customer impacts.

Table 30 . Irrigation TOU: Marke t Potential (MW in 2032) and

Levelized Cost by State ($/kW

- yr )

Territory State Market Potential (MW) Levelized Cost

($/kW

- yr ) *

Pacific Power California 1.7 $40

Oregon 3.8 $62 Washington 1.8 $97

Subt otal 7.3 $66

Rocky Mountain

Power Idaho 9.5 $20

Utah 0.7 $58 Wyoming 0.3 $97

Subt otal 10.5 $25

Total 17.8 $41

* Subtotals and total s are weighted by market potential

.



### Table 31 and Table 35 show d etailed assumptions for an irrigation TOU program

.

Table 31 . Irrigation TOU: Program Basics
Program Element Assumption Customer sectors eligible Irrigation customers

. End uses eligible for program Irrigation pumping

. Customer size requir ements None

. Applicable hours 120 hours : a ssumes two o n

- peak hours each weekday

, June to August

.



### Table 32 . Irrigation TOU: Planning Assumptions

Inputs Value Source(s) or Rationale

Annual administrative costs $15,000 Assumes 1/10 FTE to run the program system

- wide. Technology cost (per new participant) $1,000 Technology costs assume $1,000 per new participant for meter

and installation costs.

Marketing cost (per new participant) $720/year (first year costs) $72/year (ongoing costs) Assu mes 10 hours of effort by staff per new participant

. An additional hour per year is assumed for ongoing marketing and customer support.

Overhead: first costs $150,000 Assumes 1 FTE to design and launch the program.

Technical potential as % of

load basis 30% Idaho Power achieved 11% and 7% in 2001 and 2002 through an Irrigation TOU Pilot program. The on

- peak rate was $0.05/kWh

, and the off peak rate was $0.014/kWh, and peak hours ranged from 1:00 pm to 9:00 pm. It is assumed

, with the shortened on

peak window of 2 hours

, customers will be able to shift a hi gher percentage of load.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 44 Inputs Value Source(s) or Rationale

Program participation (%) 13.5% CA, ID, WA, WY 12.5% OR, 4.5% UT The current participation levels in several of PacifiCorp's voluntary nonresidential Class 3 rates range from 0.37% to 9% participation, with 9% of Utah customers participating in an Irrigation TOU program. It is assumed PacifiCorp would be able to increase participation with a revised program design , using a more dramatic peak

- to

- off

- peak rate differential. Participation

rates shown are incremental to cur rent participation in states with an existing irrigation TOU rate.

Event p articipation (%) 100% Event participation is captured in the average load impact.



## Nonresidential CPP
Under a CPP program, customers receive a discount on their normal retail rates during non

critical

- peak periods in exchange for paying premium prices during critical

- peak events. A s the peak price has been determined in advance, however, customers receive some degree of certainty regarding participation costs. The basic rate structur e is a TOU tariff, with the rate using fixed prices for usage during different blocks of time (typically on

- , off

- , and mid

- peak prices by season). During CPP events, the normal peak price under a TOU rate structure would be replaced with a much higher price

, generally set to reflect the utility’s avoided supply cost during peak periods.

The Cadmus team estimates 2 MW market potential in the Rocky Mountain Power territory , with

an additional 1 MW of market potential in the Pacific Power territory The m ajority of market potential occurs in the indus trial sector, dominated by Utah, Wyoming

, and Oregon loads.

CPP cost s remain relatively low, ranging from $9 /kW

- year in Oregon and Utah to $96/kW

- year in California , as shown in Table 33

. Given the program assumption of a minimum 1,000 kW , no metering costs are included, as customers of this size already would have an interval meter. Additionally, pricing programs do not require incentive payments and have minimal

administrative costs. As with irrigation TOU, cost variation s result from the amount of load that can be reduced by a single customer (as marketing costs are tied to partici pants and not to the load reduced) as well as from costs associated with starting up the program ( assumed to be the same in each state, regardless of participation )

.

Table 33

. Nonresidential CPP: Market Potential (MW in 2032) and

L evelized Cost by State ($/kW

- yr )

Territory State Market (MW) Levelized Cost

($/kW

- yr ) *

Pacific Power California 0.03 $96 Oregon 0.91 $9 Washington 0.15 $25

Subt otal 1.09 $14

Rocky Mountain Power Idaho 0.08 $38

Utah 1.39 $9 Wyoming 0.90 $10

Subt otal 2.37 $11

Total 3.46 $12

* Subtotals and total s are weighted by market potential

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 45 

### Tabl e 34 and Table 35 show d etails on cost assumptions for the Nonresidential CPP program

.

Tabl e 34

. Nonresidential CPP: Program Basics
Program Element Assumption Customer sectors eligible All C&I market segments

. End uses eligible for program Total load of all end uses

.

Cu stomer size requirements C&I customers with maximum monthly demand greater than 1

, 000 kW

. Applicable hours Top 40 system hours

, assum ing 10 four

- hour events

.



### Table 35

. Nonresidential CPP: Planning Assumptions

Inputs Value Source(s) or Rationale

Annual administrative costs $15,000 Assumes the program will require 1/10 FTE for annual

administration

. Technology cost (per new participant) $0 Assumes customers meet ing the program eligibility requirements will already have interval meters in place.

Marketing cost (per participant) $720/year (first year costs) $72/year (ongoing costs) Assumes 10 hours of effort by staff

, valued at $72/hour. An additional hour per year is assumed for ongoing marketing and customer support.

Overhead: first costs $150,000 Assumes 1 FTE, 1/2 for Rocky Mountain Power and 1/2 for Pacific Power, to design and launch the program

.

Technical potential as % of load basis 5.0% In the 2010 C alifornia Statewide Nonresidential CPP Evaluation, program impacts ranged from 2.8 % to
5.26% of load for SCE, SDG&E and PG&E. In 2011, load impacts ranged by utility: PG&E averaged 5.9%, SCE averaged 5.7% and SDG&E averaged 5.8%.

Program participation (%) 4.0% CA, 2.4% ID, 2.7% OR, 2.1% UT, 4.5% WA,
2.4% WY CPP programs typically have low p articipation rates.
California , for example. experienced a 1.1% participation rate across the state, account ing for 2.9% of peak load enrolled. Individual utility participation

range d from 0.1% for SC E to 3.5% for PGG&E in 2005. *
PG& E’s on

- peak energy rates during High

- Price Periods

and Moderate

- Price Periods are five times and three times higher, respectively, than on

- peak energy rates during non

- event days. SCE’s High

- Price Periods and

Moderate

- Price Periods are about 9.3 times and 3.3 times higher, respectively, than on

- peak rates during

non

- event days. (Quantum Consulting 2005 Evaluation of Nonresidential Day

- Ahead and Reliability Demand Response Programs). Values are expected to vary

across states

, depending on their customer mix. For example

, certain industries ( such as mining in Wyoming ) are less likely to participate.

Event participation (%) 100% As technical potential includes customers who did and did not submit bids, there is a default event participation
rate of 100%

. *Cadmus relied on data from the 2005 California CPP programs because the programs offered then were similar in design to PacifiCorp (opt

- in), whereas currently, California only offers opt

- out programs to its commercial and industrial customers.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 46 

## Demand Buyback
Under DBB, the utility offers payments to large C&I customers for reducing their demand when requested by the utility. The customer remains on a standard rate but has the option to voluntarily bid or propose load reductions in response to the utility’s request. The bid amount generally depends on market prices posted by the utility ahead of the curtailment event, and the reduction level is verified against an agreed

- upon baseline usage level. PacifiCorp’s existing Energy Exchange is a typical D BB program.

Market electricity prices tend to be the main participation drivers in this program. PacifiCorp’s Energy Exchange program has seen minimal participation in recent years, primarily due to electricity prices (and therefore posted prices to parti cipating customers ) having been too low to spur participation. As shown in Table 36 , results from this assessment indicate 14 MW could be achieved during an event in t he Rocky Mountain Power territory . In the Pacific Power territory,

5 MW of potential will likely be achievable during any one event. As described below, these potentials assume future market prices would warrant PacifiCorp making higher per

- kW payments than seen recently in the Energy Exchange. Despite minimal participation in recent years, Pac ifiCorp could rely on existing program infrastructure s to reduce costs to $26/kW

- year
, making DBB a relatively low

- cost option.

Table 36 . Demand Buyback: Market Potential (MW in 2032) and

Levelized Cost by State ($/kW

- yr )

Territory State Market Potential (MW) Levelized Cost ($/kW

- yr ) *

Pacific Power California 0.1 $26

Oregon 4.2 $26 Washington 0.7 $26

Subt otal 5.1 $26

Rocky Mountain Power Idaho 0.4 $26

Utah 9.2 $26 Wyoming 4.2 $26

Subt otal 13.7 $26

Total 18.8 $26

* Subtotals and total s are weighted by market potential

.



### Table 37 and Table 38 show d etailed assumptions for DBB.

Table 37

. Demand Buyback: Program Basics
Program Element Assumption Customer sectors eligible All C&I market segments

. End uses eligible for program Total load of all end uses

. Cu stomer size requirements C&I customers with maximum monthly demand greater than 1

, 000 kW

. Applicable hours Top 50 system hours

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 47



### Table 38 . Demand Buyback: Planning Assumptions

Inputs Value Source(s) or Rationale

Annual administrative costs $75,000 Assumes 1/2 FTE to run the program system

- wide. Technology cost (per new participant) $0 Assumes customers who meet the program eligibility requirements will already have interval meters in place.

Marketing cost (per new participant) $720 /year (first year costs) $72/year (ongoing costs) Assumes 10 hours of effort by staff , with an additional hour per year

assumed for ongoing marketing and customer support.

Incentives (annual costs per participating kW) $20 Assumes $0.40 per kWh for 50 hours of interruption. This figure is slightly lower than the $0.50 per kWh pai d by California utilities.

Overhead: first costs $75,000 Assumes 1/2 FTE, 1/4 for Rocky Mountain Power

, and 1/4 for Pacific Power, to expand current program offerings.

Technical potential as % of

load basis 7% The average total load shed during events, account ing for customers who

did and did not submit a bid (event participation) , was 7% for PG&E and 7.6% for SCE ( 2011 Statewide Demand Bidding Programs for

Nonresidential Customers: Report , Christensen Associates).

Program participation (%) 13% CA, 8% ID, 9% OR, 10% UT, 15% WA, 8% WY Participation rates are based on SCE ’ s participation 2011 rate of 10.8%.

Values are expected to vary across states

, depending on the customer

mix in each . For example

, certain industries ( such as mining in Wyoming )

are less likely to participate.

Event participation (%) 100% As technical potential includes customers who did and did not submit bids, a default event participation rate of 100% was assumed.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 48 

# CLASS 2 DSM (ENERGY

- EFFICIENCY) RESOURCE S

Scope of Analysis

A ssessing Class 2 DSM (energy

- efficiency) resources primarily focused on updat ing estimates of

available potential in PacifiCorp’s service territory (Rocky Mountain Power and Pacific Power, excluding Oregon) over a 20

- year planning horizon (2013 to 2032). T his study separately

examined technical and achievable technical potential for residential, commercial, industrial, irrigation, and street lighting sectors in California, Idaho, Utah, Washington, and Wyoming. 29



### Within each state’s sector

- level assessment, the study further distinguished customer segments or facility types

, and their respective applicable end uses. The a nalysis addressed:

S ix residential segments (existing and new construction for single

- family, multifamily,

and manufactured homes) ;

Twenty

- four commercial segments ( 12 building types within existing and new construction ) ;

Fourteen industrial segments (existing construction only) ;

Four street lighting segments ( new and existing customer

- owned and company

- owned for existing fixtures ) 30 

### ; and

O ne segment for irrigation

.

Table 39

, Table 40 , and Table 41 show the full set of customer segment s and end uses for each

sector analyzed in this study

. Volume II, Appendix C

, provides a comprehensive list of state

- and

sector

- specific segments and end uses

.

29 The Energy Trust of Oregon, which delivers energy efficiency in Oregon, completed an assessment of potential in PacifiCorp’s Oregon service territory in 2012: http://energytrust.org/library/reports/121114_2012_ResourceAssessment.pdf

. 30 New construction was not modeled in Utah or Wy o m in g due to lack of forecasted load growthPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 49



### Table 39 . Residential Sector Dwelling Types and End Uses
Residential Customer Segments End Uses

Manufactured Computer
Multifamily Cooking oven
Single

- f amily Cooking range
Copier

Dehumidifier
Dryer

DVD

Freezer
Heat pump
Home audio system
Lighting interior specialty
Lighting standard (interior and exterior)

Microwave

Monitor

Multifunction device

Other
Plug load other
Pool pump

Printer
Refrigerator
Set top box
Space cooling

- central
Space cooling

- room Space heating

- central
Space heating

- room

TV

Ventilation and circulation
Water heating <= 55 gal
Water heating > 55 galPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 50



### Table 40 . Commercial Sector Customer Segments and End Uses
Commercial Customer Segments End Uses
Grocery Computer

Health Cooking

Office

— large Fax

Office

— small Flat screen monitors
Lodging Freezers

Miscellaneous Heat pump

Restaurant Lighting exterior

School Lighting interior fluorescent

Retail

— large Lighting i nterior HID

Retail

— small Lighting interior other

Warehouse Lighting interior screw base

Warehouse

– controlled atmosphere Other
Other plug load
Photo copiers

Printers
Refrigeration
Refrigerators

Servers
Space cooling

- chillers
Space c ooling

- DX e vap Space cooling

- room Space heat
Vending machines

Ventilation and circulation
Water heat <= 55 gal
Water heat > 55 galPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 51



### Table 41 . Industrial Sector Customer Segments and End Uses
Industrial Customer Segments (NAICS) Electric End Uses
Agriculture HVAC

Chemical manufacturing Indirect boiler

Electronic manufacturing Lighting

Food manufacturing Process electro chemical
Industrial machinery Process heat
Lumber wood products Proces s other

Miscellaneous manufacturing Process cool
Paper manufacturing Fans

Petroleum manufacturing Pumps
Stone clay glass products Process aircomp
Transportation equipment manufacturing Process refrig
Mining Motors other

Metal manufacturing Other

Wastewater

Water



### The study included examining a comprehensive set of energy

- efficiency measures , incorporating

measures assessed by the Council in its 6 th 

### Power Plan, the RTF, and the Energy Trust o f Oregon , as well as those within the Cadmus team’s library of measures

. A nalysis began by assessing the technical potential of hundreds of unique energy

- efficiency measures ( actual quantities are shown in Table 42 ). Conside ring all permutations of these measures across states,
customer sectors, customer segments, end uses, and construction vintages required compiling and analyzing customized data for over 1 9 ,000 measure permutations

. Volume II, Appendix B

, provides a complet e list of energy

- efficiency measures analyzed in all states

.

Table 42

. Class 2 DSM Measure Counts *

Sector Measure
Counts Measure

Permutations

Residential 131 3,262

Commercial 145 12,284

Industrial 93 3,640
Irrigation 3 15

Street l ighting 4 64

Total 376 19,265

* Measure counts and permutations represent only measures with potential energy

efficiency savings. Appendix C

- 2 includes the comprehensive list of energy

efficiency measures considered in this study.



### The remainder of this section is divide d into four parts :

A detailed description of the methodology used for estimating the technical and

achievable technical Class 2 DSM potential ;

Class 2 DSM r esource potential

, by state and sector;PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 52 

### Detailed Class 2 DSM resource potential for each sector

, by segment and end use; and

A comparison of these results with the 2011 Assessment

.



## Assessment Methodology

General Approach

The Cadmus team’s general methodology can be best described as a combin ed ―top

down/bottom

- up‖ approach. As shown in Figure 2

, the top

- down component beg an with the most current load forecast, adjusting for building codes

, equipment efficiency standards , and market

trends not accounted for in that forecast , then decompos ing this into its constituent customer sector, customer segment, and end

- use components. The bottom

- up component consider ed potential technical impacts of va rious Class 2 DSM measures and practices on each end use.

I mpacts could then be estimated

, based on engineering calculations and account ing for fuel shares, current market saturations, technical feasibility, and costs.

In this chapter, t hese unique

, measure

- level impacts have been aggregated to produce resource potential estimates at the end use, customer sector, state, and service territory levels. Summaries of resource potential, by state, sector, and end use can be found in Appendix C

- 4.

Figure 2 . General Methodology for Assessment of Class 2 DSM Resource Potential

The study considers t hree types of potential : naturally occurring

, technical

, and achievable

technical

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 53 

### Naturally occurring conservation refers to reductions in energy use that occur due to normal market forces, such as technological change, energy prices, market transformation efforts, and improved energy codes and standards. This analysis accounted for naturally occurring

conservation in three ways:

First, the assessment accounted for gradual efficiency increases due to the retirement of older equipment in existing buildings and the subsequent replacement with units that

meet minimum standards at that time. For some end uses, the technical potential

a ssociated with certain energy

- efficiency measures assumed a natural adoption rate. For example, savings associated with ENERGY STAR appliances accounted for current

trends in customer adoption.

Second, energy consumption characteristics of new construction reflected current state

specific building codes

.

Third , the assessment accounted for improvements to equipment efficiency standards that are pending and will take effect during the planning horizon. The assessment did not, however, forecast changes to standards that have not passed; rather, it treated these at a ―frozen‖ efficiency level.

These impacts resulted in a change in baseline sales

, from which the technical and achievable technical potential could be estimated.

Technical potential includes all technically feasible Class 2 DSM measures, regardless of costs

or market barriers. T echnical potential divide s into two classes: discretionary (retrofit) and lost

opportunity (new construction and replacement of equipment on burnout).

This study’s technical potential e stimation s for Class 2 DSM resources drew upon best

- practice

research methods and standard analytic techniques in the utility industry. Such techniques

remained consistent with conce ptual approach es and methodolog ies used by other planning entities within PacifiCorp’s service area , such as those of the Council in developing regional

energy

- efficiency potential

, and remain ed consistent with met hods used in PacifiCorp’s 2007 and

2011 A s sessments

.

Achievable technical potential represents the portion of technical potential that might reasonably

be achievable in the course of the 20

- year planning period, given the possibility that market

barriers could imped e customer adoption

. At this po int, it does not consider cost

- effectiveness , as identified levels of achievable technical potential principally serve as planning guidelines and to inform the IRP process. The Ramp Rate section of this chapter further describes t he amount of technical potential considered achievable on an annual basis beginning in 2013

.

Developing sound utility IRPs requires k nowledge of alternative resource options and reliable information on the long

- run resource potential of achievable technolo g ies. DSM r esource potential studies principally seek to develop reasonably reliable estimates of the magnitude, costs, and timing of resources likely available over the planning horizon ’s course ; they do not

, however, provide guidance as to how or by what means identified resources might be acquired. For example, identified potential for electrical equipment or building shell measures might be attained through utility incentives, legislative action instituting more stringent efficiency codes and standards, or other means.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 54 

## Overview
Estimating Class 2 DSM potential draws on a sequential analysis of various energy

- efficiency measures in terms of technical feasibility (technical potential) and expected market acceptance

, considering normal barriers possibly imp ed ing measure implementation (achievable technical potential). The assessment utilized three primary steps:

Baseline forecast ing : Determin ing 20

- year future energy consumption by state, sector,
market segment

, and end use

. The study calibrate d the base year

, 2012, to PacifiCorp’s

sector load forecasts in each state. It then remove d PacifiCorp’s special accounts to

ensure a forecast appropriate for Class 2 DSM activity. 31 

### As described above, the baseline forecasts shown in this report include the Cadmus team’s estimated impacts of naturally occurring potential

. 32



### Est imation of alternative forecast s of technical potential: Estimat ing technical potential

, based on alternative forecast s, that reflect technical impacts of specific energy

- efficiency

measures.

Estimation of achievable technical potential: A chievable technical potential calculated by applying ramp rates and an achievability percentage to the technical potential , as this

section la ter describe s in detail.

This approach offered two advantages :

First, savings estimates would be driven by a baseline calibrated to PacifiCorp’s base year (2012) sales

. Although subsequent baseline years may differ from PacifiCorp’s load

forecast

, compar ison s to PacifiCorp’s sales forecast help ed control for possible errors. Other approaches may simply generate the total potential by summing estimated impacts of individual measures, which can result in total savings estimates represent ing unrealistically high or low baseline sales percentages

.

S econd

, the approach maintain ed consistency among all assumptions underlying the baseline and alternative (technical and achievable technical) forecasts. T he alternative

forecasts changed relevant inputs at the end

- use level to reflect impact s of energy

efficiency measures. As estimated savings represent ed the difference between the baseline and alternative forecasts, they could be directly attributed to specific changes made to analysis inputs.



## Data Sources

F ull assessment of Class 2 DSM resource potential required compil ing large amounts of

measure

- specific technical, economic, and market data from secondary sources and primary

research. M ain data sources used in this study included:

31 These accounts have significant loads and work with key account managers to manage these loads.

32 The Cadmus team’s baseline forecast accounted for codes and standards not embedded in PacifiCorp’s load forecast. In addition, the baseline drew upon end

- use saturations, which generally align with those in PacifiCorp’s load forecast, though some end

- use saturations may differ after accounting for future Class 2 DSM activity or because Cadmus used other, more recent data sources in the baseline. Due to the se adjustments, 2032 baseline sales presented in this report may not match PacifiCorp’s official load forecast.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 55 

### PacifiCorp : 2012 sales fo recasts , historic and projected energy

- efficiency activities,

current customer counts and forecasts, and the recent Energy Decisions Survey

. Table 43

s hows a complete list of data elements provided by PacifiCorp.

Table 43

. PacifiCorp Data Sources Used in Class 2 DSM Analysis

Data Element Key Variables Use in This Study

2011 sales and customer

counts Number s of customers and total sales by state and customer segment. Data used for customers and sales for calibration in the

end

- use model.

2012 sales and customer
forecasts Sales and customer forecasts by

state and customer sector

, excluding projected DSM activity. Informs e nd

- use model base case forecast

, with new customers serving as drivers in end

- use model development.

Historic and projected
Class 2 DSM program achievements Program participation

, number of measures installed, and savings

. Measure saturations ; validation of measure characterizations (savings, costs).

2006 Residential Energy

Decision s Survey Dwelling characteristics, equipment saturations, and fuel

shares. Dwelling type breakouts ; square footage per dwelling ; applicability factors ; incomplete factors ; development of building simulation prototypes ’ forecast calibration.

2005 and 2007 Commercial Energy

Decision s Survey s Building characteristics, equipment saturations, and fuel

shares. Building type breakouts ; square footage per dwelli ng ; measure applicability factors ; development of building simulation prototypes ; forecast calibration.

2011 FinAnswer

® Express
Market Characterization
Studies Measure data

. Measure savings ; costs and useful life assumptions

.

20 09

– 2010 Program

Evaluation Reports Savings estimates

. The savings estimates for measures were based on recent evaluation studies, as available.



### Building Simulations : This study relied on normal consumption and load profile

e stimates for the majority of end uses in commercial segments

, as developed for the 2007 Assessment using the eQuest building simulation models

. Energy intensities have been adjusted to account for pertinent codes and standards adopted since the 2007 Assessment.

The current assessment required development of new building simulations ( using SEEM)

for the residential sector

, with s eparate models created for each state, customer segment, and construction vintage. 33



### Pacific Northwest Sources : Several Northwest entities provided data critical to th is study, including the Council and the RTF. Data included technical information on measure savings, costs, and useful lives ; hourly end

- use load shapes (to supplement buildings simulations, as descri bed above) ; and commercial building physical and energy consumption characteristics. Table 44 provide s further d etails

.

33 For details on eQuest and SEEM (v.94), see (respectively): http://www.doe2.com and http://www.nwcouncil.org/energy/rtf/measures/support/SEEM /Default.asp

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 56



### Table 44 . Class 2 DSM Pacific Northwest Data Sources

Pacific Northwest

Data Source Key Variables Use in This Study

Council 6th Power Plan Measure data estimates. Measure savings, costs, and lives; cross

- check of potential estimates.
Council Hourly Electric Load Model Hourly load shapes. Hourly end

- use load shapes for the residential, commercial, and industrial sectors.

RTF Website Measure data. Measure savings, costs, and lives.



### California Energy Commission (CEC) : This study used information available in the

2005 and 2008 Database of Energy Efficiency Resources (DEER) to validate many assumptions and data collected on energy

- efficiency measure costs and savings.

Ancillary Sources : Other data sources primarily consisted of available information from

the 2 007 and 2011 Assessment s ; past energy

- efficiency market studies ; energy

- efficiency potential studies ; and evaluations of energy

- efficiency programs offered throughout the

country

. In addition to the previously cited PacifiCorp Market Characterization Stud ies

and t he Council’s 6th Power Plan

, data source s included the U.S. Department of Energy

Industrial Assessment Centers Database and reports from the N orthwest E nergy
E fficiency A lliance (NEEA) on its Industrial Efficiency Alliance I nitiative and Emerging Technologies and Behaviors for Energy Efficient Industrial Refrigeration

.



## Baseline Forecasts PacifiCorp’s state

- and sector

- level sales and customer forecasts provided the basis for assess ing

energy

- efficiency potential

. Prior to estimating potential, the study disaggregated state

- and

sector

- level load forecasts by customer segment ( business, dwelling

, or facility type s ), building vintage (existing structures and new construction )

, and end uses (all applicable end uses in each

customer sector and segment )

.

The first step in developing the baseline forecasts determine d the appropriate customer segments

within each state and sector. D esignations drew upon categories available in some key data

sources used in the study, primarily PacifiCorp’s 2011 cus tomer database and the recent Energy Decisions Survey , followed by mapping appropriate end uses to relevant customer segments in

each state. 34



### Once appropriate customer segments and end uses had been determined for each sector, the study produced the basel ine end

- use forecasts, based on integration of current and forecasted customer counts with key market and equipment usage data. For the commercial and residential

sectors, calculating total baseline annual consumption for each end use in each customer segm ent used the following equation :

34 Not all segments were modeled in all states. For example, the large office segment did not prove relevant in the entirely rural California service territory. Similarly, not all end

- uses within a sector necessarily proved relevant in every customer segment ( e.g. , cooking typically is not present in the commercial sector’s warehouse

segment ).PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 57



### EUSE ij 

### = Σ

e 

### ACCTS i 

### * UPA i 

### * SAT ij 

### * FSH ij 

### * ESH ije 

### * EUI ije



### where:

EUSE ij 

### = total energy consumption for end use j in customer segment i

ACCTS i 

### = the number of accounts/customers in customer segment i

UPA i 

### = units per account in customer segment i ( UPA i 

### generally the average square feet per customer in commercial segments

, and 1.0 in residential dwellings, assessed at the

whole

- home level) 35



### SAT ij 

### = the share of customers in customer segment i with end use j

FSH ij 

### = the share of end use j of customer segment i served by electricity

ESH ije 

### = the market share of efficiency level e in equipment for customer segment and

end use ij

EUI ije 

### = end

- use intensity : energy consumption per unit (per square foot for commer cial)

for the electric equipment configuration ije

For each sector, t otal annual consumption could be determined as the sum of EUSEij across the end uses and customer segments. E nsuring accuracy of the baseline forecasts depended on the

calibration of end

- use model estimates of total consumption to PacifiCorp’s forecasted sales

from 2012

.

Consistent with other potential studies

, and commensurate with industrial end

- use consumption

data ( which varied widely in quality )

, allocating the industrial sector’s loads to end uses in various segments drew on data available from the U.S. Department of Energy’s E nergy
I nformation Administration (EIA)

. 36 

### For the irrigation sector, the total load in each state has been

well established

, consist ing a lmost entirely of pumping , with a small amount of energy in system

controls and motor drives for wheel

- based systems

. Street lighting loads were allocated based on PacifiCorp data on company versus customer ownership and on the number and type of fixtures

p resent in each state.

Volume II, Appendix C

, provides s ummaries of baseline forecasts for each state and sector

.



## Derivation of End

- Use Consumption Estimates

E stimates of e nd

- use energy consumption by segment, end use, and efficiency level ( EUI ije 

### ) provide one of the most important components in develop ing a baseline forecast. In the residential sector, the study based estimates on unit energy consumption (UEC), represent ing

annual energy consumption associated with an end use ( represent ed by a speci fic type of equipment, such as a central air conditioner or heat pump )

.

35 The average square footage by home type was entered into building simulations used in the SEEM models; therefore, the results reflected weather and h ome size differences between states.

36 U.S. Department of Energy (DOE), EIA. 2006. Manufacturing Energy Consumption Survey

.PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 58 

### For the commercial sector, the study treated consumption estimates as end

- use intensities (EUIs),

represent ing annual energy consumption per square foot served

. A ccuracy of these esti mates proved critical , as they had to account for weather and other factors

, described below

, that drive differences between various states and segments.

For the industrial sector, end

- use energy consumption represent ed total annual industry consumption b y end use, as allocated by the secondary data

, described above. In irrigation energy consumption, nearly all usage was allocated to the pumping end use

, and a small amount

was allocated to ―other

. ‖ 37 

### Street lighting was allocated entirely to lighting and was segmented to

company

- or customer

- owned fixtures.

The study derived many end

- use consumption estimates from building simulation models (eQuest and SEEM for commercial and residential segments, respectively) to account for key regional differences

, incl uding weather, state codes, building size s , and shell characteristics. For

non

- weather

- sensitive end uses that could not be modeled within a building simulation framework (e.g., residential refrigerators), the study used consumption estimates from ENERGY

S TAR ; the EIA’s Residential Energy Consumption Survey (RECS) and the Commercial Buildings Energy Consumption Survey (CBECS); the 2007 Commercial Building Stock Assessment (CBSA ) 38 

### completed by NEEA; and the 2006 California Commercial End

- Use Survey

. 39



### Most k ey drivers used in developing commercial simulation models (operating schedules, setback temperatures, and building size s ) drew upon data in PacifiCorp’s Energy Decisions Survey

. 40 

### The study based r esidential simulation models on the RTF’s SEEM models for i ts

energy

- efficiency measures. To create a simulation, SEEM used a number of input parameters

, including those for occupancy, equipment, ducts, envelope, foundation s , and infiltration . The

Cadmus team updated the SEEM models specifically for PacifiCorp’s service territory. Volume II, Appendix C

, s ummari zes end

- use consumption estimates for residential (UECs), commercial (EUIs), and industrial (end

- use percentages).



## Energy

- Efficiency Measures

As t echnical potential drew upon an alternative fore cast

, reflect ing installation of all technically

feasible measures, selecti ng appropriate Class 2 DSM resources to include in this study posed a central concern. To alleviate the concern and arrive at the most robust set of appropriate measures, f

or the re sidential and commercial sectors the study began with a broad range of

energy

- efficiency measures for possible inclusion

, screened to include only measures commonly available, based on well

- understood technolog ies , and applicable to PacifiCorp’s buildings and

end uses. Many of these measures are included in the Council ’s 6th Power Plan and/ or assessed

37 Non

- pumping end uses include system controls and motor drives for wheel

- based systems.

38 http://neea.org/resource

- center/regio nal

- data

- resources/commercial

- building

- stock

- assessment

39 http://www.energy.ca.gov/ceus/

40 Extensive efforts sought to validate and cross

- check results from the Energy Decisions Survey with data from other sources, including CBECS, CBSA, and other availa ble studies.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 59 

### by the RTF . The industrial sector measures drew upon the Council’s 6th Power Plan and on other general categories of process improvements. 41



### Table 45

, Table 46 , and Table 47 outline types of energy

- efficiency measures assessed in the residential, commercial, and industrial sectors, respectively. Equipment measures replac e end

use equ ipment (e.g., high

- efficiency central air conditioners), while non

- equipment measures

reduc e end

- use consumption without replacing end

- use equipment (e.g., insulation). Volume II, Appendix B

, provides a complete list of all measures, including descriptions

.

Table 45 . Residential Energy

- Efficiency Measures Types

End Use Measure Types
Heating and cooling Non

- Equipment : air

- to

- air heat exchangers; insulating concrete form and structural insulated panel construction; cool roof and green roof; ceiling, wall (2x4, 2x6)

, floor and slab insulation; insulated exterior doors and weatherstripping; duct sealing and insulation; HVAC unit quality installation and tune

- up; efficient windows; whole

- house fan; infiltration control; new home ther mal shell with low infiltration; multi

- zone thermostat; radiant barrier. Equipment : high

- efficiency heat pump; ground source heat pump; high

- efficiency central AC; ENERGY STAR room AC; ductless heat pump; evaporative cooler; heat pump conversion.

Ventilation and circulation Equipment : ECM motor.
Lighting Non

- Equipment : daylighting control; occupancy sensor; time clock. Equipment : compact fluorescent lamps ( CFL ) ; light emitting diodes ( LED )

. Water heating Non

- Equipment : hot water pipe insulation; faucet aerators; low

- flow showerheads; ENERGY STAR dishwasher and clothes washer; drain water heat recovery. Equipment : high

- efficiency storage and heat pump water heaters.
Appliances Non

- Equipment : removal of standalone freezer s and secondary refrigerator s

. Equipment : ENERGY STAR freezers and refrigerators; high

- efficiency cooking oven s

, range s , and dryer s

. Plug load Non

- Equipment : smart strip; ENERGY STAR battery charger. Equipment: ENERGY STAR computer, monitor, TV, set top box, dehumidifier, DVD player, home audio system, multifunction device, copier, and printer; high

- efficiency

microwave.
Pool pump Equipment : pool pump.

41 Industrial improvements derived from a variety of practices and specific measures, such as those defined in the

DOE’s Industrial Assessment Centers Database: http://www.iac.rutgers.edu/database/PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 60



### Table 46

. Commercial Energy

- Efficiency Measures Types

End Use Measure Types

HVAC Non

- Equipment : ceiling, wall, and floor insulation; duct repair, sealing

, and insulation; windows;

equipment tune

- up; automated ventilation control; pre

- cooling; direct digital control system optimization; constant air to variable

- air volume ( VAV ) conversion; high

- efficiency VAV box; economizers; exhaust air to ventilation air heat recovery and variable frequency drive ( VFD ) control; re

- commissioning; exhaust hood makeup air; chilled water/condenser water settings

optimization; chilled water piping loop w ith VSD control; cooling tower approach temperature; two

speed and variable

- speed fan; pipe insulation for chillers; cool and green roof; natural ventilation; infiltration reduction; new construction Integrated Building Design; window film; hotel ke y card control; high

- efficiency motor, motor rewind and VFD; low

- pressure distribution complex; cooking hood controls; optimized variable volume lab hood. Equipment : high

- efficiency heat pumps; high

- efficiency chillers, packaged terminal AC units, and DX p ackages; ground source heat pump; evaporative cooler. Lighting Non

- Equipment : daylighting , continuous and stepped dimming controls; bi

- level control; occupancy

sensors; efficient refrigeration lighting and exit signs; time clock; exterior building lighting; surface and covered parking lighting; solid state LED white lighting; new construction integrated building design. Equipment : high

- efficiency fluorescent, induction, metal halide, CFL, LED, and lighting packages

Water h eating Non

- Equipment : hot water pipe insulation; high

- efficiency chemical, residential, and commercial

dishwashing systems ; demand controlled circulating systems; low

- flow showerheads, spray heads, and faucet aerators; ultrasonic faucet control; commercial

- and residential

- sized clothes washers; water cooled refrigeration with heat recovery; drain water heat recovery water he ater. Equipment : high

- efficiency water heater; heat pump water heater. Refrigeration Non

- Equipment : compressor and rooftop unit supply fan VFD; demand control defrost; strip

curtains; floating condenser head pressure control; anti

- sweat controls; glass an d solid door refrigerator/freezer; walk

- in and case electronically commutated motors ( ECM ) and controllers; case replacement; display case night cover and motion sensor; standalone to multiplex compressor; commissioning or re

- commissioning; visi cooler; ve rtical and semi

- vertical no doors refrigeration.
Appliances Non

- Equipment: appliance recycling

.

Equipment : ENERGY STAR freezers and refrigerators.
Plug l oad Non

- Equipment: network PC power management and server virtualization; power supply

transformer/converter; smart strip; high

- efficiency ice maker; ENERGY STAR battery charging system, scanner, and water cooler. Equipment: ENER GY STAR computer, monitor, fax , copier, printer, and vending machine; high

efficiency server. Cooking Non

- Equipment: High

- efficiency combination and convection oven, fryer, griddle; ENERGY STAR

hot food holding cabinet and steam cooker.PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 61



### Table 47

. Industrial Energy

- Effi ciency Measures Types

Measure Types
Agricultural process improv ements
Air compressor improvements
Building improvements
Circulating fans
Clean room improvements
Cold storage retrofit/tune

- up Compressor improvements
Electric chip fabrication improvements
Facility energy managements/recommissioning
Fan system improvements
General process improvements
High

- efficiency motors

HVAC equipment improvements
Improved controls
Lighting controls
Lighting equipment improvements

Motor rewinds
Process heat operations and maintenance
Properly sized fans
Pump improv ements
Refrigeration improvements

Switch from belt drive to direct drive
Synchronous belts

Transformers
Variable speed drives
Ventilation system improvements



### In addition, street lighting and irrigation sectors both have efficiency measures. Street lighting

measures replace existing high

- pressure sodium or mercury vapor lighting with LEDs. Irrigation

measures include scientific irrigation scheduling (SIS) , high

- efficiency motors, and other system improvements.



## Measure Impacts

A ssessing technical potential began by estimat ing measure

- level impacts , which required compiling and analyzing data on the following characteristics for each measure :

Measure savings : E nerg y savings associated with a measure

, as a percentage of total

end

- use consumption. Sources include d: standard engineering algorithms , energy simulation modeling, the Council’s 6th Power Plan, RTF, PacifiCorp’s 2011 FinAnswer ®



### E xpress market c haracterization s tudies

, secondary data sources (case studies), and the

California DEER database.

Measure life : The measure’s expected useful life . Sources include d: the DEER database,

the Council’s 6th Power Plan, other potential studies, and DSM program evaluations.PacifiCorp Assessment of Long

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### Measure applicability : A general term encompassing a number of factors, including the technical feasibility of installation

, the measure’s current or naturally occurring

saturation

, and s haring of energy savings with competing measures

. Sour ces include Council’s 6th Power Plan, RTF, and the DEER database.

Measure costs : P er

- unit cost s (either full or incremental, depending on the application)

associated with measure installation. Sources include d the Council’s 6th Power Plan,
RTF, RS Means, the DEER database, merchant Websites ( e.g., Home Depot, Trane), and other secondary sources.

Operations and maintenance ( O&M ) costs : A measure’s a nnual operation and maintenance costs. These may be positive or negative

, compared to the baseline , and are

su btracted from the measure’s net present value cost when calculating its cost of conserved energy. This study only included O&M costs for Washington and Idaho.

Non

- energy benefits : Additional benefits attributable to a measure, such as water savings , and ac counted for in the measure’s net present value cost when calculating its

cost of conserved energy. This study only included non

- energy benefits for Washington

and Idaho.

Secondary energy b enefits : Additional energy benefits attributable to a measure, such as natural gas savings

, 42 

### subtracted from the measure’s net present value cost when calculating cost s of conserved energy (also only included for Washington and Idaho )

.

Conservation Credit : The 10% regional conservation credit used in the 6 th 

### Power Plan is not included in the levelized costs presented in this report. PacifiCorp will apply the

credit for Class 2 DSM resources in Washington in the IRP modeling process. 43



## About Technical Potential
Technical potential represents total energy available to be saved from all measures, adjusting only for applicability. For example, high wall insulation levels can be placed in a certain percentage of homes, a certain share of which may already have such insulation in place. Consequently, technical potential only includ e s technically feasible homes without measures in place.

Another important aspect in assessing technical potential is

, wherever possible, to assume installation of the highest

- efficiency equipment. For example, this study examined CFL and LED general service lighting in residential applications and, in assessing technical potential

, assum ed that, as equipment fails or new homes are built, customers will install LED lighting wherever technically feasi ble regardless of cost. CFLs would be assumed installed in sockets ineligible for LEDs, where applicable. Competing non

- equipment measures have been treated the same way, assuming installation of the highest

- saving measures where technically feasible.

42 The study conducted analysis at an end

- use level. For example, for a measure applied to an air conditioning

end

- use, these benefits included the value of heating energy saved across electric and natural gas heating fuels.

43 PacifiCorp will also apply a 10% conservation credit to Class 2 DSM savin gs in Oregon for IRP modeling.PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 63 

### In e stimating technical potential, one cannot merely sum up savings from individual measure installations, as significant interactive effects can result from the installation of complementary measures. For example, upgrading a heat pump in a home where insulat ion measures have already been installed can produce fewer saving s than upgrades in an uninsulated home. A nalysis of technical potential accounts for two types of interaction s :

Interactions between equipment and non

- equipment measures: As equipment burns

o ut, technical potential assumes it will be replaced with higher

- efficiency equipment,

reduc ing average consumption across all customers. Reduced consumption causes non

equipment measures to save less than they would have, had equipment remained at a

consta nt average efficiency. Similarly, savings realized by replacing equipment decrease upon installation of non

- equipment measures

.

Interactions between non

- equipment measures: Two non

- equipment measures applying to the same end use may not affect each other’s savings. For example, installing

a low

- flow showerhead does not affect savings realized from installing a faucet aerator. Insulating hot water pipes, however, would cause water heater s to operate more efficiently, thus reducing savings from either measure

. T his assessment accounted for

such interaction s by ―stacking‖ interactive measures

— iteratively reducing baseline consumption as measures were installed, thus lowering savings from subsequent

measures.

While theoretically, all retrofit opportunities in existing construction (often called ―discretionary‖ resources) could be acquired in the study’s first year, this would skew the potential for equipment measures and provide an inaccurate picture of measure

- level potential. Therefore, the study assume d the realization for these opportunities in equal

, annual amounts

, over the 20

- year planning horizon. By applying this assumption, natural equipment turnover rates, and other adjustments described above, the annual incremental and cumulative potential

was estim ated by state, sector, segment, construction vintage, end use, and measure.



## About Achievable Technical Potential

Achievable technical potential can be defined as the portion of technical potential expected to be

r easonably achievable in the course of a planning horizon. The quantity of energy

- efficiency potential realistically achievable depend s on several factors

, including the customers’ willingness

to participate in energy

- efficiency programs (partially a function of incentive levels )

, retail

energy r ates

, and a host of market barriers historically impeding adoption of energy

- efficiency measures and practices by consumers. 44 

### These barriers tend to vary, depending on the customer sector, local energy market conditions, and other, hard

- to

- quantify factors

. A ssessing achievable

44 Consumers’ apparent unwillingness to invest in energy efficiency has been attributed to certain energy

efficiency market barriers. A rich body of literature exists concerning the ―market barriers to energy efficiency.‖

In one such study, market barriers identified fell into five broad classes of market imperfections, thought to inhibit energy

- efficiency investments: (1) misplaced or split incentives; (2) high upfront costs, and a lack of access to capital; (3) a lack of in formation, and uncertainty concerning the benefits, costs, and risks of energy

efficiency investments; (4) investment decisions guided by convention and custom: and (5) time and ―hassle‖
factors. For a discussion of these barriers, see: William H. Golove a nd Joseph H. Eto. March 1996. ―Market Barriers to Energy Efficiency: A Critical Reappraisal of the Rationale for Public Policies to Promote Energy.‖ Lawrence Berkeley National Laboratory, University of California, Berkeley, California. LBL

- 38059.PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 64 

### technical potential , however, adopts a central tene t that a ssum es it is ultimately a function of the customers’ willingness and ability to adopt energy

- efficiency measures ; this information can be best ascertained through direct elic itation s from potential participants.

Though m ethods for estimating achievable technical potential var y across potential assessment

efforts , t wo dominant approaches appear to be most widely utilized:

1. T he first approach assumes a hypothesized relationship between incentive levels and market penetration of energy

- efficiency programs. This achievable potential generally

can be defined as that achieved solely through utility incentive programs, and often it is

based on an incentive level at 50% of the incremental cost.

2. The second approach generally relies on a fixed percentage of the technical potential

, which is based on past experiences with similar programs

. I n the Northwest, for example, the Council has historically assumed that, by the end of the 20

- year assessment horizon,

85 % of the technical potential could be achieved , including savings from utility programs, market transformation

, and changes in codes and standards.

Consistent with the Council, this study use d option two, a ssuming up to 85% of technical potential could be acquired over the 20

- year planning horizon. In addition to applying a fixed percentage, this assessment incorporated ramp rates to estimate annual achievable technical potential. As discussed below, two lay ers of ramp rates have been incorporated for all measures and market regions.

Estimated achievable technical potential principally serve s as a planning guideline. Acquiring

such DSM resource levels depend s on actual market acceptance of various technologi es and measures, which partly depend on removing barriers ( not all of which a utility can control )

.

In addition to utility

- sponsored programs, alternative delivery methods, such as existing market

transformation efforts and codes and standards promotion

, can be used to capture portions of

these resources , d epending on actual experience s with various programs

. This proves particularly relevant in the context of long

- term Class 2 DSM resource acquisition plans, where incentives might be necessary in earlier years to motivate acceptance and installations. As acceptance increases, so would demand for energy

- efficient products and services, likely leading to lower costs, and thereby obviating the need for incentives and (ultimately) preparing for transitions to

codes and standards.

Measure Ramp Rates The study applie d measure ramp rates to lost opportunity and discretionary resources

, though interpretation and application of these rates differed for each class ( as described below )

. M easure ramp rates generally m atched those used in the Council’s 6th Power Plan

, al though the study incorporated additional considerations for Class 2 DSM measure acquisition :

T he first year of the 6th Power Plan ramp rates (2010) aligned with the study’s first year (2013).

For measures not specified in the 6th Power Plan

, the study assigned a ramp rate
considered appropriate for that technology (i.e. , the same ramp rate as a similar measure

in 6th Power Plan )

.PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 65 

### G eneral service CFL s required use of a custom ramp rate, with the stu dy’s CFL penetration estimate in 2013 align ing with PacifiCorp’s 2012 activity, market trends, and forecasted 2013 activity.

Lost Opportunity Resource s 

### Q uantifying achievable technical potential for lost opportunity resources in each year required

de termi n ing amount s technically available through new construction and natural equipment

turnover. New construction rates drew directly from PacifiCorp’s customer forecast. The study developed e quipment turnover rates by dividing units in each year by the measure life. For example, if 100 units initially had a 10

- year life, one

- tenth of units ( 10 ) would be replaced. In the following year, 90 units would remain

, and one

- tenth of these (9) would be replaced, and so on

over the study’s course.

As the mix of existing equipment stock ages , the remaining useful life (RUL) would be

, on

average, one

- half of the effective useful life (EUL)

. 45 

### The fraction of equipment turn ing over each year would be a function of this RUL ; thus, the technical potential for lost opportunity

m easures would have an annual shape before application of any ramp rates, as shown in Figure

3 . The same concept applie d to new construction, where resource acquisition opportunities only

become available during home or building construct ion . In addition to showing an annual shape, Figure 3 demonstrates amount s of equipment turn ing o ver during the study period as a RUL

function : the shorter the RUL, the higher the percentage of equipment assumed to turn over.

Figure 3 . Existing Equipment Turnover for Varying RULs

45 EULs r epresented median lifetime s , defined as the year that one

- half of measures installed remained in place and operable and one

- half did not , as defined by the RTF: http://www.nwcouncil.org/energy/rtf/subcommittees/measurelife/RTF%20Measure%20Useful%20Life%20Gui delines%20Final%202012%200515.pdfPacifiCorp Assessment of Long

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### In addition to natural timing constraints imposed by equipment turnover and new construction

rates

, the Cadmus team applie d measure ramp rates to reflect other resource acquisition

limitations over the study horizon

, such as market availability. T hese measure ramp rates had a

maximum value of 85%, reflecting the Council’s assumption that

, on average across all

measures
, up to 85% of technical potential could be achiev ed over a 20

- year planning horizon

. As illustrated by Figure 4

, a measure that ramp s up over 10 years would reach full market maturity (85% of annual technical potential) by the end of that period

, whereas another measure might take 20 years to reach full maturity.

Figure 4 . Examples of Lost Opportunity Measure Ramp Rates

To calculate annual achievable technical potential for each lost opportunity measure, the study multiplied technical resource availability and measure ramping effects together, consistent with

the Council ’s methodology

. P articularly in the early years of the study horizon , a gap occur s between assumed acquisition and the 85% maximum achievability. Thus, these ―lost‖ resources

can be assumed not available until the measure’s EUL e lapse s . Therefore, depending on EUL and measure ramp rate assumptions, some potential may be pushed beyond the study’s 20 th 

### year
, and total lost opportunity achievable technical potential may be less than 85% of technical potential.

Figure 5 shows such a case for a measure with a five

- year RUL/10

- year EUL. T he spike in achievable technical potential starting in year 2023 (after the measure’s EUL) resulted from acquisition of opportunities missed at the beginning of the study period

.PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 67 

### Figure 5 . Example of Combined Effects of Technical Resource Availability and

Measure Ramping Based on 10

- Year EUL

Table 48 , below, illustrates this method

, based on the same five

- year RUL/10

- year EUL measure

on a 10

- year ramp rate ( the light blue line in Figure 5 )

, assuming 1,000 inefficient units are in place in 2012. In the first 10 years (2013 through 2022), lost opportunities accumulate as the

measure ramp

- up rate caps availability of high

- efficiency equipment. Starting in 2023 ( the 11 th



### year ) , opportunities lost 10 years prior become available again. Table 48 also shows that this EUL and measure ramp rate combination results in 85% of tech nical potential achieved by the study period ’s close

.

As described, amounts of achievable technical potential are a function of the EUL and measure ramp rate. The same 10

- year EUL measure, on a slower 20

- year ramp rate, would achieve less of

its 20

- year te chnical potential (a lso shown in Figure 5 ). Across all lost opportunity measures included in this study, approximately 72% of technical potential appea rs achievable over the

20

- year study period , a finding consistent with the Council’s assumption that less than 85% of lost opportunity resources can be achiev ed

. 46

46 A Retrospective Look at the Northwest Power and Conservation Council’s Conservation Planning Assumptions

. April 2007. http ://www.nwcouncil.org/library/2007/2007

- 13.htmPacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 68



### Table 48 . Example of Lost Opportunity Treatment : 10

- Year EUL Measure on a 10

- Year Ramp Rate

Year Incremental

Stock Equipment

Turnover (Units) Cumulative

Stock Equipment

Turnover (Units) Measure

Ramp

Rate Installed

High Efficiency

Units Missed

Opportunities

for Acquisition in

Later Years (Units) Missed

Oppor tunities Acquired (Units) Cumulative

Units

Installed Cumulative

Percent of

Technical

Achieved

2013 200 200 9% 17 180 0 17 9%

2014 160 360 16% 26 130 0 43 12%

2015 128 488 24% 30 92 0 73 15%

2016 102 590 31% 32 65 0 106 18%

2017 82 672 39% 32 44 0 138 20%

2018 66 738 47% 31 29 0 168 23%

2019 52 790 54% 29 19 0 197 25%

2020 42 832 62% 26 11 0 223 27%

2021 34 866 70% 23 6 0 246 28%

2022 27 893 77% 21 2 0 267 30%

2023 21 914 85% 18 0 153 438 48%

2024 17 931 85% 15 0 110 563 60%

2025 14 945 85% 12 0 78 653 69%

2026 11 956 85% 9 0 55 717 75%

2027 9 965 85% 7 0 38 762 79%

2028 7 972 85% 6 0 25 793 82%

2029 6 977 85% 5 0 16 814 83%

2030 5 982 85% 4 0 10 828 84%

2031 4 986 85% 3 0 5 836 85%

2032 3 988 85% 2 0 2 840 85%
Note: Units represent those installed annually. Columns may not add to totals due to rounding.

Discretionary Resource s 

### Discretionary resources differ from lost opportunity resources due to their acquisition availability at any point with in the study horizon. From a theoretical perspective, this suggests all achievable technical potential for discretionary resources could be acquired in the study’s first year , though, from a practical perspective, this outcome is realistically impossible to achieve due to

infra structure and budgetary constraints and to customer considerations

.

Further, due to interactive effects between discretionary and lost opportunity resources, immediate acquisition would distort the potential for lost opportunity resources. For example, if

one assumes all homes would be weatherized in the first year of a program, potential ly available high

- efficiency HVAC equipment would decrease significantly (i.e., a high

- efficiency heat pump would save less energy in a fully weatherized home).

Consequently, the study addresse d discretionary resources in two steps :

1. Develop ing a 20

- year estimate of discretionary resource technical potential

, assuming technically feasible measure installations would occur equally ( at 5% of the totalPacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 69 

### available) for each year of the study

, and avoid ing distorti on of interaction s between discretionary and lost opportunity resources

, as described above.

2. Overlay ing a measure ramp rate to specify the timing of achievable discretionary resource potential, thus transforming a 20

- year cumulative technical value into annual,

incremental

, achievable values

.

The discretionary measure ramp rates specify only the timing of resource acquisition and do not affect the portion of the 20

- year technical potential achieved over the study period.

Figure 6 shows incremental (bars) and cumulative (lines) acquisitions for two different discretionary ramp rates. A measure on the 10

- y ear d iscretionary ramp rate reach es full maturity (85% of its total technical potential) in 10 years, with market penetration increasing in equal increments each year. A measure on the emerging technology discretionary ramp rate would take longer to reach full maturity (also 85% of total technical potential), but ultimately it would arrive at the same cumulative savings as the measure on the 10

- year ramp rate.

Figure 6 . Examples of Discretionary Measure Ramp Rates

In this study, discretionary measures accounted for 70 % of total technical potential and achieved 85% of that technical potential over the 20

- year horizon. Lost opportunity measures accounted for the remaining 30 % of total technical potential and achieved 65 % of that technical potential over 20 years (as described above). Overall, the study estimates 79% of total technical potential (discretionary and lost opportunity) can be achieved over the study horizon.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 70 

### Market Ramp Rates After addressing technical and general market constraints, the study applie d state

- specific market ramp rates to reflect the unique market characteristics of each state within PacifiCorp’s service territory that were not captured by the more generic measur e

- specific ramp rates

, as previously

described.

For example , robust Class 2 DSM programs have been offered in Utah and Washington for many years and thus have well

- developed delivery infrastructures and high customer awareness in these states. In Wyoming, with newer Class 2 DSM programs , the study assume s the ramp

- up time for full acquisition will be slower. California and Idaho markets fall between these extremes factoring in the company ’s smaller and more rural service areas in these states and the impac t on
market factors

.

To accurately reflect acquisition trends in each state, the Cadmus team designed market ramp rates to set identified 2013 achievable technical potential

, reflect ing a continued growth in market activity over PacifiCorp’s forecasted 2012 Class 2 DSM acquisitions in each state. Figure

7 illustrates these market ramp rates, with Utah and Washington un adjusted for market constraints ( i.e., assumed to be at full program maturity ), Idaho and California as ―established‖

markets

, and Wyoming as an ―emerging‖ market.

Figure 7 . Market Ramp Rates by State

Overlaying t hese market ramp rates on the measure ramp rates provided a final estimate of annual achievable technical potential in each state . For discretionary opportunities, slower acquisition pushes some resources out to later years, but the 20

- year achievable technical potential remains the same. However, due t o timing constraints of lost opportunities, failure to acquire these resources in early years may push opportunit ies beyond the 20

- year study period,PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 71 

### depending on the EUL. A s shown in Figure 8

, applying the ―emerging‖ market ramp rate in Wyoming only leads to a 2% reduction in 20

- year achievable technical potential.

Figure 8 . Example of Market Ramp Rate Impact s for Wyoming



## About Levelized Costs of Conserved Energy
In addition to achievable technical potential, the levelized cost of conserved energy (levelized cost) had to be determined to characterize each measure in the Class 2 DSM supply curves. Where possible, the study a ligned its approach for calculating levelized costs for each measure to

the Council’s levelized

- cost methodology, while recognizing differences in cost

- effectiveness screening in each state with in PacifiCorp’s service territory

. 47 

### Table 49 summarizes components of levelized cost in each PacifiCorp state assessed in this study

.

Table 49 . Levelized Cost Components by State

Component State

Washington Idaho California Wyoming Utah
Initial capital cost Included Utility incentive

Reinstallation cost Included Not included *

Annual incremental O&M Included Not included
Secondary energy impacts Included Not included

Non

- energy impacts Included Not included

Administrative costs 20% of incremental cost

* Assumes the customer will reinstall the measure upon burnout without utility intervention.

47 Failure to align costs used for IRP optimization with methods used to assess program cost

- effectiveness could lead to an inability to deliver selected quantities in a cost

- effective manner in a given jurisdi ction.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 72 

### Utah ’s levelized cost was assessed on a Utility Cost Test ( UCT ) basis, while the other states are

evaluated on a Total Resource Cost ( TRC ) basis. T o maintain consistency with the Council

, RTF and accepted regulatory practices , secondary benefits, non

- energy impacts, and incremental

O&M have been included for Washingto n and Idaho . In California and Wyoming, only capital costs (initial and reinstallation) and administrative costs have been included. For Washington

resources , the Council’s 10% conservation credit will appl y during the IRP modeling process

, and this credit has not been included in the levelized costs presented in this report.

Th e approach to calculating a measure’s levelized cost of conserved energy aligned with that of

the Council ’s

, considering the costs required to sustain savings over a 20

- year study horizon, including reinstallation costs (except in Utah) for measures with useful lives less than 20 years. If

a measure’s useful life extended beyond the end of the 20

- year study, the Cadmus team incorporated an end effect, treating the measure’s levelize d cost over its useful life as an annual

reinstallation cost for the remainder of the 20

- year period

. 48 

### For example, Figure 9 shows the timing of initial and reinstall ation costs for a measure with an eight

- year lifetime

, in context with

the 20

- year study. As a measure’s lifetime in this study ends after the study horizon, the final four years (Year 17 through Year 20) have been treated differently, levelizing measure c osts over its eight

- year life and treating these as annual reinstallation costs.

Figure 9 . Illustration of Capital and Reinstallation Cost Treatment

For PacifiCorp’s Utah service territory, the study adopted the utility’s share of initial capital costs (i.e., an incentive amount) in the levelized cost calculation. The following assumptions regarding incentive amounts applied for Utah:

Specific program measure (e.g., evaporative coolers and appliance recycling) incentives aligned with the current program design.

Zero and negative incremental cost measures used incentives based on their assumed kWh savings, and on PacifiCorp’s average, first

- year
, cost per kWh saved of $0.02/kWh

. Company

- owned street lighting incentives were set to 100% of incremental

measure cost s

.

48 This method applied both to measures with a useful life greater than 20 years and those with useful lives extending beyond the 20 th year at the time of reinstallation.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 73 

### Incentives for all other measure s represented 70% of the incremental measure cost , based on a high ( but realistic ) incentive level required to achieve 85% of the technical potential

. 49



### For Utah, the study did not include reinstallation costs, given the assumption that the utility only provide d incentive s for first measure installations. That is, customers will reinstall the measure without utility intervention , and savings persist throughout the p lanning period, though the cost

is incurred only during the first installation.

To determine an appropriate assumption for administrative costs, the Cadmus team review ed eight electric utilities’ recent (2010 and 2011) annual reports

, compa ring non

- incenti ve expenditures on Class 2 DSM programs with reported measure costs

. 50 

### The review included only utilities with sufficient information to determine incremental costs, and properly interpreting the data required some professional judgment

. The study excluded third

- party administrators

, as administrative costs may differ from utility

- sponsored programs

.

To most closely align with Class 2 DSM resources, the Cadmus team removed demand response, education, and renewable energy programs from the analysis ( subject to availability of granular data). Across these utilities, the Cadmus team found average administrative costs as 22.8% of

measure incremental costs. Removing one outlier with a 45% administrative percent led to a 19.9% average. 51 

### Consequently, the Cadmus te am used a 20% administrative cost assumption for

this assessment ( a formulation consistent with the Council’s assumed 20% administrative adder

in the 6 th 

### Power Plan )

. 

## Summary of Resource Potential s

Table 50 and Table 52 show 2032 baseline sales and cumulative potential by sector and state,

re spectively. Study results indicate 819 aMW of technically feasible

, energy

- efficiency potential by 2032, the end of the 20

- year planning horizon, with an estimated 648 aMW ( 79% of the

technical potential) a chievable a c ross all sectors and states ( or 12% of forecast ed baseline sales

in 2032 )

. As a percentage of baseline sales, savings vary by sector and state, as shown in Table

50 and Table 52

. These results account for line losses and represent savings at the generator. In addition, these values represent cumulative energy savings.

Th e cumulative e nergy savings differ s from the sum of incremental savings due to the phase

- in of energy standards. For example, although the potential includes CFLs in early years, these

CFLs have zero cumulative potential by the 20 th 

### year due to EISA provisions. In other words, the baseline accounts for higher

- efficiency standards, and

— based on the effective life by the end of the planning period

— all bulbs will be replaced by CFLs by following this standard.

49 Incremental measure costs vary by resource type (i.e., discretionary or retr ofit), with incremental costs equaling full costs for discretionary resources, and for lost opportunities, the incremental cost is the difference between

the standard

- efficiency and higher

- efficiency alternatives.

50 Utilities included (with state): Allian t Energy (IA); Avista (WA); Avista (ID); National Grid (MA); NSTAR (MA); PSE (WA); Xcel Energy (CO); and Xcel Energy (MN).

51 Appendix B

- 2 provides a list of utility administrative expenditures and incremental costs, estimated from the annual reports.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 74 

### The study estimate d demand impacts by spreading annual potential by state, sector, segment, and end use over hourly load shapes. Peak impacts

, reported below

, represent average demand savings in the top 40 hours of system demand ( occurring in summer )

. Peak impacts vary by sector and state, as shown in Table 51 and Table 53

.

These savings draw upon forecasts of fu ture consumption, absent PacifiCorp Class 2 DSM program activities. While these consumption forecasts accounted for past PacifiCorp Class 2 DSM resource acquisition , the identified estimated potential is inclusive of ( not in addition to ) forecasted program savings. As discussed, the 2032 forecasted baseline sales presented in this

report may differ from PacifiCorp’s official sales forecast

.

Table 50

. Baseline Sales, Technical and Achievable Technical Class 2 DSM Potential

( Cumulative aMW in 2032 ) by Sector

Sector Baseline

Sales (aMW) Technical

Potential (aMW) Technical as a

Percent of
Baseline Sales Achievable

Technical Potential (aMW) Achievable Technical

as a Percent of
Baseline Sales

Residential 1,295 274 21% 190 15%

Commercial 1,522 282 19% 234 15%

Industrial 2,352 243 10% 207 9%
Irrigation 129 16 12% 13 10%

Street l ighting 13 4 35% 4 30%

Total 5,311 819 15% 648 12% Note: Results may not sum to total s due to rounding

.



### Table 51

. Technical and Achievable Technical Class 2 DSM Potential ( Cumulative Coincident Peak MW in 2032) by Sector

Sector Technical Potential (MW) Achievable Technical

Potential (MW)

Residential 706 545

Commercial 493 407

Industrial 291 247
Irrigation 49 42

Street l ighting 0.6 0.5

Total 1,540 1,241 Note: Results may not sum to total s due to rounding

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 75 

### Table 52

. Baseline Sales, Technical and Ach ievable Technical Class 2 DSM Potential ( Cumulative aMW in 2032 ) by State

Territory State Baseline Sales (aMW) Technical

Potential (aMW) Achievable

Technical Potential (aMW) Achievable Technical as

Percent of Baseline
Sales

Pacific Power California 96 18 14 1 5 %

Washington 487 94 75 1 5 %

Subtotal 582 112 88 1 5 %

Rocky

Mountain

Power Idaho 268 47 34 1 3 %

Utah 3,002 491 389 1 3 %
Wyoming 1,459 169 136 9 %

Subtotal 4,729 707 560 1 2 %

Total 5,311 819 648 1 2 %
Note: Results may not sum to total s due to rounding

.



### Table 53 . Technical and Achievable Technical Class 2 DSM Potential ( Cumulative Coincident Peak MW in 2032) by State

Territory State Technical Potential (MW) Achievable Technical Potential (MW)

Pacific Power California 28 23

Washington 172 140

Subtotal 200 163

Rocky Mountain Power Idaho 77 61

Utah 1,042 839
Wyoming 221 178

Subtotal 1,339 1,078

Total 1,540 1,241 Note: Results may not sum to total s due to rounding.



### Table 54 shows technical and achievable technical potential by sector and resource type, referring to whether resources can be considered discretionary or represent lost opportunities. Discretionary r esource opportunities exist in current building stock (retrofit opportunities in existing construction), while lost opportunities rely on equipment burnout and new construction.

For the industrial and irrigation sectors

, the study model ed all measures as discretionary

resources

. While in practice, natural equipment turnover and new construction will drive some opportunities , the majority of savings will likely be acquired during regular rebuilding and

refurbishment of existing equipment stocks. In combinat ion with the nature of available data, these practices pose difficulties in definitively isolating lost opportunity shares of savings. Therefore, all savings in these sectors have been classified as discretionary , an approach

consistent with the Council

. 52 

### C aveats aside, study results estimate d iscretionary resources

52 R esidential and commercial assessments tied lost opportunities to specific forecasts for new construction and to decay patterns for specific types of end

- use equipment ( e.g., chillers and water heaters). In the industrial sector,

the two elements have insuf ficient market data to allow delineation of lost opportunities (though many exist)

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 7 6 

### represent 75% ( 488 aMW out of 648 aMW ) of cumulative achievable technical potential in

2032

, as shown in Table 54

.

Table 54

. Technical and Achievable Technical Class 2 DSM Potential ( Cumulative aMW in 2032) by Sector and Resource Type

Sector Technical Potential Achievable Technic al Potential

Discretionary Lost Opportunity Discretionary Lost Opportunity

Residential 113 160 96 94

Commercial 202 80 172 62

Industrial 243 0 207 0
Irrigation 16 0 13 0
Street Lighting 0 4 0 4

Total 574 245 488 160 Note: Results may not sum to total s due to rounding

.



### Figure 10 provides a graphical representation of the cumulative achievable technical potential by

sector in each study year, incorporating measure and market ramp rates, as discussed previously

. The 20 20 dip in potential represents the effect of the EISA

- backstop provision ; i.e., all general service incandescent lighting will have to meet minimum efficacy standards of 45 lumens per watt starting in 2020

. In the baseline forecast, due to the comparatively short life of incandescent lighting and an assumption that CFLs become the de facto standard by 2020 (because they are the lowest cost option that currently meets the 45 lumens per w att), it is

assumed tha t all incandescents are replaced with CFLs by 2020. T hese impacts are captured in

Cadmus’ baseline forecast ; therefore , there is assumed to be no impact after 2019 from previously installed CFLs that would lead to a drop in cumulative potential even though there is new incremental potential.

Figure 10

. Acquisition Schedule for Achievable Technical Potential by Year and SectorPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 77 

## Class 2 DSM Detailed Resource Potential

Residential Sector

Residential customers in PacifiCorp’s service territory account for about one

- quarter of

forecasted 2032 baseline retail sales. S ingle

- family, manufactured, and multifamily dwellings comprising this sector present a variety of potential savings sources, including equipment efficiency upgrades (e.g., heat pumps, air conditioning ), improvements to building shells (e.g., insulation, windows, air sealing ), and increases in lighting efficiency.

Based on resources included in this assessment, the Cadmus team estimated residential sector

, cumulative

, a chievable technical potential of 190 aMW over 20 years, corresponding to a 15 %

reduction (ranging from 13 % to 17 %

, by state) in forecasted 2032 baseline residential consumption ( as shown in Table 55 ). Utah , which represents 63% of forecasted 2032 residential

baseline sales

, account s for 6 2 % ( 112 aMW) of this identified achievable technical potential

.

Table 55 . Re sidential Sector Class 2 DSM Potential by State (aMW in 2032 )

Territory State 2032

Baseline
Sales Technical

Potential Achievable

Technical Potential Achievable Technical As

Percent of Baseline Sales

Pacific Power California 46 9 7 14%

Washington 196 44 33 17%

Subtotal 242 54 39 16%

Rocky

Mountain

Power Idaho 106 25 16 15%

Utah 820 169 118 14%
Wyoming 127 26 17 13%

Subtotal 1,053 220 151 14%

Total 1,295 274 190 15%
Note: Results may not sum to total s due to rounding.



### As shown in Figure 11

, single

- family homes represent 7 6 % ( 145 aMW) of total achievable

technical residential potential, followed by multifamily ( 3 2 aMW) and manufactured homes ( 13 aMW). Each home type’s proportion of baseline sales primarily drive s these results, but other factors, such as heating fuel sources, play an important role in determining potential.

For example, multifamily homes more commonly use electric ity for space heating than do single

- family homes , increas ing their relative share s of space heating potential. Alternatively, lower use per customer for multifamily units decrease s this potential

, as some measures may not
be cost

- effective at lower consumption levels. Other factors include varying equipment saturation levels by state, home type, and weather, as reflected in heating and cooling loads.

S pecific factors affecting results have been included in the state

- and segment

- specific data, provided in Volume II, Appendix C.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 78 

### Figure 11 . Residential Sector Class 2 DSM Achievable Technical Potential

by Segment (Cumulative in 2032 )

HVAC system savings account for over one

- half ( 59 % ) of total achievable technical potential by end use ( as sho wn in Table 56 and Figure 12 ) , where s pace heating (central and room) accoun ts
for 2 6 %, cooling accounts for 2 7 %, heat pumps account for 3 %, and an additional 3% comes

from ventilation and circulation

. While significant opportunities exist in residential l ighting during the early years examined by this study, this end use accounts for only 8 % of cumulative

achievable technical potential by 2032

, driven down by impact s of the 2020 EISA backstop provision. A dditional potent ial includes plug loads

, water heating

, refrigerators and freezers (included in appliances

, and almost exclusively associated with recycling ), and other appliances.

These results reflect Utah’s large share of forecasted residential sales ( 62 % ). While assumptions driving lighting and appliance savings tend to remain consistent throughout the territory, other

end uses can be affected by customer demographics (such as saturations of specific end uses)

, which can vary widely between states. For ex ample, 84% of cooling savings shown in Table 56

and Figure 12 occurs in Utah. D etailed results show ing achievable technical potential for individual states and home types

, provided in Volume II, Appendix C

, reflect differences in equipment saturations, shares for electricity, and baseline sales.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 79 

### Table 56

. Residential Sector Class 2 DSM Potential by End Use ( Cumulative aMW in 2032 )

End Use Baseline

Sales Technical

Potential Achievable

Technical Potential Achievable

Technical as
Percent of
Baseline Sales Achievable

Technical as
Percent of

Total
Computer 33 2 2 5% 1%
Cooking oven 11 0.2 0.1 1% 0%
Cooking range 5 0.0 0.0 0% 0%

Cool central 207 62 50 24% 26%

Cool room 9 1 1 11% 1%
Copier 2 0.0 0.0 2% 0%

DVD 4 0.4 0.4 10% 0%

Dehumidifier 1 0.1 0.1 6% 0%
Dryer 95 1 1 1% 1%

Freezer 30 8 7 23% 4%

Heat central 151 45 26 17% 13%
Heat pump 27 8 6 22% 3%

Heat room 150 36 23 15% 12%
Home audio system 11 1 1 7% 1%
Lighting interior specialty 23 16 14 60% 7%
Lighting standard 82 7 2 2% 1%

Microwave 20 3 2 10% 1%

Monitor 7 0.2 0.2 2% 0%

Multifunction device 0.0 0.0 0.0 0% 0%

Other 29 0.0 0.0 0% 0%
Plug load other 77 3 2 3% 1%
Pool pump 2 1 1 45% 1%

Printer 21 1 1 4% 1%
Refrigerator 70 21 12 17% 6%
Set top box 13 3 3 20% 2%

TV 46 2 2 4% 1%

Ventilation and circulation 66 13 5 7% 3%
Water heat GT 55 gal 9 4 4 42% 2%
Water heat LE 55 gal 93 33 27 29% 14%

Total 1,295 274 190 15% 100%PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 80



### Figure 12 . Residential Sector Class 2 DSM Achievable Technical Potential by End Use in 2032



## Commercial Sector

For the commercial sector

, results indicate 234 aMW of cumulative achievable technical potential over 20 years. As in the residential sector, Utah dominate s this potential ( 70 % ) due to its large share (70%) of forecasted baseline sales

. Table 57 lists commercial sector potential by state.

Table 57 . Commercial Sector Class 2 DSM Potential by State ( Cumulative aMW in 2032 )

Territory State Baseline
Sales Technical

Potential Achievable

Technical Potential Achievable Technical as

Percent of Baseline Sales

Pacific Power California 33 6 5 17%

Washington 162 34 28 18%

Subtotal 195 40 34 18%

Rocky

Mountain

Power Idaho 61 11 9 15%

Utah 1,064 196 163 15% Wyoming 202 36 29 15%

Subtotal 1,328 242 200 15%

Total 1,522 282 234 16%

Note: Results may not sum to total s due to rounding

.



### As shown in Figure 13

, ― miscellaneous ‖ buildings represent the largest share of cumulative

, achievable

, technical potential in the commercial sector (3 6 %)

. These buildings either are unclassified within PacifiCorp’s Customer Information System or are classified to a segment outside the named segments (e.g.

, firehouses ). Considerable savings opportunities also emerged

in the commercial sector’s office ( 17 % ), school ( 10 % ), and retail ( 8 % ) segments. Lower levels of achievable technical potential appeared in lodging facilities, warehouses, restaurants, groceryPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 81 

### stores, health care facilities , and data centers

. Volume II, Appendix C

, provides d etailed information regarding achievable tech nical potential within each state

.

Figure 13 . Commercial Sector Class 2 DSM Achievable Technical Potential by Segment in 2032

L ighting efficiency (including interior and exterior applications) represents the largest portion of

achievable technical potenti al in the commercial sector ( 37 % ), followed by cooling (1 6 % ) and

ventilation and circulation ( 13 % ), as shown i n Table 58 and Figure 14 . These results reflect the pending federal standard, effectively outlawing most T

- 12 la mps

.

Table 58

. Commercial Sector Class 2 DSM Potential by End Use

( Cumulative aMW in 2032 )

End Use Baseline

Sales Technical

Potential Achievable

Technical

Potential Achievable

Technical as
Percent of

Baseline
Sales Achievable

Technical as
Percent of

Total
Computers 32 6 5 16% 2%
Cooking 4 1 0.5 13% 0%
Cooling c hillers 10 4 4 34% 2%
Cooling DX e vap 99 40 34 34% 14%
Cooling room 2 1 1 24% 0%

Fax 2 1 1 39% 0%

Flat screen monitors 7 0.2 0.1 2% 0%

Freezers 1 0.1 0.1 12% 0%
Heat pump 24 8 7 28% 3%
Lighting exterior 126 38 32 26% 14%
Lighting interior fluorescent 324 39 33 10% 14%PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 82 End Use Baseline

Sales Technical

Potential Achievable

Technical

Potential Achievable

Technical as
Percent of

Baseline
Sales Achievable

Technical as
Percent of

Total
Lighting i nterior HID 78 8 7 9% 3%
Lighting i nterior Other 86 14 12 14% 5%
Lighting interior screw base 42 4 2 4% 1%

Other 40 13 11 28% 5%
Other plug load 94 7 6 6% 3%
Photo copiers 8 0.1 0.1 1% 0%

Printers 6 0.2 0.2 3% 0%
Refrigeration 87 22 18 21% 8%
Refrigerators 7 2 1 21% 0%

Servers 6 1 1 19% 0%
Space heat 78 23 19 25% 8%
Vending machines 13 3 2 16% 1%

Ventilation and Circulation 327 38 31 10% 13%

Water h eat GT 55 g al 1 0.2 0.2 18% 0%

Water h eat LE 55 g al 20 8 7 33% 3%

Total 1,522 282 234 15% 100%

Note: Results may not sum to total s due to rounding ; ― o ther‖ includes servers, fans, and HVAC in data centers.



### Figure 14 . Commercial Sector Class 2 DSM Achievable Technical Potential by End Use in 2032PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 83 

## Industrial Sector
The study assessed t echnical and achievable energy

- efficiency potential for major end uses within 14 major industrial segments in PacifiCorp’s servi ce territory. These customer segments
were based on SIC 53 

### allocations in PacifiCorp’s customer database

. The assessment estimated

207 a MW of industrial a chievable technical potential, representing approximately 9 % of

forecasted 2032 industrial baseline sales.

Table 59 . Industrial Sector Class 2 DSM Potential by State ( Cumulative aMW in 2032 )

Territory State Baseline
Sales Technical

Potential Achievable

Technical Potential Achievable as Percent of

Baselin e Sales

Pacific Power California 4 1 0.4 10%

Washington 108 13 11 10%

Subtotal 112 14 12 10%

Rocky Mountain

Power Idaho 29 3 2 8%

Utah 1,084 121 103 9%
Wyoming 1,127 106 90 8%

Subtotal 2,240 229 195 9%

Total 2,352 243 207 9%

Note: Results may not sum to total s due to rounding

.



### In examining aggregate results for the industrial sector, some caution should be used in associating summary potential information for a particular facility type to individual states.

While every state included nearl y all residential and commercial customer segments

, some industrial sector facility types applied only to a single state. Utah, for example, is the only state

to indicate machinery and equipment manufacturing potential

. Volume II, Appendix C

, provides

s tat e

- and industry

- specific results

.

Miscellaneous manufacturing represents the largest percentage of achievable technical potential (16%), as shown in Figure 15

. This includes all manufacturing that is unclassified or fall s outside other named segments, such as apparel or leather manufacturing. Industrial machinery represents the segment with the next largest portion of potential.

53 SIC, the Standard Industrial Classification system, is used to identify the industry of a given customer.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 84



### Figure 15 . Industrial Sector Class 2 DSM Achievable Technical Potential by Segment in (Cumulative in 2032 )

The majority of industrial sector savi ngs ( 60 % ) can be attribut ed to efficiency gains in air

compress ors , pumping, air distribution , and other motors ( includ ing mining application s )

. As

many motors used in mining do not fit into traditional industrial motor categories, they have been

classified as ― Motors

— Other‖ and represent a significant s lice of po tential (2 7 aMW). Lighting and process heating present the two end uses with the most savings, each accounting for 20% of achievable technical potential. R emaining potential split s between HVAC 54 

### and other building improvements, process improvements, and lighting ( as shown in Figure 16 and Table 60 ).

Table 60

. Industr ial Sector Class 2 DSM Potential by End Use ( Cumulative aMW in 2032 )

End Use Baseline

Sales Technical

Potential Achievable

Technical

Potential Achievable Technical

as Percent of

Baseline Sales Achievable

Technical
as Percent of Total

Fans 141 12 11 7% 5%

HVAC 220 30 25 12% 12%
Lighting 158 48 41 26% 20%

Motors

- other 674 31 27 4% 13%

Other 111 7 6 5% 3%

Process cool ing 118 7 6 5% 3%

Process heat ing 235 47 40 17% 20 %
Pumps 241 19 16 7% 8%

Indirect boiler 33 0 0 0% 0%

54 A substantial portion of industrial HVAC savings derive from clean room applications.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 85 End Use Baseline

Sales Technical

Potential Achievable

Technical

Potential Achievable Technical

as Percent of

Baseline Sales Achievable

Technical
as Percent of Total

Process air

c omp ressors 152 30 25 16% 12%

Process electro

chemical 130 0 .0 0 .0 0% 0%

Process other 73 0.3 0.3 0% 0%
Process refrig eration 64 11 9 14% 4%

Total 2,352 243 207 9% 100%



### Figure 16 . Industrial Sector Class 2 DSM Achievable Technical

Potential by End Use ( Cumulative in 2032 )



## Irrigation Sector
Although irrigation potential remains small compared to other sectors

, the study estimated achievable technical potential represents 10 % of 2032 baseline sales , with more than one

- half of

this potential in Idaho. I rrigation sector electricity consumption primarily consists of motors used for pumping, with a much smaller portion used for miscellaneous, non

- pumping end uses. 55


### Consequently , all irrigation potential derives from measures improv ing pumping efficiency, including high

- efficiency motors, irrigation system improvements , and SIS

. Table 61 shows c umulative potential in 2032 associated with these meas ures.

55 Non

- pumping end uses include system controls and motor drives for wheel

- based systems.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 86 

### Table 61 . Irrigation Sector Class 2 DSM Potential by State ( Cumulative aMW in 2032 )

Territory State Baseline
Sales Technical

Potential Achievable

Technical Potential Achievable as Percent of
Baseline Sales

Pacific Power California 12 2 1 10%

Washington 20 2 2 10%

Subtotal 32 4 3 10%

Rocky Mountain

Power Idaho 71 9 7 10%

Utah 24 3 2 10%
Wyoming 3 0.3 0.3 10%

Subtotal 97 12 10 10%

Total 129 16 13 10%

Note: Results may not sum to total s due to rounding

.



### Irrigation savings mainly originate from reduced pump motor energy use, which may be

achieved from reduced pressure , reduced flow

, 56 

### or both. The savings magnitude also directly

relate s to pump lift (total dynamic head), which varies across different servic e territories . This

proves a critical consideration in delivering cost

- effective programs in this sector, which will likely become more viable in jurisdictions such as Idaho where deep wells tend to be more

common ly used for irrigation water.



## Street Light ing

U pgrading high

- pressure
, sodium

, street lighting fixtures to LEDs offers approximately 3.7 aMW

in achievable technical potential by 2032 , representing a reduction in forecasted baseline sales of

a pproximately 30 % , as shown in Table 62

.

Table 62 . Street Lighting Sector Class 2 DSM Potential by State

( Cumulative aMW in 2032 )

Territory State Baseline
Sales Technical

Potential Achievable

Technical Potential Achievable as

Percent of
Baseline Sales

Pacific

Power California 0.3 0.1 0.1 31%

Washington 0.9 0.3 0.3 30%

Subtotal 1.2 0.4 0.4 30%

Rocky

Mountain

Power Idaho 0.5 0.2 0.2 33%

Utah 9.7 3.3 2.8 29%
Wyoming 1.3 0.5 0.4 31%

Subtotal 11.5 4.0 3.4 30%

Total 13 4.4 3.7 30%

Note: Results may not sum to total s due to rounding

.



### Across all states, customer

- owned fixtures account for 68% of achievable technical street lighting potential in 2032

. Company

- owned fixtures capture the remaining 32% of achievable technical potential. Table 63 shows achievable technical potential for company

- and customer

owned fixtures, by state.

56 This includes scientific irrigation scheduling, which saves energy by minimizing irrigation requirements.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 87 

### Table 63 . Street Lighting Sector Class 2 DSM Achievable Technical Potential by

State and Fixture Owner ship ( Cumulative aMW 2032)

Territory State Baseline Sales Achievable Technical Potential

Company

- Owned Customer

- Owned Company

- Owned Customer

- Owned

Pacific

Power California 0.1 0.2 0.0 0.1

Washington 0.4 0.5 0.1 0.1

Subtotal 0.5 0.7 0.1 0.2

Rocky

Mountain

Power Idaho 0.0 0.5 0.0 0.2

Utah 2.3 7.3 0.7 2.2
Wyoming 1.2 0.1 0.4 0.0

Subtotal 3.5 7.9 1.0 2.3

Total 4.0 8.6 1.2 2.6

Note: Results may not sum to total s due to rounding

.



## Comparison of Results with the 2011 Assessment

As noted , this assessment builds upon a study completed in 2011, including the following updates to the Class 2 DSM analysis :

A ccounting for new ly enacted building codes and equipment efficiency standards , even if they have not yet taken effect ;

A djusting for PacifiCorp’s actual and projected DSM program accomplishments from 2010 through 2012 ;

I ncorporating adjustments to measure savings , based on recent evaluation results, including data available from the Regional Technical Forum (RTF) ;

A pplying 2011 customer information to determine segmentation ; and

U tilizing 2012 sales and customer forecasts.

T ogether, these chan ges decrease d total achievable technical 20

- year potential from 1,156 aMW

to 648 aMW, a system

- wide decrease of 44 %.

Much of this decrease resulted from changes in long

- term forecasted baseline sales. Compared to

the 2011 A ssessment, the assessment’s forecasted 20

- year sales have decreased by 25%. Sales in

Pacific Power ’s territory ( Washington and California ) decreased by 12% , compared to Rocky

Mountain Power ’s territory ( Idaho

, Utah , and W yoming )

, which decreased by 27%. The

commercial sector saw the most significant decrease in projected sales, at 36%. Residential loads decreased by 28%

, and industrial decreased by 16% ( with minimal load changes occurr ing for street lighting and irrigation).

Part of this decrease, as described in the Introduction sec tion of this study

, resulted from incorporation of pending equipment efficiency standards. In addition, baseline sales were impacted by naturally occurring potential, including turnover of existing equipment to prevailingPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 88 

### or pending standards on burnout as well as on the continuing adoption of high

- efficiency units. 57


### For example, baseline sales for residential plug load equipment in the 20 th 

### year drop ped from the prior study by about 40% (142 aMW)

, largely due to this study projecting continuing high

ENERGY STAR market shares. 58



### Table 64 compar es , by sector, achievable technical potential ( in aMW and as a percent age of sales) between the two assessments

. T his comparison includes potential in the 20 th 

### year (2030 for the 2011 Assessment and 2032 for the current assessment).

Table 64 . Comparing Class 2 DSM Achievable Technical

Potential in 2011 and Current Assessments

Sector Achievable Technical Potential

( Year

- 20 Cumulative aMW) Achievable as a Percent of

Year

- 20 Baseline Sales

2011

Assessment Current

Assessment 2011

Assessment Current

Assessment

Residential 514 190 29% 15%

Commercial 361 234 15% 15%

Industrial 265 207 9% 9%
Irrigation 13 13 10% 10%
Street lighting 4 4 36% 30%

Total 1,156 648 16% 12%



### Savings assumptions served as o ne driver of th is decrease in potential. As shown in Volume II, Appendix C, measure savings were updated to reflect new data, including the residential SEEM

models and recent RTF measure savings workbooks. The 2011 assessment primarily relied on workbooks used in the 6 th Power Plan. In Washington, most measures were updated based on recent RTF work. RTF updates primarily reflect recent evaluation work as well as ongoing

review s of savings assumptions.

Accounting for this sales change, nonresidential potential ( as a percent of sales ) did not change significantly from the 2011 Assessment . For the commercial, industrial , and irrigation secto rs
, both studies estimate d cumulative achievable technical potential of 15%, 9%

, and 10% of

year

- 20 baseline sales , respectively

. Street lighting potential changed from 36% to 30% of sales, due to availability of updated data on existing s tock.

While potential, in percentage terms, remained the same at the sector level for commercial, industrial, and irrigation , d ifferences occurred between the two studies at the end

- use level. For example, this study thoroughly reviewed and updated measure s comprising interior lighting potential ; these were based on more recent lighting fixture data, a methodology to estimate post

installation lumen requirements, 59 

### new building codes

, and the 2012 lighting standard. Table 65

57 These high saturations will l ikely continue without PacifiCorp program intervention.

58 Includes television, DVD players, computer monitors, computers, set top boxes, and other plug loads; from: http://www.energystar.gov/index.cfm?c=partners.unit_shipment_data_archives

59 The 2011 Ass essment determined potential by assuming a reduction in lighting power density while holding total lumens constant. The current study allows lumens to vary by up to 10% of pre

- levels.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 89 

### provides differences in the two studies at a rolled

- up
, end

- use level for the commercial sector

, including some key drivers for these differences.

In the residential sector, however, cumulati ve achievable technical potential as a percent age of

year

- 20 baseline sales decreased from 29% to 15 % , driven by many factors

— most significant ly updates to assumed market shares of ENERGY STAR appliances and office equipment, including dehumidifiers, compu ters, monitors, televisions , set top boxes, and printers. Using the

most recent ENERGY STAR market share reports at the time of this study , the potential

attributed to this equipment dropped by more than two

- thirds.

Another notable change emerged in using SEEM models to estimate UECs and savings for

HVAC and shell measures. T he prior study used Energy

- 10 models , whereas the RTF used SEEM models to estimate savings for shell and other measures. For all HVAC end uses, the SEEM models reduced savings relative to the prior study. 60 

### Table 66 presents additional details on differences between the two studies in the residential sector, at the end

- use level.

60 Other factors, such as measure saturations, efficiency standards, an d measure efficiency levels also contributed to changes in the HVAC potential, but SEEM models alone would drive the savings down.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 90



### Table 65 . Comparison of 2011 and Current Assessment Commercial Class 2 DSM Achievable Technical by End Use Group (Cumulative aMW in Year 20)

End Use Group Baseline Sales Achievable

Technical Potential Change in Potential
Key Driver s of Differences 2011 Current 2011 Current aMW Percent

Residential

- style appliances 0 8 0 1 1 N/A Refrigerator and freezer recycling included in the current study

. Data centers N/A 40 0 11 11 N/A Data centers not included in the previous study

. Space Heating and Cooling 305 213 115 65

- 50

- 43% Review of applicability assumptions and savings estimates

. Lighting (interior and exterior) 1

, 081 656 166 86

- 80

- 48% Updated methodology

.

Office equipment 273 149 30 12

- 18

- 59% Higher ENERGY STAR market share s led to lower baseline sales. Savings shifted from achievable technical to naturally occurring.

C ooking and vending machines 6 17 0 3 3 N/A Vending machines not included in the previous study.

Refrigeration 172 87 25 18

- 7

- 28% Reallocation of sector sales by segment

, based on the latest PacifiCorp customer database

, indicated lower total sales in segments using refrigeration.

Servers (excludes d ata c enters) N/A 6 N/A 1 1 N/A Not included in the prior study

.

Ventilation and Circulation 499 327 14 31 17 121% A n a dditional measure (motors VFD) account ed for most of the
difference in potential change ; Y ear

- 20 s ales dropped due to constant EUI assumption in current study

. Water heat (includes clothes washers and dishwashers) 32 21 11 7

- 4

- 35% No significant change in potential as a percent of sales. Sales dropped due to new efficiency standards.

Total 2

, 36 7 1

, 524 361 23 4

- 126

- 35%

* N umbers may not sum to total s due to rounding

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 91



### Table 66 . Comparison of 2011 and Current Assessment Residential Class 2 DSM Achievable Technical by End Use Group (Cumulative aMW in Year 20)

End

- Use Group Baseline Sales Achievable

Technical Potential Change in Potential
Key Driver s of Differences 2011 Current 2011 Current aMW Percent

Appliances (refrigerator, freezer, dryer) 281 195 16 20 4 25% Updated efficiency standards for refrigerators and freezers.

The 2011 Assessment assumed an end to appliance recycling

in Year 5 ; current study maintains this throughout the study

horizon.

Cooking (range and oven) 39 16 3 0.1

- 3

- 97% Updated efficiency standards

.

Space heating and cooling 660 544 276 106

- 170

- 62 % Updated efficiency standard for heat pumps , updated savings based on SEEM models, and updated technical feasibility for evaporative coolers for each state

.

Lighting (standard and specialty) 199 105 83 16 67

- 81 % Revised methodology to account for EISA, new assumptions on per home usage

. Office equipment 210 126 62 9

- 53

- 86 % Increase in ENERGY STAR market share projections

.

Pool pump 4 2 1 1 0 0 % Savings updated based on new usage data ; Y ear

- 20 sales dropped due to constant UEC assumption in current study

. Plug load (microwave, home audio, dehumidifier, other) 182 138 18 5

- 13

- 72 % Updated efficiency standards for dehumidifier ; increased
ENERGY STAR market share in baseline forecast

.

Ventilation and circulation 83 66 15 5

- 10

- 67 % Removal of the VFD motor measure in current study due to technical feasibility constraints

. Water heat (includes clothes washers and dishwashers) 130 102 41 31

- 10

- 24 % Updated efficiency standard for water heaters and appliances

.

Total 1

, 78 7 1

, 294 51 4 19 0

- 322

- 63 %

* N umbers may not sum to total s due to rounding

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 92 

# SUPPLEMENTAL RESOURCES

Scope of Analysis

As in the 2007 and 2011 Assessments, the term ―supplemental resources‖ refer red to renewable

and non

- renewable customer

- sited generation. While these resources may not reduce a building’s energy consumption or peak demand, they provide benefits to the electric grid by reducing

energy amount s required from utility

- owned resources. This study assessed the following such

resources :

CHP

Solar P V

SWH

Traditi onally, such resources fall outside the standard classification of Class 2 DSM resources

for two main reasons : e ither they reduc e utility

- provided electricity consumption at the building

level ( and not at end use , as applies to CHP and PV)

, or they rely on renewable resources (PV and SWH).

For each technology, this report includes methods and results for estimating technical potential, market potential, and levelized energy cost s

. L evelized costs presented have been based on the

TRC test for all states and technologies , except for on

- site solar resources in Utah

, which use the UCT

. 

## Methodology Overview

For supplemental resources, the definition of technical potential is similar to that used in the

Class 2 DSM analysis , represent ing total electric generatio n (or savings, in the case of SWH) that

could be offset if all resources were installed in all technically feasible applications. For example, the PV technical potential assume d every rooftop with favorable (i.e., southern) solar

exposure would have a PV s ystem installed. This largely unrealizable potential should be

considered a theoretical construct.

The next potential level is market potential

— analogous to achievable technical potential for

Class 2 DSM resources

. M arket potential measure s the likely pen etration within PacifiCorp ’s

service territory, given existing (or projected) market conditions. For supplemental resources, market potential is based on historic adoption of resources, accounting for state

- to

- state
variation s, as appropriate. For example, for PV

, market potential tie s to the presence or absence of utility rebates in each state

.

For each technology, the Cadmus team calculated a levelized cost from a total resource or utility perspective, depending on the state and technology. Although varia tions in assumptions exist between technolog ies , overall TRC levelized cost s include d :

The installation cost, less the federal investment tax credit ( ITC ) for systems installed

before 2017 , assuming the ITC expire s as planned on December 31, 2016. S tate tax credits and utility incentive s are not deducted from the installation cost

, as although thePacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 93 

### TRC test counts these as benefit s to customer s install ing the system s
, they are also

included as cost s to the state’s taxpayers, resulting in a zero net ef fect.

U tility cost s other than incentives

, interconnection for CHP

, or program administrative

costs for on

- site solar

.

O&M costs assumed to occur annually

, adjusted to the net present value.

Fuel costs for CHP , using PacifiCorp projections for average annual natural gas costs, by service territory (Pacific Power and Rocky Mountain Power). 61



### For on

- site solar resources in Utah

, the study calculated levelized costs

, reflecting the utility ’s

cost of administering the program

, including the following:

A dministration and marketing costs.

I ncentive amount s, assumed to be a percent age of installed cost s after applying the

federal tax credit 62 

### and accounting for projected trends in incremental costs. State tax
credits do not affect the utility incentive amoun t.

For both perspectives, the Cadmus team used PacifiCorp’s 6.88% nominal discount rate

, along

with a 1

. 9% inflation rate

, to adjust future costs to present dollars

. C osts were then divided by the system’s energy production over its life span, obtain ing the levelized cost of energy ( LCOE )

. E nergy production includes a line loss factor, varying by state and sector, as shown in Section 1 of this report

. T hese line loss values represent avoided losses on the utility system, not energy

loss from the customer

- sited unit to the facility ( which is assumed to be zero )

. E nergy production

over the system’s life account ed for system performance degradation , as applicable

.



## CHP

Technologies Assessed

CHP systems generate electricity and utilize waste heat for thermal l oad s, such as space or water heating. They can be used in buildings with a fairly coincident thermal and electric load or in buildings producing combustible biomass or biogas , such as lumber mills or landfills

.

Traditionally, CHP systems ha ve been install ed in hospitals, schools, and manufacturing facilities, but they can be used across nearly all C&I market segments with average monthly energy load s greater than about 30 kW. CHP broadly divide s into subcategories

, based on fuel s used ; n onrenewable CHP typically runs on natural gas, while renewable CHP runs on a biologically derived fuel (biomass or biogas).

61 PacifiCorp provided annual gas rate projections ( nominal $/MMB tu) for use in the levelized cost analysis

.

62 The incentive does not increase with expiration of the federal tax credit in 2016.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 94 

### The Cadmus team analyzed the same n onrenewable CHP systems as in the 2011 Assessment :

R eciprocating engines (RE)

M icroturbines (MT)

G as turbines (GT)

F uel cells (FC)

REs cover a wide size range, while GTs typically are large systems. FCs and MTs are newer technologies with higher capital costs, though FCs have the highest electrical conversion efficiency.

The renewable CHP assessment included the same te chnologies as the 2011 Assessme n t

, analyz ing industrial biomass systems and anaerobic digester biogas systems :

Industrial biomass systems are utilized in industries such as lumber mills or pulp and paper manufacturing where site

- generated waste products can be combusted in place of natural gas or other fuels. This analysis assume d the combustion process includes a CHP system (generally, steam turbines) to generate electricity on

- site. I ndustrial biomass

systems generall y operate on large scale s , with a capacity greater than 1 MW

.

Anaerobic digesters create methane gas (biogas fuel) by breaking down liquid or solid biological waste. Anaerobic digesters can be coupled with a variety of generators, including REs and MTs, and typically are installed at landfills, wastewater treatment

facilities

, (WWTF s ), and livestock farms.

The study did not include waste heat

- to

- power (WHP) system s, as initial research identified the following challenges:

The United States currently has very little WHP installed (33 sites, 557 MW, excluding landfill gas).

WHP can only be applied in industries producing high

- temperature heat (e.g., metal and chemical manufacturing).

WHP presents significant technical barriers (e.g., space limitations, disp ersed waste heat

sources, and low volume/seasonal operations).

Although WHP offers potential energy savings, low market awareness and willingness to adopt this technology at this time, coupled with relatively significant technical barriers, suggest small

m arket potential for these applications.



## Data Sources

The Cadmus team reviewed many data sources to determine inputs most appropriate for CHP analysis . As shown in Table 67

, U.S. Environmental Protection Agency ( EPA ) and U.S. Department of Energy ( DOE ) reports on CHP technologies provided many inputs, with other sources used for additional inputs, as appropriate

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 95 

### Table 67 . References for CHP Analysis

Source Inputs Website Link
Catalog of CHP Technologies, U.S. EPA System Size, Installed Cost, Heat Rate,
O&M Cost www.epa.gov/chp/documents /catalog_chptech_full.pdf

Biomass Combined Heat and Power Catalog of Technologies, U.S. EPA System Size, Heat Rate, O&M Cost,

WWTF Data www.epa.gov/chp/documents /biomass_chp_catalog.pdf

R.S. Means State Cost Adjustment N/A
Combined Heat and Power Partnership, U.S. EPA Federal ITC www.epa.gov/chp/incentives/

Gas

- Fired Distributed Energy Resource Technology Characterizations, U.S. DOE Measure Life www.nrel.gov/docs/fy04osti/3 4783.pdf

California Self

- Generation Incentive Program (SGIP) 10th Impact Evaluation Report Capacity Factor w ww.cpuc.ca.gov/PUC/energ y/DistGen/sgip/

California SGIP Combined Heat and Power Performance Investigation Performance Degradation www.cpuc.ca.gov/PUC/energ y/DistGen/sgip/
Market Opportunities for Biogas Recovery Systems at U.S. Livestock Facilities, U.S. EPA Agricultural CHP Data www.epa.gov/agstar/docume nts/biogas_recovery_systems _screenres.pdf
Agricultural Waste Management Field Handbook,
USDA Agricultural CHP Data policy.nrcs.usda.gov/OpenNo nWebContent.aspx?content=

31475.wba
Census of Agriculture, US DA Farm Data www.agcensus.usda.gov/Pub lications/2007/Full_Report/Vo lume_1,_Chapter_1_State_L

evel/
Landfill Methane Outreach Program (LMOP), U.S.

EPA Landfill Gas Data www.epa.gov/lmop/

Energy Insights CHP Eligibility by Facility Type and Size N/A

Combined Heat and Power Installation Database Existing CHP Installations www.eea

- inc.com/chpdata/
PacifiCorp 2011 Customer Data, Current Installations, Interconnection Cost,

Natural Gas Costs, Inflation Rate, Discount Rate, Line Losses N/A



## Inputs

The tables below s ummari ze key inputs for each technology

. Table 68

, Table 69

, Table 70 , and

Table 71 list assumptions for nonrenewable fuel systems by techn ology and size range

. Table 72

and Table 73 list assumptions for renewable fuel systems by fuel and technology

.

O&M costs represent typical maintenance costs and do not include fuel costs. The net heat rate, measured in Btu/kWh, equal s the increased system fuel use (t ota l fuel input to the CHP system

minus the fuel normally used to generate the same thermal output ) divided by the electricity

output

. In biogas systems, the analysis assume d waste heat fed back to the anaerobic digester f or biogas generation ; therefore, the total heat rate was used, rather than the net heat rate

.

For biogas systems, the cost shown represents the generator cost . Additional expense s for

build ing digester s have not been included

, as this could be completed in dependently of the CHP system. Similarly for biomass systems, the study assumed boiler and fuel processing systemsPacifiCorp Assessment of Long

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- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 96 

### would already be in place at large industrial facilities ; therefore, only CHP generator costs have

been included.

Table 68 . Inputs for Natural Gas Fuel Cells

Input 100

– 250 kW 250

– 750 kW 750

– 1,500 kW National average installation cost ($/kW) $6,310 $5,580 $5,250
Annual O&M cost ($/kWh) $0.038 $0.035 $0.032
Net heat rate (Btu/kWh) 4,168 6,022 6,043
Annual performance degradation 5%
Capacity factor 0.71
Measure life (years) 10

Federal ITC through 2016 30% of installed cost



### Table 69

. Inputs for Natural Gas

- Fired Gas Turbines

Input <3,000 kW ≥3,000 kW National average installation cost ($/kW) $3,324 $1,314 Annual O&M cost ($/kWh) $0.0111 $0.0074
Net heat rate (Btu/kWh) 7,013 5,839
Annual performance degradation 0%
Capacity factor 0.81
Measure life (years) 20

Federal ITC through 2016 10% of installed cost



### Table 70

. Inputs for Natural Gas

- Fired Microturbines

Input <50 kW 50

– 150 kW >150 kW National average installation cost ($/kW) $2,970 $2,490 $2,440 Annual O&M cost ($/kWh) $0.020 $0.0175 $0.016

Net heat rate (Btu/kWh) 7,313 5,796 6,882
Annual performance degradation 5%
Capacity factor 0.49
Measure life (years) 10

Federal ITC through 2016 10% of installed costPacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 97



### Table 71

. Inputs for Natural Gas

- Fired Reciprocating Engines

Input <200 kW 200

– 500

kW 500

– 2,000

kW 2,000

– 4,000 kW >4,000

kW National average installation cost ($/kW) $2,210 $1,940 $1,640 $1,130 $1,130
Annual O&M cost ($/kWh) $0.022 $0.016 $0.013 $0.010 $0.009
Net heat rate (Btu/kWh) 4,383 4,470 4,385 5,107 4,950
Annual performance degradation 6%
Capacity factor 0.40
Measure life (years) 20

Federal ITC through 2016 10% of installed cost



### Table 72

. Inputs for Industrial Biomass Steam Turbine Systems

Input <2,000 kW 2,000

– 5,000 kW >5,000 kW National average installation cost ($/kW) $1,117 $475 $429

Annual O&M c ost ($/kWh) $0.004

Heat rate (Btu/kWh) 4,515 4,568 4,388
Annual performance degradation 1%
Capacity factor 0.90
Measure life (years) 25

Federal ITC through 2016 10% of installed cost



### Table 73

. Inputs for Biogas Systems

Input FC GT MT RE National average installation cost ($/W) $5,713 $2,319 $2,633 $1,610

Annual O&M c ost ($/kWh) $0.025 $0.0085 $0.014 $0.0165
Heat rate (Btu/kWh) 8,705 12,400 12,703 10,357
Annual performance degradation 5% 0% 5% 6%
Capacity factor 0.71 0.81 0.49 0.40
Measure life (years) 10 20 10 20

Federal ITC through 2016 (% of installed cost) 30% 10% 10% 10%



### I nstallation costs shown in the above tables have been based on national averages. A nalysis adjusted these values for each state

, based on living cost s in the part of state served by PacifiCorp. Table 74 shows t hese adjustment factors ( with the cost in each state as a percentage

of th e national average cost).

Table 74

. CHP Cost Adjustments by State

CA ID OR UT WA WY

Material 103% 100% 100% 81% 103% 99%

Labor 114% 65% 97% 69% 93% 49%

Total 107% 88% 99% 77% 99% 82%PacifiCorp Assessment of Long

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The Cadmus Group, Inc. / Energy Services Division 98 

## Levelized Cost of Energy

The Cadmus team calculated the LCOE for each configuration shown above in each state and installation year (2013

– 

### 2032). Table 75 shows results for units installed in 2013 ( with d etails provided in Volume II, Appendix D

- 1 ).

Costs slight ly increase for systems installed after 2016, when the federal tax credit expires.

L evelized costs vary across states due to differences in cost

- of

- living adjustments, line losses,

and natural gas rates. E nergy production over the system’s life account s for system performance degradation.

The Cadmus team calculated levelized cost s based o n the TRC perspective for all states

, for consistency with treatment of other generation resources in the IRP, as t he se systems are treated

as Qualifying Facilities, as defined by The Public Utility Regulatory Policies Act of 1978

.

Table 75

. 2013 Levelized Cost by Configuration and State
Technology Size Range CA ID OR UT WA WY

Fuel Cell 100

– 250 kW $0.15 $0.15 $0.15 $0.15 $0.15 $0.15

250

– 750 kW $0.14 $0.14 $0.14 $0.14 $0.14 $0.14

750

– 1,500 kW $0.13 $0.13 $0.14 $0.14 $0.14 $0.14

Gas Turbine <3,000 kW $0.09 $0.09 $0.09 $0.09 $0.09 $0.09

>3,000 kW $0.06 $0.06 $0.06 $0.06 $0.06 $0.06

Microturbine <50 kW $0.13 $0.13 $0.14 $0.14 $0.14 $0.13

50

– 150 kW $0.11 $0.11 $0.11 $0.11 $0.11 $0.11

>150 kW $0.11 $0.11 $0.11 $0.11 $0.12 $0.11

Reciprocating Engine <200 kW $0.10 $0.10 $0.10 $0.10 $0.10 $0.10

200

– 500 kW $0.08 $0.08 $0.09 $0.09 $0.09 $0.09

500

– 2,000 kW $0.08 $0.08 $0.08 $0.08 $0.08 $0.08

2,000

– 4,000 kW $0.07 $0.07 $0.07 $0.07 $0.07 $0.07

>4,000 kW $0.06 $0.07 $0.07 $0.07 $0.06 $0.06

Biomass

— Steam Turbine <2,000 kW $0.01 $0.02 $0.02 $0.02 $0.02 $0.02

2,000

- 5,000 kW $0.01 $0.01 $0.01 $0.01 $0.01 $0.01

>5,000 kW $0.01 $0.01 $0.01 $0.01 $0.01 $0.01

Biogas Fuel Cell $0.09 $0.09 $0.09 $0.09 $0.09 $0.09

Gas Turbine $0.11 $0.11 $0.11 $0.11 $0.11 $0.11

Microturbine $0.05 $0.06 $0.06 $0.06 $0.05 $0.06

Reciprocating Engine $0.03 $0.04 $0.04 $0.04 $0.04 $0.04



## Technical P otential

The Cadmus team calculated technical CHP potential based on the sources described above, including PacifiCorp customer data, and data on farms, landfills

, and WWTFs with in PacifiCorp ’s service territory , resulting in a total estimated 20

- year system

- wide technical potential of 4,301 MW , as measured at the generator

. Tab le 76 , below, details technical potential by technology and by rated system capacity (MW).PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 99 

### The study based average energy production on the capacity factors of systems described above.

To avoid double

- counting opportunities across technologies, the study divided total potential for each size range into different technologies, based on distributions of existing installations for states within PacifiCorp’s territory. For example, for syste ms less than 500 kW, RTs, MTs, and FCs represented 77%, 19%, and 4% of installations, respectively. For all technologies, across all states, the technical potential for energy generation was estimated at 2,233 aMW (an average capacity factor of 0.52 ).

Tab le 76

. CHP Technical Potential by State and Technology ( Cumulative MW in 2032)

System Type Technical Potential (MW)

CA ID OR UT WA WY System

Natural Gas Total 54 162 346 2,546 449 354 3,911

< 500 kW 31 82 156 1,053 212 158 1,693

500

– 999 kW 3 8 40 409 87 36 583

1

– 4.9 MW 20 45 108 818 151 110 1,252

5 MW+ 0 26 42 264 0 49 382

Biomass Total 12 3 141 41 31 6 233

< 500 kW 1 2 22 11 5 1 43

500

– 999 kW 1 1 15 6 4 2 29

1

– 4.9 MW 10 0 71 16 13 3 113

5 MW+ 0 0 32 8 8 0 48
Biogas Total 2 22 31 52 8 42 157

Landfill 0 0 1 8 5 3 17

Farm 2 22 29 44 3 39 139

WWTF 0 0 1 0 0 0 1

Total 68 187 519 2,639 488 402 4,301



## Market P otential

The Cadmus team applied data on recent CHP system installations in PacifiCorp ’s service territory to determine market potential or likely installations in future years. The study based the

assumed annual market penetration rate on the actual capacity installed

, relati ve to estimated technical potential

, and calculated by dividing the average annual ca pacity (MW) of CHP installed from 2008 through 2011 by the estimated technical potential for the 2008

– 2032 period

. 63 

### P ercentage s of technical potential installed each year could then be applied to the

estimated

, 20

- year technical potential to calculate market potential over the next 20 years, as

shown in Table 77 and Table 78

. T h e study estimated a cumulative 20

- year market potential of

3 36 MW at the generator

.

63 Technical potential for 2008

– 2032 was calculated by adding the actual installations from 2008

– 2011 (seven new installations with a total capacity of 50 MW) to the 20

- year tec hnical potential estimated in this study. As installation data were not yet available for 2012, Cadmus assumed the 2012 installation rate equaled the average

of 2008

– 2011. The study calculated the market penetration rate as a single value across PacifiCorp ’s service area, due to the limited number of installations by state.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 100



### Table 77

. CHP Market Potential by State ( Cumulative in 2032)

Technology CA ID OR UT WA WY Total
System Capacity (MW) 5 .3 15 41 206 38 31 336
Number of Systems * 15 37 82 398 79 70 681
Total Energy (aMW) 3 7 24 101 18 15 168

* Number of systems does not include the reinstalled systems



### Table 78

. CHP Market Potential by Fuel ( Cumulative in 2032)

Technology Natural Gas Industrial Biomass Biogas Total
System Capacity (MW) 305 18 1 2 336
Number of Systems * 632 22 28 681
Total Energy (aMW) 147 16 5 168

* Number of systems does not include the reinstalled systems



### As the market potential was based on current installation rates, this study did not assume ramping. That is, each year’s incremental potential was assumed to be one

- twentieth of the total

20

- year potential. For measures with an effective life of less than 20 years, the study assume d the

measure would be reinstalled upon burnout.

Peak Impacts CHP unit p eak impacts were assumed the equivalent of system capacity. That is, all CHP systems could operat e at their nameplate capacity d uring peak periods. This resulted in peak impacts of 336 MW.



## Solar PV

Solar PV systems include a collection of solar modules, generally mounted on building roofs,

with an inverter to convert available sunlight into electricity compatible with a building’s

standard electrical infrastructure. W idely applicable in the residential and nonresidential sectors

, solar PV has been in use for several decades.



## Technical Potential

Methodology Determining technical potential for solar PV in PacifiCorp’s territory prima rily involved estimating roof areas available for residential and nonresidential building stock over the study period, combined with relevant industry data, projections for system power density (installed kW per square foot), and capacity factor projection s.

The study used building stock data gathered during PacifiCorp’s E nergy D ecision S urveys
, conducted in 2005 for commercial and in 2006 for residential , combined with 2011 customer
data and relevant building characteristic assumptions, to identify the tot al roof area expected

feasible for solar PV system installations. The Cadmus team then conducted a literature review of typical PV system power densit ies and expected efficiency improvements over the 20

- year study period , which enabled calculation of expected system power density. Finally, the study applied the PVWatts tool, developed by NREL, to calculate residential and nonresidential capacity factor values for each state.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 101 

### Figure 17 depicts high

- level steps for determining technical potential for solar PV. Technical and market potential account for line losses, as shown in the Introduction section of this report , and all potential results are prese nted as values at the generator.

Figure 17

. Calculation Steps for Technical Potential

Data Sources and Assumptions

As shown in Table 79

, th e Cadmus team used several sources to estimate technical potential in

each state.

Table 79

. Data Sources Used in Solar PV Technical Potential Calculations

Input Source Website Link

Available Roof Area by Building Type (Commercial) PacifiCorp Energy Decisions Surveys (2005 and 2006) N/A

Available Roof Area by Building Type (Residential) N/A

Number of Customers by Building Type (Commercial) PacifiCorp Customer Forecast Used in 2013 IRP and 2011 Customer Information System N/A

Number of Customers by Building Type (Residential) N/A

New Construction Rates by Building Type PacifiCorp customer forecast Used in 2013 IRP N/A

Portion of Roof Area Useable for Solar

PV Navigant Consulting, PV Grid Connected Market

Potential under a Cost Breakthrough Scenario

, 2004 http://www.ef.org/documen

ts/EF

- Final

- Final2.pdf

Power Density of Solar PV U.S. Department of Energy, Photovoltaics

- Energy for

the New Millennium: The National Photovoltaics Program Plan 2000

- 2004 , DOE/GO

- 10099

- 940 (Washington, DC, January 2000) Available upon request Total Roof Area

Shading and Orientation

System Power Density (including efficiency improvements)

Capacity Factors by State

Line

- loss Factors

Technical

PotentialPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 102 

### Results Figure 18 shows estimated 20

- year technical pot ential for solar PV in each state within PacifiCorp’s territory, indicating a combined technical potential of 9,725 MW for the residential

sector

, 16,208 MW for the nonresidential sector

, and 25,933 MW overall. 64



### Figure 18

. PacifiCorp Solar PV Technical Potential by State and Sector in 2032

Building stock within PacifiCorp’s territory in each state largely drove state

- specific technical potential. However, high technical potential alone did not drive market potential, as discussed in the following section.



## Market Potential

Methodology

Assumed market penetration rate s drew upon actual capacity instal led, relati ve to estimated technical potential

. The Cadmus team obtained installed capacity data from PacifiCorp for January 2010 through July 2012 net metering agreements in each state . In addition, PacifiCorp provided projections for the remainder of 201 2. Table 80 details these data.

64 Unless otherwise noted, all capacity results reported refer to direct current (DC) capacity values.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 103



### Table 80

. Installed Solar PV Capacity by State and Sector 2010

– 2012

Installed Capacity (MW)

State Sector 2010 2011 2012*

CA Res 0.027 0.108 0.272

NonRes 0.002 0.027 0.319

ID Res 0.024 0.008 0.086

NonRes 0.013 0.166 0.002

OR Res 1.593 1.964 2.679

NonRes 1.564 3.322 3.785

UT Res 0.561 0.797 1.032

NonRes 0.486 1.229 3.917

WA Res 0.055 0.064 0.104

NonRes 0 0.078 0.023

WY Res 0.075 0.029 0.041

NonRes 0.081 0.053 0.024

Total Res 2.335 2.97 4.214

NonRes 2.146 4.875 8.07

* Note: The 2012 installed capacity was based on actual data through July and projected data for August through December.



### Each state received an annual market penetration rate, based on the presence (or lack thereof) of incentive programs in the state. Using data from Table 80

, the Cadmus team calculated the

average annual percent age of technical potential achieved in the states with long

- term incentive programs (Oregon and California) and in the states without inc entive programs (Washington, Idaho, and Wyoming) . The Cadmus team averaged market potential in Oregon and California to estimate the long

- term market penetration for Utah.

Although Utah had higher installation rates, relative to technical potential, than non

- program states, Utah’s incentive program remains in the pilot stage , and it likely does not accurately

represent the long

- term impacts of a mature and long

- running incentive program. Therefore, using installation data to date for Utah could underrepres ent long

- term market penetration rates.

This methodology, which the study used for calculating market penetration, updated the methodology used in the 2011 Assessment

, which based the market penetration rate on PV incentive programs throughout the United States with available installed capacity data. Very few states in PacifiCorp's territory had such data available at that time, and, in addition, most data were outdated. (In the Results section, Table 82 compares market penetration rates used in th is study to those in the 2011 Assessment .)

Data Sources To calculate annual and total market potential for the residential and nonresidential sectors in each state, the Cadmu s team used a combination of reported actual capacity installed, by state and sector; technical potential

, calculated as described above; and ramp rates. Table 81 lis ts these

data sources.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 104



### Table 81

. Data Sources and Assumptions for Solar PV Market Potential

Input Source Website Link

Installed Capacity Based on executed net metering agreements through July 2012 and projected through December 3012

, provided by PacifiCorp

. N/A

Ramp Rate (for states

without incentive

programs : ID, WA, WY ) Lost Opportunity Emerging Technology Ramp Rate

. www.nwcouncil.org/energy/powerplan/6/

default.htm

Ramp Rate (OR and CA) * Assumed flat ramp rate of 5% per year

, over 20 years,
reflect ing presence of an established incentive

program

. N/A

Ramp Rate (UT only) Assumes an initial five

- year period to ramp up and maintain consistency with program filings. N/A

*At Pacif iCorp’s direction, 2013

– 2017 market potentials for Utah were fixed to match program filing s

.



### The study used ramp rates to adjust annual market potential numbers and to account for factors such as market momentum, supply chain initialization, and consumer education. R amp rates,
shown in Figure 19 , did not impact 20

- year total technical or market potentials , merely impacting the assumed rate of acquisition

.

Figure 19

. Solar PV Ramp Rates

Results

As shown in Table 82 , th is study’s methodology resulted in increased estimated market penetration for states with existing incentive programs ( Oregon

, California , and Utah ), compared

to the 2011 assessment

. The table’s values represent the average percentage of the 20

- year technical potential, acquired annually.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 105 

### Table 82

. Solar PV Annual Market Penetration Rates Used in the 2011 and 2013 IRPs

Existing Program? State 2011 Assessment Annual Market Penetration Rate

Residential Nonresidential

No WA 0.02%

0.02% 0.01%

ID 0.01%

WY 0.01%

Yes OR 0.02%

0.14% 0.08%

CA 0.02%

UT 0.02%



### Table 83 summarizes technical and market potential results for the residential and nonresidential

sectors in each state. A total of 428 MW of installed capacity may be achieved system

- wide by

2032. Table 84 provides the energy corresponding with these capacity potentials.

Table 83

. Solar PV Technical and Market Potential ( Cumulative MW in 2032)

State Sector 20

- year Technical Potential (MW) 20

- year Market Potential (MW)

CA Res 170 4.7

NonRes 342 5.2

ID Res 450 1.6

NonRes 682 1.4

OR Res 2,402 66

NonRes 4,999 76

UT Res 5,473 151

NonRes 7,306 111

WA Res 572 2.0

NonRes 1,135 2.3

WY Res 658 2.4

NonRes 1,744 3.5

Total Res 9,725 228

NonRes 16,208 199



### Table 84

. Solar PV Technical and Market Penetration ( Cumulative aMW in 2032 )*

State Sector Technical Potential (aMW) Market Potential (aMW)

CA Res 23 0.7

NonRes 46 0.7

ID Res 65 0.3

NonRes 97 0.2

OR Res 322 9.5

NonRes 669 11

UT Res 816 24

NonRes 1,079 17

WA Res 76 0.3

NonRes 149 0.3

WY Res 106 0.4

NonRes 275 0.6

Total Res 1,408 35

NonRes 2,316 30

* Note : values in this table include performance degradation losses for systems installed prior to 2032.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 106 

### Peak Impacts

T o estimate the peak impact of achievable solar PV potential, the Cadmus team combined the modeled hourly output profile of typical solar PV systems in each state and sector, as described previously, with the PacifiCorp peak 40 hours of annual demand. By matching these two curves,

the Cadmus team calculated an average capacity fact or applying to peak demand periods for solar PV in the residential and commercial sectors for each state. In general, every MWdc of

installed PV result s in approximately 400 kW of peak reduction, varying slightly by state and

segment. T otal peak reduction for PV is estimated at 177 MW.



## Levelized Cost of Energy

Methodology

The LCOE , based on a single representative PV system for each sector

, compares life

- cycle costs to energy savings

. The LCOE was calculated using the TRC perspective for all states except

Utah ( where , as noted, the UCT is the accepted perspective ) . The Cadmus team calculated

levelized cost s separately for residential customers ( separated into single

- family and multifamily buildings ) and commercial customers (a category includ ing health, lod ging, large office, large retail, and school buildings )

.

T he study adjust ed installation and O&M costs in future years based on inflation and discount

rates . The Cadmus team also collected data on cost trends, module efficiency improvements, and module pe rformance degradation to estimate energy output s of systems installed in future yea rs and of systems as they age. The PVWatts model , developed by NREL, produced estimate s of capacity factor s for a typical system within each state

, during the first year of operation.

Data Sources and Assumptions

The Cadmus team reviewed multiple data sources for the analysis , as shown in Table 85 ( by input s used in analysis )

. The table includes W ebsite links to sources ( if available )

. If report s or data cannot be found online, interested parties may contact the Cadmus team or PacifiCorp to

request the information.

Table 85 . Data Sources Used for the Sol ar PV LCOE Analysis

Input Source Website Link (Where Available)

Installed Cost California Solar Initiative (CSI) Program Data

,

downloaded July 2012

. http://www.californiasolarstatistics.ca.gov/current_d ata_files/

Installed Cost Utah Solar PV Incentive Pilot Program Data from

2011

. Provided by PacifiCorp

.

Installed Cost Utah State Energy Program 2011 data

. Provided by Utah State Energy Program

. Installed Cost Energy Trust data

. Provided by the Energy Trust

. Inverter Costs Solar Buzz Website. http://www.solarbuzz.com/Inverterprices.htm
Annual Change

in Installed Cost Lawrence Berkeley National Laboratory. Tracking

the Sun IV: The Installed Cost of Photovoltaics in
the U.S. from 1998

- 2010. September 2011. http://eetd.lbl.gov/ea/emp/re

- pubs.html

O&M Cost Arizona Renewable Energy Assessment by Black

and Veatch; Comparative Costs of California Central Station Electricity Generation Technologies by the

CEC with Aspen Environmental Group; and Renewable Energy Transmission Initiative for RETI Provided by NREL in its 2007 comments

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 107 Input Source Website Link (Where Available)

Coordinating Commi ttee

. Tilt Utah Solar PV Incentive Pilot Program Data for

2011

. Provided by PacifiCorp

.

Azimuth Utah Solar PV Incentive Pilot Program Data for

2011

. Provided by PacifiCorp

.

Capacity Factor PVWatts Solar Calculator

. http://rredc.nrel.gov/solar/calculators/PVWATTS/ve

rsion1/
Annual Change

in Module Efficiency ―Solar Energy Technologies Program, Multi

- Year

Technical Plan 2003

- 2007 and beyond‖ U

. S

. DOE

E nergy E fficiency and R enewable E nergy

. Can be provided by the Cadmus team upon request.

Average Size Utah Solar PV Incentive Pilot Program Data for

2011

. Provided by PacifiCorp

.

Average Size Utah State Energy Program

. Provided by the Utah State Energy Program

. Average Size Energy Trust data for 2011

. Provided by Energy Trust

. Performance Degradation PVWatts default model assumption

. http://rredc.nrel.gov/solar/cal culators/PVWATTS/ve rsion1/derate.cgi

Measure Life Assumptions used by NREL's System Advisor

Model (SAM)

. http://www.sam.nrel.gov

Federal Rebate Database of State Incentives for Renewables and

Efficiency

. http://www.dsireusa.org/incentives/incentive.cfm?In centive_Code=US37F&re=1&ee=1

State Rebates Database of State Incentives for Renewables and

Efficiency

. http://www.dsireusa.org/



### This analysis did not include interconnection costs. The cost to cover basic application review s and meter replacement s by the u tility is estimated at less than 1% of total system costs, therefore

ha ving a minimal impact on cost

- effectiveness.

Overview of Installed System Cost Data

The Cadmus team gathered and reviewed i nstalled system cost data from four main sources:

1. T he Utah Solar PV Incentive Pilot Program

2. T he Utah State Energy Program

3. T he California Solar Initiative ( CSI )

4. Energy Trust of Oregon ProgramPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 108 

### Table 86 compar es installed cost s reported for these programs

.

Table 86

. Comparison of Installed Costs for Solar PV Systems in the U.S.
Size (kW) (CEC PTC AC)* 2011 Utah Pilot

Systems (2012 $/W) 2011 Utah State Energy

Program Systems (2012 $/W)** 2011 CSI

Systems (2012 $/W) 2012 CSI

Systems (2012 $/W) Energy Trust

(2012 $/W)***

< 5 kW $6.57 $7.56 $7.94 $7.46 $7.70

5 to 10 kW Sample size is too small $6.84 $6.40 $5.91 n/a

10 to 30 kW Sample size is too small $8.14 $6.13 $5.20 $7.21

*The CEC P hotovoltaics for Utility Scale Applications (P VUSA ) Test Conditions (PTC) module size was used

, with t he inverter efficiency taken into account to convert direct current ( DC ) to alternating current (AC). PVUSA Test Conditions include: 1,000 watts of solar irradiance per square meter; 20 degrees Celsius air temperature ; and wind speed of 1 meter per second at 10 meters above ground level. S tandard test conditions (S TC ) include: 1,000 watts of solar irradiance per square meter ; 25 degrees Celsius cell temperature ; air mass equal ing 1.5 ; and ASTM G173

- 03 standard spectrum. The PTC rating, lower than the STC rating, offers a more realistic measure of module output

, as test conditions better reflect "real

- world" solar and climatic conditions, compared to the STC rating. **Values converted from cost per DC watt at STC to cost per AC watt at PTC

, by assuming : 1.2 W STC

- DC per 1.0 W CEC

PTC

- AC.

*** The Energy Trust provided ave rage system cost data for residential and nonresidential systems , with t he < 5 kW system cost correspond ing to residential systems (with an average size of 2.7 kW)

, and the 10 to 30 kW system cost correspond ing to nonresidential systems (with an average si ze of 13.9 kW).



### For Utah and CSI system costs, the Cadmus team used the year customer s first applied for the

program, assum ing this the best proxy for the year the cust omer received a price quote. Analysis

also eliminated CSI systems with third

- party system owner s, as it could not be determined whether these systems fell under a Power Purchase Agreement

, which generally result ed in higher reported cost s

. The study removed sales tax from California costs to isolate PV equipment

and installation costs. D ata received from other sources already included this adjustment ; therefore, no further sales tax

- related adjustments were necessary

.

Residential and Commercial Inputs to Levelized Cost Analysis Solar PV system costs remain at historic lows and will likely continue to decrease. Due to large influxes of inexpensive PV modules over the past several years (primarily from China), costs have decreased more rapidly than suggested by longer

- term trends. Pending tariff regulations from the Department of Commerce on Chinese

- manufactured solar PV modules likely will play a role in leveling out recent declines in solar PV prices.

Whether present cost reduction rates will persist beyond the short term is unknown , and significant uncertainty exists regarding short

- term price predictions. Consequently, the Cadmus

team used long

- term historical cost data, presented in the Lawrence Berkeley National Laboratory ( LBNL ) study referenced in Table 87

, which represent s a conservative predictor of

future cost trends.

The following tables summarize inputs used for the analysis

. Table 87 lists a ssumptions for

residential single

- family systems.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 109



### Table 87

. Solar PV Residential Single

- Family Assumptions

Input Value Reasoning
Average S ize 3 kW Average residential system size in the 2011 Utah Solar PV Incentive Pilot Program was 3.2 kW , as was t he average residential system size in the Utah State Energy Program in 2011. T he average size in the E nergy Trust program in

2012 is 2.7 kW.

Measure Life (years) 30 The t ypical module manufacturer warranty period is 25 years. The NREL SAM

assumes a 30

- year life.

2013 Installation
Cost ($/W) $7.45 Average cost from programs reviewed

.

Annual Change i n Nominal
Installation Cost - 4.6% From the LBNL study

, as the trend from 1998 to 2010; s upported by lower costs in Germany and Japan

, which should be achievable in the U.S. as the market grows. Though costs have seen a larger annual decline in recent years (per LBNL, as much as 22% from 2010 to 2011), it is not expected this will continue over 20 years.

O&M Cost ( nominal cost for

inver ter replacement in year 15 ) $2,133 Based on Solarbuzz inverter costs reported for March 2012 of $0.711/W. Assumes one inverter replacement over the 30

- year life , which also falls within the range ($25

– $100 per year)

, presented by NREL comments on the 2007 report

.

Tilt (degrees) 32 Average residential system tilt in the Utah Solar PV Incentive Pilot Program from

2010

– 2011

. Azimuth South Average residential system azimuth in the Utah Solar PV Incentive Pilot Program

from 2010

– 2011

. Inverter Efficiency 95% Typical inverter efficiency

. Annual Change in Module Efficiency 2.1% US DOE EERE report on Solar Energy Technologies Program Multi

- Year

Technical Plan ; average a cross all three classes of technology (mono

- crystalline, poly

- crystalline, and amorphous thin

- film).

Annual
Performance Degradation 1% PV Watts default derate value

.

Capacity Factor Depends on location From PV Watts

. *Some assumptions also apply to calculations made for the technical and/or market potential.



### Table 88 lists assumptions for multifamily, commercial , and industrial systems.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 110 

### Table 88

. Solar PV Multifamily, Commercial, and Industrial Assumptions

Input Value Reasoning
Average S ize 20 kW The average commercial system size in the 2011 Utah Solar PV Incentive Pilot Program was 19.1 kW. The average size in the 2011 Utah State Energy Program was 11.5 kW. It is assumed a full

- scale incentive program would see more participant s and larger systems.

Measure Life (years) 30 Typical module manufacturer warranty period is 25 years. The NREL SAM

assumes a 30

- year life.

2013 Installation
Cost ($/W) $6.67 Average cost from the programs reviewed

.

Annual Change i n Nominal Installation
Cost - 4.6% Found in the LBNL study as the trend from 1998 to 2010; s upported by lower costs in Germany and Japan

, which should be achievable in the U.S. as the market grows. Though costs have seen a larger annual decline in recent years (per LBNL, as much as 22% from 2010 to 2011), it is not expected this will continue over 20 years.

O&M Cost ( nominal
cost for inverter replacement in year

15 ) $14,220 Based on Solarbuzz inverter costs reported for March 2012 of $0.711/W ;

a ssumes one inverter replacement o ver the 30

- year life.

Tilt (degrees) 25 Average commercial system tilt in the Utah Solar PV Incentive Pilot Program from 2010

– 2011

. Azimuth South Average commercial system azimuth in the Utah Solar PV Incentive Pilot Program from 2010

– 2011

. Inverter Efficiency 95% Typical inverter efficiency

. Annual Change in Module Efficiency 2.1% U

. S

. DOE EERE report on Solar Energy Technologies Program Multi

- Year

Technical Plan ; average across all three classes of technology (mono

crystalline, poly

- crystalline, an d amorphous thin

- film).

Annual Performance Degradation 1% PV Watts default derate value

.

Capacity Factor Depends on location From PV Watts

. *Some assumptions also apply to calculations made for the technical and/or market potential.



### Results

As shown in Table 89 , LCOE likely will decrease over the next 20 years, with the notable exception of the federal ITC expiration at the end of 2016, causing LCOE to i ncrease before resuming a downward trend through 2032. As discussed, t he markedly lower LCOE for Utah results from use of the UCT, whereas the remainder of the states’ LCOE use the TRC perspective

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 111 

### Table 89

. Solar PV Levelized Cost of Energy Summary Results and Capacity Factors

State Sector Levelized Cost* Capacity

Factor 2013 ($/kWh) 2017**

($/kWh) 2032**

($/kWh)

CA Res $0.30 $0.35 $0.18 0.16

NonRes $0.27 $0.32 $0.16 0.1 6

ID Res $0.28 $0.33 $0.17 0.1 7

NonRes $0.26 $0.30 $0.16 0.1 7

OR Res $0.30 $0.35 $0.18 0.1 6

NonRes $0.27 $0.32 $0.17 0.1 6

UT Res $0.07 $0.06 $0.03 0.17

NonRes $0.06 $0.05 $0.03 0.17

WA Res $0.30 $0.36 $0.18 0.1 6

NonRes $0.28 $0.33 $0.17 0.1 6

WY Res $0.25 $0.30 $0.15 0.1 9

NonRes $0.23 $0.27 $0.14 0.1 9



### * Utah LCOE was calculated using the UCT, while other states use the TRC test

. **The Federal ITC will expire at the end of 2016. LCOE estimates for 2017 and 2032 assume the ITC will not be extended

or renewed.



## Solar Water Heating

SWH systems use sunlight to pre

- heat domestic hot water tanks, reducing the need for electric ity

to heat water

. W idely applicable in the residential and nonresidential sectors

, SWHs have been in

use for several decades.



## Technical and Market Potential

Methodology

The Cadmus team calculated technical potential for SWH using the following steps:

1. The study calculated t he total number of electric hot water heaters in each state and sector, based on survey data

.

2. The estimated number of electric water heaters was reduced by the number of heat pump

water heaters included in the 20

- year Class 2 DSM achievable technical potential

.

3. The number of eligible water heater s wa s then multiplied by the water heater UEC in each segment, calculated as part of the Class 2 DSM analysis.

4. A series of RETScreen models determine d representative solar fraction values for each state and sector, representing the percentage of water heating consumption the unit could offset. These values were applied to the results of step three to arrive at the 20

- year technical potential.

The Cadmus team assumed a 15% maximum market penetration for all segments , basing t his market potential percentage on actual Energy Trust rebate data (for program years 2009 throughPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 112 

### 2011) and on technical potential calculated by E nergy Trust . The Cadmus team used the same lost opportunity ramp rate as the Council to allocate the 20

- year potential annually

. 65



### Results

Table 90 shows the results of the Cadmus team’s analysis and summarizes 20

- year cumulative technical and market potential by state and sector , as measured at the generator

. 66



### Table 90

. SWH Technical and Market Potential by State and Sector

( Cumulative aMW in 2032)

Sector CA ID UT WA WY Total *

Technical Potential

Nonresidential 0.12 0.12 0.96 0.27 0.20 1.67

Residential 1.85 3.20 10.5 2.47 2.43 20.5

Total * 1.97 3.32 11.4 2.74 2.63 22.1

Market Potential

Nonresidential 0.02 0.02 0.14 0.04 0.03 0.25

Residential 0.28 0.48 1.57 0.3 7 0.36 3.06

Total * 0.30 0.50 1.71 0.41 0.39 3.31 *Totals may vary slightly due to rounding

.



### Though the SHW industry generally does not discuss systems in terms of rated capacity (e.g., kilowatts), it can be useful to understand the general instantaneous output of a SHW system for assessing utility grid impacts and for comparison with other efficiency or renewable energy

measures. In 2004, the International Energy Agency established a 0.7 kW thermal 

### /m 2 

### (0.065

kWthermal /ft 2 

### ) value as a benchmark for converting a gross collector area into an equivalent rated power value. 67



### Peak Impacts Peak impacts derive from the water heating load s hape and its coincidence factor during peak periods. In other words, the peak impact is calculated based on MW = aMW * CF, where CF represents the coincidence factor. T he Pacific Power territory has a coincidence factor of 0.973

, and Rocky Mountain Power t erritory has a factor of 0. 971

. T otal peak reduction is estimated at

3.2 MW.

65 http://www .nwcouncil.org/energy/powerplan/6/default.htm The Council's potential did not include

manufactured homes.

66 The Energy Trust estimates potential for SWH in PacifiCorp’s Oregon service territory. Results can be found in Energy Trust’s 2012 Resource Assessm ent Update: http://energytrust.org/library/reports/121114_2012_ResourceAssessment.pdf

67 Winn, Menicucci, and Vuppuluri. Effective Power Ratings for Solar Hot Water Systems

. A vailable at: http://www.academia.edu/247830/EFFECTIVE_POWER_RATINGS_FOR_SOLAR_HOT_WATER_SYSTE

MSPacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 113 

## Levelized Cost of Energy

Methodology

The LCOE , based on a single representative SWH system for each state and sector, compares life

- cycle costs to energy savings

, calculated based on the TRC perspective for all states ( except
Utah , which use s the UCT)

. Applicable commercial segments were chosen based on average annual hot water heating electricity consumption of at least 9,000 kWh, as these facilities were more likely to have sufficient hot water heating loads to justify investments in SWH systems.

Sources 

### In early 2009, Itron released an Interim Evaluation report for the California Center for Sustainable Energy (CCSE) Solar Water Heating Pilot Program (SWH PP) . This report compiled SWH information from numerous sources, including cost data from incentive programs in the

United States and information from contractor interviews. 68



### F or the SWH analysis

, the Cadmus team reviewed the Itron report and other data s ources, such

as the ENERGY STAR W ebsite and NREL . The Cadmus team also downloaded t he most recent

California Solar Thermal program data from the California Public Utilities Commission to update installed system costs for residential and nonresidential syst ems . The Cadmus team

obtained information about average system costs for residential systems from the E nergy Trust

.

Resources for Calculations



### The s olar fraction

— the percentage of energy used for heating water provided by the SWH

— provided the data require d to calculate energy savings. Solar fractions for each se gment and location combination were developed using RETScreen International 69 

### and assumptions of gallons of hot water used per day and sector

- specific load shapes. N umber s of collectors were adjusted until the solar fraction near ed 70%, as systems typically are designed to reach a solar

fraction of 40 % to 80%. 70



### The utility incentive level was defined as 10% of the incremental cost, based on Energy Trust rebate information for program years 2009 to 2011 . The Cadmus team’s analysis applied this 10% rebate after the 30% federal rebate during program years 2013 to 2016 . The Cadmus team’s review of other states’ SWH programs indicated incentives rang ing from 10% to 20%; therefore, Energy Trust ’s incentive offers a reasonable―if slightly conservative― assumption for all states.

Overview of Installed System Cost Data



### Table 91 compares installed costs for residential retrofit SWH systems in the United States

. SWH systems, unlike some other water heater efficiency improvements, typically do not replace

68 The CCSE SWHPP Interim Report can be downloaded from: http://energycenter.o rg/uploads/CCSE_SWHPP_Interim_Report_Final.pdf

69 Natural Resources Canada developed RETScreen International, which can be downloaded free of charge from: http://www.retscreen.net/

70 NREL. The Technical Potential of Solar Water Heating to Reduce Fossil Fu el Use and Greenhouse Gas Emissions in the United States. March 2007, page 5. Accessed August 2, 2010, from http://www.nrel.gov/docs/fy07osti/41157.pdf

.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 114 

### a customer’s existing hot water heater. Rather, most SWH systems supplement existing hot water

heater s by pre

- heating the cold water supply (e.g., well or municipal) before it enters an existing

hot water heater.

Table 91 . Comparison of Installed Costs for U.S. Residential Single

- Family SWH Systems

Program Average Residential

System Cost (2012 $) Typical System Type
California Solar Thermal Program 2012 $8,401* Active glycol and drainback systems
Eugene Water and Electric Board 2008 $7,607 Active glycol and drainback systems
Energy Trust 2011

- 2012 $8,688 Active glycol and drainback systems
*Adjusted to remove sales tax.



### The Cadmus team derived i nstallation costs for nonresidential SWH projects from data reported by the California Solar Hot Water Program in 2012. The study assumed SWH system costs

remain constant over time, with economies of scale due to i ncreased market adoption balancing increasing material costs for SWH system components.

Residential, Multifamily, and Commercial Inputs



### Table 92 lis ts inputs and assumptions used in the Cadmus team’s analysis of residential systems.

Table 92

. Solar Water Heating Residential Assumptions

Input Value Reasoning Average Size (collector square feet) 48 Assumes two collectors, with the typical collector area of 40 to 60 square feet per home.

Measure Life (years) 20 Minimum collector lifetime from warranty claims in Hawaii. See SWHPP Interim Report Table 5

- 3; ENERGY STAR also lists a 20 year

lifetime: http://www.energystar.gov/index.cfm?c=solar_wheat.pr_savings_benefits

Installed Cost for Ret rofit Systems $8,500 Average cost (rounded), reported by the CA Solar Thermal Program and the Energy Trust

. Assumed Rebate (% of incremental cost) 10% The Energy Trust has offered a 10% rebate on average for the last several

years. Annual Change in Nomin al
Installed Cost 0% Costs have increased steadily over the past six years, due to increases in material costs. The study assumes costs will stabilize over the next 20 years.

O&M Cost $120 every three

years; $40 per year (nominal) Assumes customers have systems inspected every three to four years, and

occasionally have heat transfer fluid flushed and replaced. (SWHPP Interim Evaluation Report Table 7

- 6) . The Cadmus team assumes a three

- year replacement cycle, at the conservative end of the given range.

Tilt (degrees) 32 Average residential system tilt in the Utah Solar PV Incentive Pilot Program
from 2010

– 2011.

Azimuth South Average residential system azimuth in the Utah Solar PV Incentive Pilot Program. Annual Change in Efficiency 0% As solar thermal is a mature technology, improvements in efficiency are not expected.

Annual Performance Degradation 1% Assumption used in the NREL SAM, which can be downloaded for free of charge from: https://www.nrel.gov/analysis/sam/

Solar Fraction Varies by location Modeled using RETScreen International.

Federal Tax Incentive (% of installed cost, no cap) 30% The current federal tax incentive for renewable energy measures, set to expire on December 31, 2016.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 115 

### Table 93 list s inputs and assumptions for the Cadmus team’s analysis of commercial systems.

Table 93

. Solar Water Heating Multifamily and Commercial Assumptions

Input Value Reasoning
Average S ize Varies by sector

and location Size calculated based on gallons of hot water used per day in each segment

within each state.

Measure Life (years) 20 Minimum collector lifetime from warranty claims in Hawaii

. See SWHPP Interim Report Table 5

- 3; ENERGY STAR also lists a 20

- year lifetime: www.energystar.gov/index.cfm?c=solar_wheat.pr_savings_benefits

Installed Cost for Retrofit Systems ($/collector square foot) $106 Average cost per square foot for commercial and multifamily systems in the

California Solar T hermal program in 2012

.

Assumed Rebate (% of incremental cost) 10% The Energy Trust has offered a 10% rebate on average for the last several

years. Annual Change i n Nominal Installed Cost 0% The Cadmus team assume s costs will remain stable over the next 20 years

.

Annual O&M Cost 10% of installation cost divided by 20

years Assumes customers have system s inspected and glycol flushed and replaced

periodically. (SWHPP Interim Evaluation Report Table 7

- 11)

Tilt (degre es) 25 Average commercial system tilt in the Utah Solar PV Incentive Pilot Program

, from 2010

– 2011

. Azimuth South Average commercial system azimuth in the Utah Solar PV Incentive Pilot Program from 2010

– 2011

. Annual Change in Efficiency 0% As s olar thermal is a mature technology

, improvements in efficiency are not expected

. Annual Performance Degradation 1% Assumption used in the NREL SAM, which can be downloaded free of charge

from : https://www.nrel.gov/analysis/sam/

Solar Fraction Varies by locat ion

and sector Modeled using RETScreen International

.

Federal Tax Incentive (% of installed cost ; n o

cap ) 30% T he current federal tax incentive for renewable energy measures, set to expire on December 31, 2016.



### Results

Table 94 shows levelized costs for SWH systems before and after expiration of the ITC, as

calculated from the TRC perspective for all states except Ut ah (as based on the UCT). Incentive levels before and after the ITC expiration are held constant, assuming no additional utility funds

will be provided to offset additional costs from 2017 onwards.PacifiCorp Assessment of Long

- Term, System

- Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 116 

### Table 94

. SWH Levelized Cost of En ergy Before and After the ITC Expiration

Sector Levelized Cost of Energy ($/kWh)

CA ID UT* WA WY

2013

- 2016

Nonresidential $0.18 $0.16 $0.02 $0.18 $0.1 5

Residential $0.45 $0.29 $0.0 4 $0.4 5 $0.36

2017

- 2032

Nonresidential $0.25 $0.22 $0.02 $0.2 6 $0.2 1

Residential $0.63 $0.40 $0.0 4 $0.6 2 $0. 50 * LCOE values for Utah calculated using the UCT; all other states use the TRC perspective

.



## Summary of Results

Technical Potential

Table 95 provides t he technical potential for supplemental resources, by resource category territory.

Table 95

. Supplemental Resources Technical Potential by Territory

and Resource Category ( Cumulative a MW in 2032 )

Resource Rocky Mountain Power Pacific Power PacifiCorp System

CHP 3,227 1,074 4,301

On

- Site Solar: PV s 2,438 1,285 3,724

On

- Site Solar: Water Heating* 17.4 4.7 22.1

1. Total 5,682 2,364 8,047 *Excludes Oregon

Note: Results may not sum to total s due to rounding

.



## Market Potential

Table 96 shows a market potential ( or the amount of resources expected to be achievable over the 20

- year planning horizon ) of 202 aMW, broken down by resource category and territory.

Table 96

. Market Potential for Supplemental Resources by Territory and Resource Category ( Cumulative aMW in 2032 )

Resource Rocky Mountain Power Pacific Power PacifiCorp System

CHP 123 45 168

On

- Site Solar: PV s 43 23 65

On

- Site Solar: Water Heating* 2.6 0.7 3.3

Total 1 68 6 8 2 36

* Excludes Oregon

Note: Results may not sum to total s due to rounding

.