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.
Principal 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 Cadmus Group, Inc. / Energy Services Division 

TABLE OF CONTENTS: VOLUME 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

General 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........................................................................33
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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 ......................................................................................................100
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 

Market Potential ..........................................................................................................102

Levelized Cost of Energy.............................................................................................106

Solar Water Heating..........................................................................................................111

Technical and Market Potential ...................................................................................111

Levelized Cost of Energy.............................................................................................113

Summary of Results..........................................................................................................116

Technical Potential ......................................................................................................116

Market Potential ..........................................................................................................116
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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 Cost by 

State ($/kW-yr) ..............................................................................................................39

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. Nonresidential 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. Irrigation 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. Nonresidential 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 .....................................................49
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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 Types ............................................................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. Technical and Achievable Technical Class 2 DSM Potential (Cumulative 

Coincident Peak MW in 2032) by State .........................................................................75

Table 54. Technical and Achievable 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 Class 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 Market Potential by Fuel (Cumulative in 2032)................................................100
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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 Market 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) ..........................................................................................116
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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 Opportunity 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 Treatment ............................................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 Potential by State and Sector in 2032 ....................102

Figure 19. Solar PV Ramp Rates ............................................................................................104
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 

TABLE OF CONTENTS: VOLUME 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 Segmentation

Appendix C-2. Measure Inputs

Appendix C-3. Baseline Sales

Appendix C-4. Achievable Technical Potentials

Appendix C-5. Comparison of Measure Input Assumptions to 

Energy Trust of Oregon Resource Assessment

Appendix C-6. Washington Measures Compared to the Council’s 6th Plan and the 

Regional Technical Forum

Appendix D. Technical Supplements: Supplemental Resources 

Appendix D-1. Combined Heat and Power

Appendix D-2. On-Site Solar
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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 Peak Pricing

CSI California Solar Initiative

DBB Demand Buyback 

DEER Database of Energy Efficient 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 Intensities

EUL Effective Useful Life

FC Fuel Cell 

GT Gas Turbine 

HVAC Heating Ventilation and Air Conditioning

IRP Integrated Resource Plan

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 Useful Life

SEEM Simple Energy and Enthalpy Model

SGIP Self-Generation Incentive Program

SWH Solar Water Heating
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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 Water Heating

WHP Waste Heat-to-Power

WWTF Wastewater Treatment Facility
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus 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, we also thank: Jeff Bumgarner, Director of Demand Side 

Management Planning and Development; Don Jones, 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 balance considerations 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, 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 competed directly against 

supply-side options, allowing the IRP model to guide decisions regarding resource mixes, 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 estimates of the magnitude, timing, and costs of 

DSM resources likely available to PacifiCorp over a 20-year planning horizon, beginning in 

2013. The study focuses on resources realistically achievable during the planning horizon, given 

normal market dynamics that 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 2007 and 2011.

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), Class 

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, savings 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 estimates potential from 

supplemental resources, which fall outside PacifiCorp’s classification of DSM and include 

renewable and nonrenewable customer-sited generation. For this study, supplemental resources 

include: combined heat and power (CHP), solar photovoltaics (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.html
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 2

work conducted by the Energy Trust of Oregon (Energy Trust), which provides energyefficiency 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 (energyefficiency); 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)2over 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 potential of supplemental resources (including on-site solar 

and CHP) account for the remaining 27% (236 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 2032):

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 4,094 168

Rocky Mountain Power Subtotal 4,801 728

Pacific Power 

Class 2 DSM Resource* 112 88

Supplemental Resource* 1,885 68

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 number 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, Inc. / Energy Services Division 3

Table ES-2 shows estimates of coincident peak demand impacts from the identified resources.

4

These impacts have not been adjusted to account for resource competition and/or interactions

and, therefore, cannot be considered additive in nature. 

For example, if all Class 2 DSM (energy-efficiency) resources were acquired, they would reduce 

the load basis from which Class 1 and 3 DSM (capacity-focused resources) 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 accounting 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 quantity 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 2032):

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 1 DSM Resource N/A 488

Class 2 DSM Resource 1,339 1,078

Class 3 DSM Resource N/A 45

Supplemental Resource 10,023 367

Rocky Mountain Power Subtotal N/A 1,978

Pacific Power 

Class 1 DSM Resource N/A 116

Class 2 DSM Resource*** 200 163

Class 3 DSM Resource N/A 20

Supplemental Resource 5,012 149

Pacific Power Subtotal N/A 448

PacifiCorp System Total N/A 2,426

* Class 2 DSM resource potential is stated as 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 determined 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, Inc. / Energy Services Division 4

Capacity-Focused (Class 1 and Class 3) DSM Resources

Market potential results from the Class 1 and 3 DSM resources, provided in Table ES-2 and 

Table ES-3 (below), break down by resource class, sector, and territory. They represent an 

assessment of load management opportunities/products within PacifiCorp’s service territories 

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 current program offerings, while Class 3 

DSM results are incremental to current time-varying rate program offerings.

Table ES-3. Class 1 and Class 3 (Capacity-focused) DSM Resource Market Potential by 

Customer Sector and Service Territory (MW in 2032)

Rocky Mountain Power Pacific Power PacifiCorp System

Class 1 DSM—"Firm"

Residential 151 41 192

Small Commercial 1 1 2

Large Commercial 55 42 97

Industrial 70 22 92

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 12 2 14

Irrigation 11 7 18

Subtotal 45 20 66

Total 533 137 670

The irrigation sector accounts for 37% of total Class 1 market potential, and the residential sector 

contributes another 32%. Currently, PacifiCorp operates residential direct load control (DLC) air 

conditioning and irrigation DLC programs in Rocky Mountain Power’s service territory. 

Based on research by the Cadmus team into similar programs’ participation, these existing 

programs 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. Though 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 savings achieved by PacifiCorp’s current 

time-varying rate programs. Chapter 2 discusses current 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 (energyefficiency) resources has been estimated at 648 aMW, representing 79% of identified technical 

potential for this resource in five of PacifiCorp’s six state service areas (excludes Oregon).
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / 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 2032

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 an additional 

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

Resource opportunities, however, may differ in terms of value (when screened for economic 

potential in the company’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 remaining potential is 

associated with lost opportunity resources, namely new construction and replacement of existing 

equipment at the end of its normal life cycle. 

Supplemental Resources

Table ES-5 provides supplemental resource potential, with an estimated 236 aMW of market 

potential across PacifiCorp’s system. Resources considered include CHP, solar 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 2032)

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 168 68 236

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

* Potential does not include Oregon in Pacific Power territory (those data are provided to the company by the Energy Trust).

Comparison to 2011 Assessment

As noted, this assessment builds upon studies completed in 2007 and 2011. This section reviews

key differences between the current study findings and those presented in the 2011 Assessment.
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / 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 

Assessment 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)5since 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 

data, 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 during 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). The current study indicated 

the market potential for Class 1 DSM to be 604 MW, comparable to the 623 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 buyback (DBB). The large difference in irrigation TOU market potential was a result of 

assuming voluntary, rather than mandatory, participation, while lower 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 from Class 3 DSM resource offerings 

(existing and new) the 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 secondary literature on customer responses 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 

reduce PacifiCorp’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: 

Accounting for newly enacted codes and standards, even if not yet in effect;

Adjusting for PacifiCorp’s actual and projected DSM program accomplishments from 

2010 through 2012;

Incorporating adjustments 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-Term, System-Wide Potential March 2013

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Applying 2011 customer information to determine segmentation; and 

Utilizing 2012 load and customer forecasts. 

Together, these changes decreased total, system-wide, 20-year, Class 2 DSM achievable 

technical potential from 1,156 aMW to 648 aMW, or 44%. Chapter 3 provides further details on 

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

Supplemental Resources

For supplemental resources, system-wide 20-year market potential increased by 58 aMW, from 

178 aMW to 236 aMW, or a 33% decrease. Solar 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. The 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 

currently 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 solar water heaters decreased by 19 aMW relative to 

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

than maximum achievability estimates from the Northwest Power and Conservation Council’s 

(the Council’s) 6th 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

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INTRODUCTION

Background

Since 1989, PacifiCorp has developed biennial Integrated Resource Plans (IRPs) to identify an 

optimal mix of resources, balancing considerations 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, 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, demand-side management (DSM) resources 

have competed 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 develop reliable estimates of the magnitude, timing, and costs of 

DSM resources likely available to PacifiCorp over a 20-year planning horizon, beginning in 

2013. The study focuses 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 classifies DSM resources into four categories, 

differentiated by two primary characteristics: reliability and customer choice (see Figure 1). 

These resources are captured through programmatic efforts promoting efficient electricity use 

through various intervention strategies, aimed at changing: energy use peak levels (load 

curtailment), timing (price response and load shifting), energy intensity (energy efficiency), or 

behaviors (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.
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Supplemental resources, consisting mainly of small-scale, dispersed generation6on 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 (capacityfocused), 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 assessments of 

Class 4 DSM resources.

This study, the third comprehensive assessment commissioned by PacifiCorp, builds 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 Resources7(the 

2011 Assessment). 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 

Washington) 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.html
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

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The Energy Trust of Oregon (Energy Trust), however, takes responsibility for identifying and 

delivering 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 demand-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-focused 

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 interruptions, 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) 

program 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 resource class seeks 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 tariffs) and more traditional pricing 

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

This resource class consists 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 (retrofits in 

existing construction) or lost opportunities (equipment replacement and efficiency improvements

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

intervention mechanisms, such as: equipment incentives; direct installation; process and activity 

optimization leading to sustained changes in energy use; or advancement of codes and standards. 

The type and intensity of market intervention strategies, prevailing retail rates, and availability of 

capital in a given market can affect the amount and cost of Class 2 DSM resources. Once 

installed, savings are assumed to persist (remain firm) over the 20-year study period (customers 

will reinvest in ―equal to‖ or greater efficiency at the end of the measure’s

useful life). 

 

8

http://energytrust.org/library/reports/121114_2012_ResourceAssessment.pdf
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

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Supplemental Resources

For this study, supplemental resources represent small-scale,

9

dispersed power generation 

technologies. This 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 Solar, which includes small-scale photovoltaics (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 within PacifiCorp’s territory.

Resource Interactions

In assessments involving diverse DSM resources (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., interactions between similarly 

focused resource classes, such as Class 1 and 3 DSM). These effects must be carefully 

considered to avoid double-counting available potential. This study explicitly estimates intraclass 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 been accounted for in the Class 2 DSM analysis. First, a ―stacking 

effect‖ occurs when complementary retrofit measures—such as wall, ceiling, and floor 

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

reductions in end-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 tends 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 stacking effect, if nonequipment measures can be captured first, replacement of existing equipment with highefficiency equipment can be expected to have smaller impacts 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-Term, System-Wide Potential March 2013

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The analysis also accounts for technical interactions among measures, such as lighting retrofits

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 interactions 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 for 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 load curtailment program and no 

remaining potential would be available for Demand Buyback (DBB) or CPP where load 

curtailment is 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.

Interactions Between Energy-Focused and Capacity-Focused 

Resources

Interactions also exist between Class 2 and Class 1 and 3 DSM resources as well as with 

supplemental resources. Primarily, because implementation of energy-efficiency or supplemental 

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

and 3 DSM resources. Though an important factor to recognize, this study did not attempt to 

quantify such interactions due to uncertainties regarding resources likely to be found economic 

and pursued.

Incorporating 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 incorporates estimates of enacted legislation’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, motors, and other end-use equipment. Capturing effects from this 

legislation has been particularly important, as residential lighting has played a large role in 
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / 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 codes. 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, 

varying by size) Commercial/Residential 2015

Water Heater ≤ 55 gallons (e.g. EF = 

0.948 for 40 gallon)

Commercial/Residential 2015

HVAC

Central Air Conditioner (SEER 14) Residential – California only 2015

Heat Pump - Air Source (14 SEER/ 8.2 

HSPF) Residential 2015

Room Air Conditioner (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 taking 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 impacts of upcoming equipment standards in estimating Class 2 DSM resource 

potential, the Cadmus team incorporated these standards into the baseline forecast. Table 2

shows estimated impacts of changes in equipment efficiency standards on forecasted baseline 
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 14

residential and commercial loads in 2032, respectively.11 Overall, new equipment standards lead 

to decreases 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

End-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 makes 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.
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Table 3. State Energy Codes

State

Energy Code Used

Residential Nonresidential

Washington14 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

California15 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 (Zone 16) was used as a proxy.

Cross-Resource Assumptions

Several 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 line 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 

sales and savings at the generator.

Report Organization

This report is divided into two volumes, with the present document (Volume I) organized into 

five sections. The three sections following the Executive Summary and Introduction sections 

address analyses of various resource options, primarily: 

Class 1 and Class 3 DSM (capacity-focused) resources; 

Class 2 DSM (energy-efficiency) resources; and

Supplemental resources.

The DSM resource sections begin by describing the scope of the analysis, followed by a

discussion of methodologies, 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.PDF
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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 additional technical

information, assumptions, data, and other relevant details for both DSM and supplemental 

resources.
PacifiCorp Assessment of Long-Term, System-Wide Potential 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 consists of products and programmatic options designed to:

Help reduce peak demand during system emergencies or periods of extreme market 

prices;

Promote improved system reliability; and

In some cases, balance variable-load resources, particularly wind energy. 

Benefits from Class 1 and 3 DSM resources accrue by providing incentives for customers to 

curtail loads during utility-specified events (e.g., DLC and DBB) or by offering pricing 

structures to induce participants to shift load away from peak periods (e.g., TOU and CPP

programs). This 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 basis, 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. This 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 Curtailment programs target larger commercial and industrial (C&I)

customers with shiftable loads and/or on-site standby generation assets that can be called 

upon by the utility, as needed. These customers, entering into curtailment agreements 

with the utility 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 

The Cadmus Group, Inc. / Energy Services Division 18

Class 3 DSM resources include time-varying prices and the DBB program. Participants receive 

incentives either through rates (time-varying prices) or per-event payments (DBB). This study 

analyzed three specific program options in this DSM resource class:

TOU and Time-of-Day (TOD) programs generally operate based on two- or three-tiered, 

time-differentiated tariff structures, 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 costs of generating and delivering power. The Cadmus 

team analyzed the potential for using TOU rates in the residential and irrigation sectors; 

in most cases, C&I time-variant rates have already been in place within the company’s 

service area; hence, the study did not further assess additional incremental opportunities.

CPP, or extreme 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-standard retail rates. This program targets large C&I customers as an

additional 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. Bid amounts 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. Reduction levels achieved can be verified using an 

agreed-upon baseline usage level, specific to the participating customer. This program 

targets large C&I customers.

The 2007 and 2011 Assessments analyzed two additional resources: real-time pricing (RTP) 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. 

Preliminary 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. The approach began with utility system loads, 

disaggregated into sector, segment, and applicable end uses. For each Class 1 and 3 DSM 

program (or program component) studied, potential impacts were first assessed at the end-use

level. End-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 

The Cadmus Group, Inc. / Energy Services Division 19

technical potentials to obtain estimates of market potentials. General analytic steps involved in 

estimating market potential (excepting the residential and small commercial DLC program) 

follow below. 

1. Define customer sectors, market segments, and applicable end uses. The first step in 

estimating the load basis was to define customer sectors, customer segments, and 

applicable end uses, similar to the energy-efficiency study (described in the next section). 

System loads 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 Analysis 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 on 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 segmentation, 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 

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 estimated 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) was calculated as 

the sum of impacts at the end-use level (e), generated in customer sector (s) by:

es

pes TPp TP

and

TPpes LEps LI pes

where,

LEps (load eligibility) represents the portion of customer sector (s) loads (MW)

applicable for program option (p), referenced as ―Eligible Load‖ in the program 

assumptions.

LIpes (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 accounts 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.

Market potential 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 percentage of customers who will 

participate in a demand response event—applicable to programs such as the irrigation 

DLC program, where customers can opt out of events). Market potential for the program 

option (MPp) was calculated as the product of technical potential for the customer sector 

(s), program participation (sign-up) rates (PPps), and expected event participation 

(EPps) rates: 

MPp TPps PPps EPps

For each capacity-focused program, projected sign-up rates for all customer segments 

were informed by secondary research, described in the program assumptions, as well as 

on PacifiCorp’s past program experience.18

 

18 Appendix A-1 provides a list of secondary sources used in this analysis.
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013 

The Cadmus Group, Inc. / Energy Services Division 21

Projected potential for Class 1 DSM products included PacifiCorp’s current program 

offerings, as the load forecast did not account for these programs’ impacts. Existing 

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 details the methodology for estimating 

impacts of existing Class 3 DSM offerings.

7. Estimate costs and develop supply curves. The levelized cost ($/kW-year) of each 

program option was calculated using estimates of program development, technology, 

incentive, ongoing maintenance, administration, and communications costs. 

Administrative costs for all programs were based on the assumption that a fully loaded 

FTE costs $150,000 per year ($72/hour). For nonresidential load curtailment and DBB 

programs, costs were calculated at the system (rather than state) level, assuming events 

would be called system-wide. Remaining programs, on the other hand, were assumed to 

be implemented at the state level.

DLC

Residential and small commercial DLC proves unique in that, unlike other demand response 

options, it affects specific end uses and equipment (e.g., air conditioners). Therefore, market 

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

1. Number of customers.

2. Expected per unit (kW) impacts.

3. Equipment saturation rate.

4. Expected participation.

Derivation of Per-Unit Impacts

Despite 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 ranging from 0.75 kW (Alliant Energy) to over 

1.5 kW (Commonwealth Edison).19

PacifiCorp already operates a large DLC program in its Utah service area. Measurement of 

program impacts has shown an average reduction of 1 kW per unit. Indexing per-unit impacts to 

Utah allowed estimation of per-unit impacts for other PacifiCorp service jurisdictions using the 

following procedure.

As PacifiCorp system peaks correlate highly to Utah weather, the 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 

The Cadmus Group, Inc. / Energy Services Division 22

(typical meteorological year) hourly data. Manual J, the protocol used to size air conditioning 

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 completed 

for the Class 2 DSM analysis. The study adjusted the 1 kW impact per switch used in Utah by 

the ratio of system peak to design temperature and air conditioner capacity; per switch kW 

impacts for the other five states were estimated. Appendix A-3 provides a summary of 

assumptions and savings per switch by state.

Equipment Saturation Rates

Equipment saturation represents the percentage of customers who were eligible for participation

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 Surveys

provided information on equipment saturation levels in each jurisdiction.

20

Expected Participation

The study based expected 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 details on DLC program participation rates.

Current Programs and Product Offerings

Class 1 DSM

PacifiCorp currently offers Class 1 DSM programs in both Utah and Idaho. The Cool Keeper 

Program, in Utah, serves as one of the country’s most successful residential and small 

commercial DLC Air Conditioning (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 methodology 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 block 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 National 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 offerings vary by state. In some cases, participation is mandatory. 
PacifiCorp Assessment of Long-Term, System-Wide Potential 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.

Residential 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 states. 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, starting 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. Other jurisdictions’ top block prices

range from 22% to 56% higher than the base price. Combining 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 subscriptions 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 combine voluntary and mandatory rates, depending on the jurisdiction and the 

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

rates vary by time of use, while others add a demand surcharge for on-peak use. Rates 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 offpeak usage, due to different prices at different periods (cross-price elasticity). Existing literature 

estimating 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 much 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’ opportunities 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 impacts 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 Renewable Energy Laboratory (NREL) study Regional Differences in 

the Price-Elasticity of Demand for Energy examined own-price elasticity across various regions 

of the United 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. evaluated 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 

The Cadmus Group, Inc. / Energy Services Division 24

For estimating residential impacts, the Cadmus team relied on conventional economic theory,

which states 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 fuels, 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 to price. Further, the 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 prices, and demand responds little to changes in price. 

The study used data from 1979 through 2004 and acknowledged that energy prices declined (in 

real dollars) during this period, which may have resulted in a tendency to reduce the elasticity 

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 jurisdictions 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 lower bound for the Mountain region elasticity reflected 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. It 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 responses to critical-peak pricing greater than responses

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 substitutes for 

on-peak usage. 

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

small nonresidential and agricultural pumping TOU customers. While the study cautioned 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% increase 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 

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.

This 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 applying 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 elasticity 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.

Coincident 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 

factors used in the rest of the Class 1 and 3 DSM potential analysis. Results suggested existing 

inverted block and TOU rates lowered on-peak usage from 1.6% to 4.0% on average across 

PacifiCorp’s six jurisdictions, resulting in 47 MW to 125 MW of reduced demand during system 

peak periods. 

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

usage on-peak, exhibiting 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 tier. 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 or Saved

Due to Rate 

Coincident Peak kW 

Impact

Percent of Estimated 

Baseline Consumption 

Shifted or Saved

Low High Low High Low High

TOU (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 rate 

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 of 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. Impacts were estimated by 

multiplying the substitution elasticity estimate by the percentage difference between the on-peak 

and off-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, the 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 25 MW and 140 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 Commercial and Industrial 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,

including 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 266 MW. As discussed in the methodology section, results of the market 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 Shifted or 

Reduced Due to Rate

Coincident kW 

Impact

Percent of Estimated 

Baseline Consumption 

Shifted or Saved

Low High Low High Low High

Residential 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 generator) during system peak hours for 

each of the Class 1 and 3 DSM programs. Table 10 shows 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 products 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 service territory has a substantially lower market potential (136 MW) than the Rocky 

Mountain Power service territory (533 MW). Additional factors contributing to the lower 

potential in the Pacific Power service territory include: lower temperatures during system peak;

lower saturations of cooling equipment (affecting the DLC AC program); and smaller irrigation

pumps (affecting the irrigation 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 2032) 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 Heating 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 reductions during system peak.

The residential and irrigation sectors exhibit the highest estimated market potential for Class 1 

and 3 DSM resources. The majority of this potential, however, already is under contract through 

PacifiCorp’s Cool Keeper (Utah) and Irrigation Load Control (Idaho and Utah) programs 

(121 MW and 209 MW, respectively). The nonresidential load curtailment program, which 

applies to both the C&I sectors, has the most remaining potential (189 MW) of any Class 1 DSM 

resource. As coincident peak impacts are based on average 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 reductions 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

Administration

Maintenance

Data acquisition

Hardware costs

Marketing expenses

Incentives25

Estimates for each type of expense category within 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 discounted 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 potential and per-unit ($/kW-year) costs

for each program in each state. The irrigation DLC program is expected to be the least expensive 

program option, with levelized costs ranging from $51/kW-year to $64/kW-year. Per-unit 

resource costs for the nonresidential load curtailment program are estimated at $69/kW-year for 

both service territories (as events are assumed to be called on a system-wide basis). The 

residential DLC AC program exhibits levelized costs ranging from $72/kW-year in Utah to 

$164/kW-year in Idaho. The assumed per-switch kW impact drives this 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 incentives for Class 1 and Class 3 DSM are treated as resource acquisition costs (rather than transfer 

payments), they are included in the levelized cost calculations.

26 A single full-time equivalent (FTE) employee 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 implementation 

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 2032)

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 totals 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 cost to the residential 

programs. Critical-peak pricing (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 (ranging 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 Buyback, 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 2032)

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 supply 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 enrolling 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 events, which may last up to four hours. The

utility compensates participating customers 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 approximately 121 MW of load under contract from its Cool Keeper 

air conditioner Program 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, where offered). As shown, Utah has the largest amount of potential 

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,

realizing 25% higher per-switch impacts.
PacifiCorp 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 ($/kWyr)*

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

Subtotal 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

Subtotal 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 totals 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 detailed assumptions about program costs, 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 cost (per new participant)

$60 per switch,

and $80 for 

installation 

labor

Based on vendor bids, research, and informal communication 

with vendors.

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

Annual vendor costs (%) 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 oneway 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.

Savings per switch Varies by state 

and sector

Savings per switch vary 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 state can be 

found in Appendix A-3.

Program participation

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% 

participation rate among eligible customers (The Brattle 

Group, WECC 20-year Demand Response Forecast 2012). 

Findings 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 ranging from 1.4% to 28%.

Event participation 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 

conditioners enrolled in the program and have electric water heat to qualify for participation. In 

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 

territories, respectively, as shown in Table 18.

Utah and Oregon offer the highest potential due to their large customer bases, compared to the 

other four states. The levelized cost remains the same across the residential and small 

commercial customer classes, given each DLC switch saves an assumed 0.5 kW, regardless of 

the customer class or state. 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

Subtotal 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

Subtotal 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 detailed assumptions about programs costs, participation rates, and 

other variables.

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

Program Element Assumption

Customer sectors eligible All residential and small commercial market segments.

End uses eligible for program Electric hot water heating, excluding heat pump water heaters. Program runs in conjunction 

with the DLC AC program.

Customer 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 communications 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 per 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 saturations 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. 

Saturations 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

PacifiCorp’s Irrigation Load Control programs 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 have transitioned to the dispatchable program option; therefore, for estimating 

potential, the irrigation DLC program is considered to be 100% dispatchable, without

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 over the 20-

year period. Given its high irrigation load, the majority of the market potential (78%) appears 
PacifiCorp 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 seasons offer much lower potential. 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 Load 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 

Subtotal 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 

Subtotal 210.4 209 1.4 $51

Total 222 209 12.5 $52

* Subtotals and totals are weighted by market potential.

Table 22 and Table 23 provides detailed 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.

Customer 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 communications 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 

types cause a lower level of load class eligibility for Oregon, Wyoming, California, and 

Washington. Additionally, irrigators are more geographically dispersed 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, choosing 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 utility (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. This 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‖

arrangements. However, customers with installed standby generation capability are considered

eligible for this program. 

Rocky Mountain Power’s service territory has an estimated 125 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 aggregators and service providers). Table 24

shows levelized costs and market potential by state. As the study assumed the program would be 

implemented system-wide, the system-level $/kW-year 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 

Subtotal 64 $69

Rocky Mountain Power

Idaho 9 $69 

Utah 91 $69 

Wyoming 25 $69 

Subtotal 125 $69

Total 189 $69

* Subtotals and totals are weighted by market potential.

Table 25 and Table 26 show detailed assumptions for the Nonresidential Load Curtailment

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.

Customer size requirements 150 kW or greater.

Applicable hours Top 60 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 meeting 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 kW)

$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 experience participation rates from 

4.5% (MidAmerican Energy) to 30% (Georgia Power and Indiana 

Michigan Power Company). See Appendix A-4 for participation by 

state.

Event participation (%) 95% Event participation in PJM and MidAmerican 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. Approximately 25% of residential customers in 

Idaho 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 Rocky 

Mountain Power territory and 7 MW of incremental market potential in the Pacific Power 

territory. Table 27 displays the market potential and levelized per-unit costs by state. Costs 

higher than in the 2011 Assessment reflect increases in PacifiCorp’s meter hardware and 

installation costs. 

Table 27. Residential TOU: Market Potential (MW in 2032) and 

Levelized Cost by State ($/kW-yr)

Territory State Market Potential (MW) Levelized Cost ($/kW-yr) *

Pacific Power

California 0.3 $347 

Oregon 4.3 $286 

Washington 2.3 $117 

Subtotal 6.9 $231

Rocky Mountain Power

Idaho - $0 

Utah 17.0 $124 

Wyoming 1.6 $195 

Subtotal 18.6 $130

Total 25.5 $157

* Subtotals and totals 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 detailed assumptions for the Residential TOU program.

Table 28. Residential TOU: Program Basics

Program Element Assumption

Customer sectors eligible All residential market segments.

End uses eligible for program All.*

Customer size requirements None.

Applicable hours Six 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.

* The TOU rate structure likely will not affect the consumption 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). Additionally, 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 market penetration rate is assumed 

to be incremental to current participation in states where TOU tariffs 

remain in effect, except Idaho, where no additional participation is 

expected (as previously discussed regarding the current Idaho

program).

Event participation (%) 100% Event participation is captured in the average load impact.

Irrigation TOU Rates

An irrigation sector TOU program is assumed to function similarly to the residential 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 

contrast to the mandatory structure analyzed in the 2011 Assessment.

Table 30 shows an estimated market potential of 11 MW in the Rocky Mountain Power service 

territory, with 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 significantly when 
PacifiCorp 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 costs, with costs highest in Washington and Wyoming, driven by estimated percustomer impacts.

Table 30. Irrigation TOU: Market 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 

Subtotal 7.3 $66

Rocky Mountain 

Power

Idaho 9.5 $20 

Utah 0.7 $58 

Wyoming 0.3 $97 

Subtotal 10.5 $25

Total 17.8 $41

* Subtotals and totals are weighted by market potential.

Table 31 and Table 35 show detailed 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 requirements None.

Applicable hours 120 hours: assumes two on-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)

Assumes 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 onpeak window of 2 hours, customers will be able to shift a higher 

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 current participation in states with 

an existing irrigation TOU rate.

Event participation (%) 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 noncritical-peak periods in exchange for paying premium prices during critical-peak events. As the 

peak price has been determined in advance, however, customers receive some degree of certainty 

regarding participation costs. The basic rate structure 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 majority of market 

potential occurs in the industrial sector, dominated by Utah, Wyoming, and Oregon loads.

CPP costs 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 variations result from the amount of load that 

can be reduced by a single customer (as marketing costs are tied to participants 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 

Levelized 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 

Subtotal 1.09 $14

Rocky Mountain Power

Idaho 0.08 $38 

Utah 1.39 $9 

Wyoming 0.90 $10 

Subtotal 2.37 $11

Total 3.46 $12

* Subtotals and totals are weighted by market potential.
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Table 34 and Table 35 show details on cost assumptions for the Nonresidential CPP program.

Table 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.

Customer size requirements C&I customers with maximum monthly demand 

greater than 1,000 kW.

Applicable hours Top 40 system hours, assuming 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 meeting 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 California 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 participation rates.

California, for example. experienced a 1.1% 

participation rate across the state, accounting for 2.9% 

of peak load enrolled. Individual utility participation 

ranged from 0.1% for SCE 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. 
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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 DBB 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 participating 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 the 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, PacifiCorp could rely on existing program infrastructures 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 

Subtotal 5.1 $26

Rocky Mountain Power

Idaho 0.4 $26 

Utah 9.2 $26 

Wyoming 4.2 $26 

Subtotal 13.7 $26

Total 18.8 $26

* Subtotals and totals are weighted by market potential.

Table 37 and Table 38 show detailed 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.

Customer size requirements C&I customers with maximum monthly demand greater than 1,000 kW.

Applicable hours Top 50 system hours.
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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 paid 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, accounting 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.
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CLASS 2 DSM (ENERGY-EFFICIENCY) RESOURCES 

Scope of Analysis

Assessing Class 2 DSM (energy-efficiency) resources primarily focused on updating 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). This 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 analysis addressed: 

Six 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 

One segment for irrigation.

Table 39, Table 40, and Table 41 show the full set of customer segments 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 Wyoming due to lack of forecasted load growth
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Table 39. Residential Sector Dwelling Types and End Uses

Residential Customer Segments End Uses

Manufactured Computer

Multifamily Cooking oven

Single-family 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 gal
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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 interior 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 cooling - DX evap

Space cooling - room

Space heat

Vending machines

Ventilation and circulation

Water heat <= 55 gal

Water heat > 55 gal
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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 Process 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 of

Oregon, as well as those within the Cadmus team’s library of measures. Analysis began by 

assessing the technical potential of hundreds of unique energy-efficiency measures (actual 

quantities are shown in Table 42). Considering all permutations of these measures across states, 

customer sectors, customer segments, end uses, and construction vintages required compiling 

and analyzing customized data for over 19,000 measure permutations. Volume II, Appendix B,

provides a complete 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 lighting 4 64

Total 376 19,265

* Measure counts and permutations represent only measures with potential energyefficiency savings. Appendix C-2 includes the comprehensive list of energyefficiency measures considered in this study. 

The remainder of this section is divided into four parts:

A detailed description of the methodology used for estimating the technical and 

achievable technical Class 2 DSM potential; 

Class 2 DSM resource potential, by state and sector; 
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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 combined ―topdown/bottom-up‖ approach. As shown in Figure 2, the top-down component began with the most 

current load forecast, adjusting for building codes, equipment efficiency standards, and market 

trends not accounted for in that forecast, then decomposing this into its constituent customer 

sector, customer segment, and end-use components. The bottom-up component considered

potential technical impacts of various Class 2 DSM measures and practices on each end use. 

Impacts could then be estimated, based on engineering calculations and accounting for fuel 

shares, current market saturations, technical feasibility, and costs. 

In this chapter, these 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 three types of potential: naturally occurring, technical, and achievable 

technical. 
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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 

associated 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 statespecific 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. Technical potential divides into two classes: discretionary (retrofit) and lostopportunity (new construction and replacement of equipment on burnout). 

This study’s technical potential estimations for Class 2 DSM resources drew upon best-practice 

research methods and standard analytic techniques in the utility industry. Such techniques 

remained consistent with conceptual approaches and methodologies used by other planning 

entities within PacifiCorp’s service area, such as those of the Council in developing regional 

energy-efficiency potential, and remained consistent with methods used in PacifiCorp’s 2007 and 

2011 Assessments. 

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 impede customer adoption. At this point, 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 the amount of 

technical potential considered achievable on an annual basis beginning in 2013.

Developing sound utility IRPs requires knowledge of alternative resource options and reliable 

information on the long-run resource potential of achievable technologies. DSM resource 

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.
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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 impeding measure implementation (achievable technical 

potential). The assessment utilized three primary steps: 

Baseline forecasting: Determining 20-year future energy consumption by state, sector,

market segment, and end use. The study calibrated the base year, 2012, to PacifiCorp’s 

sector load forecasts in each state. It then removed 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

Estimation of alternative forecasts of technical potential: Estimating technical potential,

based on alternative forecasts, that reflect technical impacts of specific energy-efficiency 

measures. 

Estimation of achievable technical potential: Achievable technical potential calculated 

by applying ramp rates and an achievability percentage to the technical potential, as this 

section later describes 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, comparisons to PacifiCorp’s sales forecast helped 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 representing

unrealistically high or low baseline sales percentages. 

Second, the approach maintained consistency among all assumptions underlying the 

baseline and alternative (technical and achievable technical) forecasts. The alternative 

forecasts changed relevant inputs at the end-use level to reflect impacts of energyefficiency measures. As estimated savings represented the difference between the 

baseline and alternative forecasts, they could be directly attributed to specific changes 

made to analysis inputs. 

Data Sources

Full assessment of Class 2 DSM resource potential required compiling large amounts of 

measure-specific technical, economic, and market data from secondary sources and primary 

research. Main 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 these adjustments, 2032 

baseline sales presented in this report may not match PacifiCorp’s official load forecast. 
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PacifiCorp: 2012 sales forecasts, historic and projected energy-efficiency activities,

current customer counts and forecasts, and the recent Energy Decisions Survey. Table 43

shows 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

Numbers 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 end-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 

Decisions 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 

Decisions Surveys

Building characteristics, 

equipment saturations, and fuel 

shares.

Building type breakouts; square footage per dwelling;

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.

2009–2010 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 

estimates 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 separate models created for each state, customer segment, 

and construction vintage.33

Pacific Northwest Sources: Several Northwest entities provided data critical to this 

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 described above); and commercial building physical and energy

consumption characteristics. Table 44 provides further details.

 

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.
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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 2007 and 2011 Assessments; 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 Studies

and the Council’s 6th Power Plan, data sources included the U.S. Department of Energy

Industrial Assessment Centers Database and reports from the Northwest Energy 

Efficiency Alliance (NEEA) on its Industrial Efficiency Alliance Initiative 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 assessing 

energy-efficiency potential. Prior to estimating potential, the study disaggregated state- and 

sector-level load forecasts by customer segment (business, dwelling, or facility types), 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 determined the appropriate customer segments 

within each state and sector. Designations drew upon categories available in some key data 

sources used in the study, primarily PacifiCorp’s 2011 customer 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 baseline 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 segment 

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).
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EUSEij = Σe ACCTSi * UPAi * SATij * FSHij * ESHije * EUIije

where:

EUSEij = total energy consumption for end use j in customer segment i

ACCTSi = the number of accounts/customers in customer segment i

UPAi = units per account in customer segment i (UPAi generally the average square feet 

per customer in commercial segments, and 1.0 in residential dwellings, assessed at the 

whole-home level)35

SATij = the share of customers in customer segment i with end use j

FSHij = the share of end use j of customer segment i served by electricity

ESHije = the market share of efficiency level e in equipment for customer segment and 

end use ij

EUIije = end-use intensity: energy consumption per unit (per square foot for commercial) 

for the electric equipment configuration ije 

For each sector, total annual consumption could be determined as the sum of EUSEij across the 

end uses and customer segments. Ensuring 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 Energy 

Information Administration (EIA).

36 For the irrigation sector, the total load in each state has been 

well established, consisting almost 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 

present in each state.

Volume II, Appendix C, provides summaries of baseline forecasts for each state and sector.

Derivation of End-Use Consumption Estimates

Estimates of end-use energy consumption by segment, end use, and efficiency level (EUIije) 

provide one of the most important components in developing a baseline forecast. In the 

residential sector, the study based estimates on unit energy consumption (UEC), representing 

annual energy consumption associated with an end use (represented by a specific 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 home size differences between states. 

36 U.S. Department of Energy (DOE), EIA. 2006. Manufacturing Energy Consumption Survey.
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For the commercial sector, the study treated consumption estimates as end-use intensities (EUIs), 

representing annual energy consumption per square foot served. Accuracy of these estimates 

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 represented total annual industry 

consumption by 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, including weather, state codes, building sizes, 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 

STAR; 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 key drivers used in developing commercial simulation models (operating schedules, 

setback temperatures, and building sizes) drew upon data in PacifiCorp’s Energy Decisions 

Survey.

40 The study based residential simulation models on the RTF’s SEEM models for its 

energy-efficiency measures. To create a simulation, SEEM used a number of input parameters,

including those for occupancy, equipment, ducts, envelope, foundations, and infiltration. The 

Cadmus team updated the SEEM models specifically for PacifiCorp’s service territory. Volume 

II, Appendix C, summarizes end-use consumption estimates for residential (UECs), commercial 

(EUIs), and industrial (end-use percentages).

Energy-Efficiency Measures

As technical potential drew upon an alternative forecast, reflecting installation of all technically

feasible measures, selecting 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, for the residential 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 technologies, 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/regional-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 available studies.
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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 replace enduse equipment (e.g., high-efficiency central air conditioners), while non-equipment measures 

reduce 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 thermal 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 freezers and secondary refrigerators.

Equipment: ENERGY STAR freezers and refrigerators; high-efficiency cooking ovens, 

ranges, and dryers.

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-Term, System-Wide Potential March 2013

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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 settingsoptimization; chilled water piping loop with VSD control; cooling tower approach temperature; twospeed and variable-speed fan; pipe insulation for chillers; cool and green roof; natural ventilation; 

infiltration reduction; new construction Integrated Building Design; window film; hotel key 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 packages; 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 heating 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 heater.

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 and 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; vertical and semi-vertical no doors 

refrigeration.

Appliances Non-Equipment: appliance recycling.

Equipment: ENERGY STAR freezers and refrigerators.

Plug load 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: ENERGY STAR computer, monitor, fax, copier, printer, and vending machine; highefficiency server.

Cooking Non-Equipment: High-efficiency combination and convection oven, fryer, griddle; ENERGY STAR 

hot food holding cabinet and steam cooker.
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Table 47. Industrial Energy-Efficiency Measures Types

Measure Types

Agricultural process improvements

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 improvements

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

Assessing technical potential began by estimating measure-level impacts, which required 

compiling and analyzing data on the following characteristics for each measure:

Measure savings: Energy savings associated with a measure, as a percentage of total 

end-use consumption. Sources included: standard engineering algorithms, energy 

simulation modeling, the Council’s 6th Power Plan, RTF, PacifiCorp’s 2011 FinAnswer®

Express market characterization studies, secondary data sources (case studies), and the 

California DEER database. 

Measure life: The measure’s expected useful life. Sources included: the DEER database, 

the Council’s 6th Power Plan, other potential studies, and DSM program evaluations. 
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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 sharing of energy savings with competing measures. Sources include 

Council’s 6th Power Plan, RTF, and the DEER database.

Measure costs: Per-unit costs (either full or incremental, depending on the application) 

associated with measure installation. Sources included 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 annual operation and 

maintenance costs. These may be positive or negative, compared to the baseline, and are 

subtracted 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 accounted 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 benefits: Additional energy benefits attributable to a measure, such as 

natural gas savings,

42 subtracted from the measure’s net present value cost when 

calculating costs of conserved energy (also only included for Washington and Idaho).

Conservation Credit: The 10% regional conservation credit used in the 6th 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 includes 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, assumed

that, as equipment fails or new homes are built, customers will install LED lighting wherever 

technically feasible 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 savings in Oregon for IRP modeling. 
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

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In estimating 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 insulation measures have 

already been installed can produce fewer savings than upgrades in an uninsulated home. Analysis 

of technical potential accounts for two types of interactions:

Interactions between equipment and non-equipment measures: As equipment burns 

out, technical potential assumes it will be replaced with higher-efficiency equipment, 

reducing average consumption across all customers. Reduced consumption causes nonequipment measures to save less than they would have, had equipment remained at a 

constant 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 heaters to operate more 

efficiently, thus reducing savings from either measure. This assessment accounted for 

such interactions 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 assumed 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 estimated 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

reasonably achievable in the course of a planning horizon. The quantity of energy-efficiency 

potential realistically achievable depends on several factors, including the customers’ willingness

to participate in energy-efficiency programs (partially a function of incentive levels), retail 

energy rates, 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. Assessing achievable 

 

44 Consumers’ apparent unwillingness to invest in energy efficiency has been attributed to certain energyefficiency 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 information, and uncertainty concerning the benefits, costs, and risks of energyefficiency 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 and 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-Term, System-Wide Potential March 2013

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technical potential, however, adopts a central tenet that assumes it is ultimately a function of the 

customers’ willingness and ability to adopt energy-efficiency measures; this information can be 

best ascertained through direct elicitations from potential participants. 

Though methods for estimating achievable technical potential vary across potential assessment 

efforts, two dominant approaches appear to be most widely utilized:

1. The 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. In 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 used option two, assuming 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 layers of ramp rates have been incorporated for all measures 

and market regions. 

Estimated achievable technical potential principally serves as a planning guideline. Acquiring 

such DSM resource levels depends on actual market acceptance of various technologies 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, depending on actual experiences 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 applied measure ramp rates to lost opportunity and discretionary resources, though 

interpretation and application of these rates differed for each class (as described below). Measure 

ramp rates generally matched those used in the Council’s 6th Power Plan, although the study 

incorporated additional considerations for Class 2 DSM measure acquisition:

The 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).
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General service CFLs required use of a custom ramp rate, with the study’s CFL 

penetration estimate in 2013 aligning with PacifiCorp’s 2012 activity, market trends, and 

forecasted 2013 activity. 

Lost Opportunity Resources

Quantifying achievable technical potential for lost opportunity resources in each year required 

determining amounts technically available through new construction and natural equipment 

turnover. New construction rates drew directly from PacifiCorp’s customer forecast. The study 

developed equipment 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 turning over 

each year would be a function of this RUL; thus, the technical potential for lost opportunity 

measures would have an annual shape before application of any ramp rates, as shown in Figure 

3. The same concept applied to new construction, where resource acquisition opportunities only 

become available during home or building construction. In addition to showing an annual shape, 

Figure 3 demonstrates amounts of equipment turning over 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 represented median lifetimes, 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.pdf

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PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

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In addition to natural timing constraints imposed by equipment turnover and new construction 

rates, the Cadmus team applied measure ramp rates to reflect other resource acquisition 

limitations over the study horizon, such as market availability. These 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 achieved over a 20-year planning horizon. 

As illustrated by Figure 4, a measure that ramps 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. Particularly in the early years of the study horizon, a gap occurs

between assumed acquisition and the 85% maximum achievability. Thus, these ―lost‖ resources 

can be assumed not available until the measure’s EUL elapses. Therefore, depending on EUL 

and measure ramp rate assumptions, some potential may be pushed beyond the study’s 20th 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. The 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.

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% of Annual Technical Potential Acquired

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PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

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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 11th

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 technical 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 technical potential (also shown in Figure 5). Across all lost opportunity measures 

included in this study, approximately 72% of technical potential appears 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 achieved.

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.htm

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Percent of 20-Year Technical Potential

Cumulative Technical

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Cumulative Achievable Technical (20-Year Ramp)
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

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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 

Opportunities 

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 Resources

Discretionary resources differ from lost opportunity resources due to their acquisition availability 

at any point within 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 

infrastructure 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, potentially 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 addressed discretionary resources in two steps:

1. Developing a 20-year estimate of discretionary resource technical potential, assuming 

technically feasible measure installations would occur equally (at 5% of the total 
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 69

available) for each year of the study, and avoiding distortion of interactions between 

discretionary and lost opportunity resources, as described above.

2. Overlaying 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-year discretionary ramp rate reaches 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.

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Annual Incremental Achievable Technical Potential as % of 20- Year Technial Potential 10-Year Discretionary (Annual) Emerging Technology Discretionary (Annual)

10-Year Discretionary (Cumulative) Emerging Technology Discretionary (Cumulative)
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Market Ramp Rates

After addressing technical and general market constraints, the study applied 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 measure-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 assumes 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 impact 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, reflecting 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 unadjusted 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 these 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 to timing constraints of lost opportunities, failure to 

acquire these resources in early years may push opportunities beyond the 20-year study period, 

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Annual Market Ramp Rate Adjustment

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depending on the EUL. As 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 Impacts 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 aligned 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 within 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 jurisdiction.

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Cumulative % of 20-Year Achievable Technical 

Potential (aMW)

Before Market Ramp After Market Ramp
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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. To maintain consistency with the Council, RTF

and accepted regulatory practices, secondary benefits, non-energy impacts, and incremental 

O&M have been included for Washington 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 apply during the IRP modeling process,

and this credit has not been included in the levelized costs presented in this report.

The 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 levelized 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 reinstallation 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 costs 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 costs.

 

48 This method applied both to measures with a useful life greater than 20 years and those with useful lives 

extending beyond the 20th year at the time of reinstallation.

Component 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Initial Capital Cost

Re-Installation Cost End Effect

Year
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 73

Incentives for all other measures 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 

provided incentives for first measure installations. That is, customers will reinstall the measure 

without utility intervention, and savings persist throughout the planning period, though the cost 

is incurred only during the first installation.

To determine an appropriate assumption for administrative costs, the Cadmus team reviewed

eight electric utilities’ recent (2010 and 2011) annual reports, comparing non-incentive 

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 team used a 20% administrative cost assumption for 

this assessment (a formulation consistent with the Council’s assumed 20% administrative adder 

in the 6th Power Plan).

Summary of Resource Potentials

Table 50 and Table 52 show 2032 baseline sales and cumulative potential by sector and state, 

respectively. 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) achievable across all sectors and states (or 12% of forecasted 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. 

The cumulative energy savings differs 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 20th 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 retrofit), 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): Alliant 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

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The study estimated 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 future 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 lighting 13 4 35% 4 30%

Total 5,311 819 15% 648 12%

Note: Results may not sum to totals 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 lighting 0.6 0.5

Total 1,540 1,241

Note: Results may not sum to totals 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 Achievable 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 15%

Washington 487 94 75 15%

Subtotal 582 112 88 15%

Rocky 

Mountain 

Power

Idaho 268 47 34 13%

Utah 3,002 491 389 13%

Wyoming 1,459 169 136 9%

Subtotal 4,729 707 560 12%

Total 5,311 819 648 12%

Note: Results may not sum to totals 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 totals 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 resource 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 modeled 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 combination 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 Caveats aside, study results estimate discretionary resources

 

52 Residential 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 insufficient 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 76

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 Technical 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 totals 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 2020 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 watt), it is 

assumed that all incandescents are replaced with CFLs by 2020. These 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 Sector

0

100

200

300

400

500

600

700

20132014201520162017201820192020202120222023202420252026202720282029203020312032

aMW

Residential Commercial Industrial Irrigation Street Lighting
PacifiCorp 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. Single-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, achievable 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, accounts for 62% (112 aMW) of this identified achievable technical potential.

Table 55. Residential 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 totals due to rounding.

As shown in Figure 11, single-family homes represent 76% (145 aMW) of total achievable

technical residential potential, followed by multifamily (32 aMW) and manufactured homes (13 

aMW). Each home type’s proportion of baseline sales primarily drives these results, but other 

factors, such as heating fuel sources, play an important role in determining potential. 

For example, multifamily homes more commonly use electricity for space heating than do 

single-family homes, increasing their relative shares of space heating potential. Alternatively, 

lower use per customer for multifamily units decreases 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. 

Specific 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 shown in Table 56 and Figure 12), where space heating (central and room) accounts 

for 26%, cooling accounts for 27%, heat pumps account for 3%, and an additional 3% comes 

from ventilation and circulation. While significant opportunities exist in residential lighting

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 impacts of the 2020 EISA backstop 

provision. Additional potential 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 example, 84% of cooling savings shown in Table 56

and Figure 12 occurs in Utah. Detailed results showing 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. 

Single Family

76%

Multifamily

17%

Manufactured

7%

Total: 190 aMW
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 dominates 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 totals due to rounding.

As shown in Figure 13, ―miscellaneous‖ buildings represent the largest share of cumulative,

achievable, technical potential in the commercial sector (36%). 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, grocery 

Appliances

10%

Cooling

27%

Heat Pump

3%

Heating

26% Lighting

8% Plug Load

7%

Pool Pump

<1%

Ventilation and 

Circulation

3%

Water Heat

16%

Total: 190 aMW
PacifiCorp 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 detailed 

information regarding achievable technical potential within each state.

Figure 13. Commercial Sector Class 2 DSM Achievable 

Technical Potential by Segment in 2032

Lighting efficiency (including interior and exterior applications) represents the largest portion of

achievable technical potential in the commercial sector (37%), followed by cooling (16%) and 

ventilation and circulation (13%), as shown in Table 58 and Figure 14. These results reflect the 

pending federal standard, effectively outlawing most T-12 lamps. 

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 chillers 10 4 4 34% 2%

Cooling DX evap 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%

Grocery

7%

Health

3%

Office

17%

Retail

8%

Lodging

3%

Miscellaneous

36%

Restaurant

4%

School

10% Warehouse

7%

Data Center

5%

Total: 234 aMW
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 interior HID 78 8 7 9% 3%

Lighting interior 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 heat GT 55 gal 1 0.2 0.2 18% 0%

Water heat LE 55 gal 20 8 7 33% 3%

Total 1,522 282 234 15% 100%

Note: Results may not sum to totals due to rounding; ―other‖ includes servers, fans, and HVAC in data centers.

Figure 14. Commercial Sector Class 2 DSM Achievable 

Technical Potential by End Use in 2032

Appliances

1%

Cooking

0%

Cooling

16%

Heat Pump

3%

Heating

8%

Lighting

37%

Other

5%

Plug Load

6%

Refrigeration

8%

Ventilation 

and 

Circulation

13%

Water Heat

3%

Total: 234 aMW
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 83

Industrial Sector

The study assessed technical and achievable energy-efficiency potential for major end uses

within 14 major industrial segments in PacifiCorp’s service territory. These customer segments 

were based on SIC53 allocations in PacifiCorp’s customer database. The assessment estimated

207 aMW of industrial achievable 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 

Baseline 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 totals 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 nearly 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 

state- 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 falls 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 savings (60%) can be attributed to efficiency gains in air 

compressors, pumping, air distribution, and other motors (including mining applications). 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 slice of potential (27 aMW). Lighting 

and process heating present the two end uses with the most savings, each accounting for 20% of 

achievable technical potential. Remaining potential splits between HVAC54 and other building

improvements, process improvements, and lighting (as shown in Figure 16 and Table 60).

Table 60. Industrial 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 cooling 118 7 6 5% 3%

Process heating 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.

Agriculture

1% Chemical Mfg

9%

Electronic 

Equipment Mfg

6%

Food Mfg

9%

Industrial 

Machinery

14%

Lumber Wood 

Products

9%

Metal Mfg

13%

Mining

2%

Miscellaneous 

Mfg

16%

Paper Mfg

2%

Petroleum Refining

2%

Stone Clay Glass 

Products

8% Transportation 

Equipment Mfg

5%

Wastewater

Water 1%

3%

Total: 207 aMW
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

compressors

152 30 25 16% 12%

Process electrochemical 130 0.0 0.0 0% 0%

Process other 73 0.3 0.3 0% 0%

Process refrigeration 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. Irrigation 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 improving pumping efficiency, 

including high-efficiency motors, irrigation system improvements, and SIS. 

Table 61 shows cumulative potential in 2032 associated with these measures.

 

55 Non-pumping end uses include system controls and motor drives for wheel-based systems.

Fans

5%

HVAC

12%

Lighting

20%

Motors Other

13%

Other

3%

Process Cool

3%

Process Heat

20% Pumps

8% Process Air 

Compressor

12%

Process Other

<1%

Process Refrig

4%

Total: 207 aMW
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 totals 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 

relates to pump lift (total dynamic head), which varies across different service 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 

commonly used for irrigation water.

Street Lighting

Upgrading 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 

approximately 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 totals 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 customerowned 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 Ownership (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 totals 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: 

Accounting for newly enacted building codes and equipment efficiency standards, even if 

they have not yet taken effect;

Adjusting for PacifiCorp’s actual and projected DSM program accomplishments from 

2010 through 2012;

Incorporating adjustments to measure savings, based on recent evaluation results, 

including data available from the Regional Technical Forum (RTF);

Applying 2011 customer information to determine segmentation; and 

Utilizing 2012 sales and customer forecasts.

Together, these changes decreased 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 Assessment, 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 Wyoming), 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 occurring for 

street lighting and irrigation). 

Part of this decrease, as described in the Introduction section 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 prevailing 
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

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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 20th year dropped from the 

prior study by about 40% (142 aMW), largely due to this study projecting continuing high 

ENERGY STAR market shares.58

Table 64 compares, by sector, achievable technical potential (in aMW and as a percentage of 

sales) between the two assessments. This comparison includes potential in the 20th 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 one driver of this 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 6th Power Plan. In Washington, most measures were updated based on 

recent RTF work. RTF updates primarily reflect recent evaluation work as well as ongoing 

reviews 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 sectors, 

both studies estimated 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 stock.

While potential, in percentage terms, remained the same at the sector level for commercial, 

industrial, and irrigation, differences occurred between the two studies at the end-use level. For 

example, this study thoroughly reviewed and updated measures comprising interior lighting 

potential; these were based on more recent lighting fixture data, a methodology to estimate postinstallation lumen requirements,59 new building codes, and the 2012 lighting standard. Table 65

 

57 These high saturations will likely 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 Assessment 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. 
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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, cumulative achievable technical potential as a percentage of

year-20 baseline sales decreased from 29% to 15%, driven by many factors—most significantly

updates to assumed market shares of ENERGY STAR appliances and office equipment, 

including dehumidifiers, computers, 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. The 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, and measure efficiency levels also contributed 

to changes in the HVAC potential, but SEEM models alone would drive the savings down.
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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

2011 Current 2011 Current aMW Percent Key Drivers of Differences

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 shares led to lower baseline 

sales. Savings shifted from achievable technical to naturally 

occurring.

Cooking 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 data centers) N/A 6 N/A 1 1 N/A Not included in the prior study.

Ventilation and Circulation 499 327 14 31 17 121%

An additional measure (motors VFD) accounted for most of the 

difference in potential change; Year-20 sales 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 2,367 1,524 361 234 -126 -35%

* Numbers may not sum to totals due to rounding. 
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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

2011 Current 2011 Current aMW Percent Key Drivers of Differences

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; Year-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 1,787 1,294 514 190 -322 -63%

* Numbers may not sum to totals due to rounding.
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SUPPLEMENTAL RESOURCES

Scope of Analysis

As in the 2007 and 2011 Assessments, the term ―supplemental resources‖ referred 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 amounts required from utility-owned resources. This study assessed the following such 

resources:

CHP

Solar PV

SWH

Traditionally, such resources fall outside the standard classification of Class 2 DSM resources 

for two main reasons: either they reduce 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 costs. Levelized 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, representing total electric generation (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 assumed every rooftop with favorable (i.e., southern) solar 

exposure would have a PV system 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. Market potential measures the likely penetration 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 

variations, as appropriate. For example, for PV, market potential ties 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 variations in assumptions exist 

between technologies, overall TRC levelized costs included:

The installation cost, less the federal investment tax credit (ITC) for systems installed 

before 2017, assuming the ITC expires as planned on December 31, 2016. State tax 

credits and utility incentives are not deducted from the installation cost, as although the 
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TRC test counts these as benefits to customers installing the systems, they are also 

included as costs to the state’s taxpayers, resulting in a zero net effect.

Utility costs 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:

Administration and marketing costs.

Incentive amounts, assumed to be a percentage of installed costs after applying the 

federal tax credit62 and accounting for projected trends in incremental costs. State tax 

credits do not affect the utility incentive amount.

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. Costs were then divided by the 

system’s energy production over its lifespan, obtaining the levelized cost of energy (LCOE). 

Energy production includes a line loss factor, varying by state and sector, as shown in Section 1 

of this report. These 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). Energy production 

over the system’s life accounted for system performance degradation, as applicable.

CHP

Technologies Assessed

CHP systems generate electricity and utilize waste heat for thermal loads, 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 have been installed in hospitals, schools, and manufacturing 

facilities, but they can be used across nearly all C&I market segments with average monthly

energy loads greater than about 30 kW. CHP broadly divides into subcategories, based on fuels

used; nonrenewable 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 $/MMBtu) for use in the levelized cost analysis. 

62 The incentive does not increase with expiration of the federal tax credit in 2016.
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The Cadmus team analyzed the same nonrenewable CHP systems as in the 2011 Assessment:

Reciprocating engines (RE)

Microturbines (MT)

Gas turbines (GT)

Fuel 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 technologies as the 2011 Assessment, 

analyzing 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 assumed the combustion process includes a CHP 

system (generally, steam turbines) to generate electricity on-site. Industrial biomass 

systems generally operate on large scales, 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, (WWTFs), and livestock farms.

The study did not include waste heat-to-power (WHP) systems, 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, dispersed 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 

market 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. 
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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 www.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, USDA 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 summarize key inputs for each technology. Table 68, Table 69, Table 70, and 

Table 71 list assumptions for nonrenewable fuel systems by technology 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, equals the increased system fuel use (total 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 assumed waste heat fed back to the anaerobic digester for 

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 expenses for 

building digesters have not been included, as this could be completed independently of the CHP 

system. Similarly for biomass systems, the study assumed boiler and fuel processing systems 
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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 cost
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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 cost ($/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 cost ($/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%

Installation costs shown in the above tables have been based on national averages. Analysis

adjusted these values for each state, based on living costs in the part of state served by 

PacifiCorp. Table 74 shows these adjustment factors (with the cost in each state as a percentage 

of the 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%
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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 details 

provided in Volume II, Appendix D-1). 

Costs slightly increase for systems installed after 2016, when the federal tax credit expires. 

Levelized costs vary across states due to differences in cost-of-living adjustments, line losses, 

and natural gas rates. Energy production over the system’s life accounts for system performance 

degradation.

The Cadmus team calculated levelized costs based on the TRC perspective for all states, for 

consistency with treatment of other generation resources in the IRP, as these 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 Potential

The Cadmus team calculated technical CHP potential based on the sources described above,

including PacifiCorp customer data, and data on farms, landfills, and WWTFs within 

PacifiCorp’s service territory, resulting in a total estimated 20-year system-wide technical 

potential of 4,301 MW, as measured at the generator. Table 76, below, details technical potential 

by technology and by rated system capacity (MW).
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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 systems 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). 

Table 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 Potential

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, relative to estimated 

technical potential, and calculated by dividing the average annual capacity (MW) of CHP 

installed from 2008 through 2011 by the estimated technical potential for the 2008–2032

period.

63 Percentages 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. The study estimated a cumulative 20-year market potential of 

336 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 technical 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.
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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 12 336

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 assumed the 

measure would be reinstalled upon burnout. 

Peak Impacts

CHP unit peak impacts were assumed the equivalent of system capacity. That is, all CHP 

systems could operate at their nameplate capacity during 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. Widely 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 primarily 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 projections.

The study used building stock data gathered during PacifiCorp’s Energy Decision Surveys, 

conducted in 2005 for commercial and in 2006 for residential, combined with 2011 customer 

data and relevant building characteristic assumptions, to identify the total roof area expected 

feasible for solar PV system installations. The Cadmus team then conducted a literature review 

of typical PV system power densities 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 presented as values at the generator.

Figure 17. Calculation Steps for Technical Potential

Data Sources and Assumptions

As shown in Table 79, the 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 

Potential
PacifiCorp 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 potential 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 rates drew upon actual capacity installed, relative 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 2012. 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 percentage of technical potential achieved in the states with long-term incentive 

programs (Oregon and California) and in the states without incentive 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 underrepresent 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 this 

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 Cadmus team used a combination of reported actual capacity installed, by state 

and sector; technical potential, calculated as described above; and ramp rates. Table 81 lists 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, 

reflecting 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 PacifiCorp’s direction, 2013–2017 market potentials for Utah were fixed to match program filings.

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. Ramp 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, this 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%

ID 0.01% 0.02% 0.01%

WY 0.01%

Yes

OR 0.02%

CA 0.02% 0.14% 0.08%

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

To 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 factor applying to peak demand periods for 

solar PV in the residential and commercial sectors for each state. In general, every MWdc of 

installed PV results in approximately 400 kW of peak reduction, varying slightly by state and 

segment. Total 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 costs separately for residential customers (separated into single-family and multifamily 

buildings) and commercial customers (a category including health, lodging, large office, large 

retail, and school buildings).

The study adjusted 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 performance degradation to estimate energy outputs of systems installed in future years 

and of systems as they age. The PVWatts model, developed by NREL, produced estimates of

capacity factors 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 

inputs used in analysis). The table includes Website links to sources (if available). If reports 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 Solar 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 Committee.

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 

Energy Efficiency and Renewable Energy.

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/calculators/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 reviews

and meter replacements by the utility is estimated at less than 1% of total system costs, therefore

having a minimal impact on cost-effectiveness.

Overview of Installed System Cost Data

The Cadmus team gathered and reviewed installed system cost data from four main sources: 

1. The Utah Solar PV Incentive Pilot Program

2. The Utah State Energy Program

3. The California Solar Initiative (CSI)

4. Energy Trust of Oregon Program 
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 108

Table 86 compares installed costs 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 Photovoltaics for Utility Scale Applications (PVUSA) Test Conditions (PTC) module size was used, with the 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. Standard test conditions (STC) include: 1,000 watts of solar irradiance per square meter; 25 

degrees Celsius cell temperature; air mass equaling 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 average system cost data for residential and nonresidential systems, with the < 5 kW system cost 

corresponding to residential systems (with an average size of 2.7 kW), and the 10 to 30 kW system cost corresponding to 

nonresidential systems (with an average size of 13.9 kW).

For Utah and CSI system costs, the Cadmus team used the year customers first applied for the 

program, assuming this the best proxy for the year the customer received a price quote. Analysis 

also eliminated CSI systems with third-party system owners, as it could not be determined 

whether these systems fell under a Power Purchase Agreement, which generally resulted in 

higher reported costs. The study removed sales tax from California costs to isolate PV equipment 

and installation costs. Data 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 represents a conservative predictor of 

future cost trends. 

The following tables summarize inputs used for the analysis. Table 87 lists assumptions 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 Size 3 kW Average residential system size in the 2011 Utah Solar PV Incentive Pilot 

Program was 3.2 kW, as was the average residential system size in the Utah 

State Energy Program in 2011. The average size in the Energy Trust program in 

2012 is 2.7 kW.

Measure Life

(years)

30 The typical 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 in 

Nominal 

Installation Cost

-4.6% From the LBNL study, as the trend from 1998 to 2010; supported 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)

$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 across 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 Size 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 participants 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 in 

Nominal Installation

Cost

-4.6% Found in the LBNL study as the trend from 1998 to 2010; supported 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; 

assumes one inverter replacement over 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 (monocrystalline, 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.

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 increase before 

resuming a downward trend through 2032. As discussed, the 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 0.16

ID Res $0.28 $0.33 $0.17 0.17

NonRes $0.26 $0.30 $0.16 0.17

OR Res $0.30 $0.35 $0.18 0.16

NonRes $0.27 $0.32 $0.17 0.16

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 0.16

NonRes $0.28 $0.33 $0.17 0.16

WY Res $0.25 $0.30 $0.15 0.19

NonRes $0.23 $0.27 $0.14 0.19

* 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 electricity 

to heat water. Widely 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 the 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 heaters was 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 determined 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 this 

market potential percentage on actual Energy Trust rebate data (for program years 2009 through 
PacifiCorp Assessment of Long-Term, System-Wide Potential March 2013

The Cadmus Group, Inc. / Energy Services Division 112

2011) and on technical potential calculated by Energy 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 0.37 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 kWthermal/m2(0.065 

kWthermal/ft2) 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 shape 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. The Pacific Power territory has a coincidence factor of 0.973, 

and Rocky Mountain Power territory has a factor of 0.971. Total 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 Assessment Update: 

http://energytrust.org/library/reports/121114_2012_ResourceAssessment.pdf

67 Winn, Menicucci, and Vuppuluri. Effective Power Ratings for Solar Hot Water Systems. Available at: 

http://www.academia.edu/247830/EFFECTIVE_POWER_RATINGS_FOR_SOLAR_HOT_WATER_SYSTE

MS
PacifiCorp 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 uses 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 (SWHPP). This report compiled 

SWH information from numerous sources, including cost data from incentive programs in the 

United States and information from contractor interviews.68

For the SWH analysis, the Cadmus team reviewed the Itron report and other data sources, such 

as the ENERGY STAR Website and NREL. The Cadmus team also downloaded the most recent 

California Solar Thermal program data from the California Public Utilities Commission to 

update installed system costs for residential and nonresidential systems. The Cadmus team

obtained information about average system costs for residential systems from the Energy Trust.

Resources for Calculations

The solar fraction—the percentage of energy used for heating water provided by the SWH—

provided the data required to calculate energy savings. Solar fractions for each segment and 

location combination were developed using RETScreen International69 and assumptions of 

gallons of hot water used per day and sector-specific load shapes. Numbers of collectors were

adjusted until the solar fraction neared 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 ranging 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.org/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 Fuel 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 

heaters 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 installation 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 increased market adoption balancing 

increasing material costs for SWH system components.

Residential, Multifamily, and Commercial Inputs

Table 92 lists 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 Retrofit 

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 Nominal 

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 lists 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 Size 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 Thermal 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 in 

Nominal Installed Cost

0% The Cadmus team assumes costs will remain stable over the next 20 years.

Annual O&M Cost 10% of installation 

cost divided by 20 

years

Assumes customers have systems inspected and glycol flushed and replaced 

periodically. (SWHPP Interim Evaluation Report Table 7-11)

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.

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 free of charge 

from: https://www.nrel.gov/analysis/sam/

Solar Fraction Varies by location 

and sector

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.

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 Utah (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 Energy 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 $0.15

Residential $0.45 $0.29 $0.04 $0.45 $0.36

2017-2032

Nonresidential $0.25 $0.22 $0.02 $0.26 $0.21

Residential $0.63 $0.40 $0.04 $0.62 $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 the technical potential for supplemental resources, by resource category 

territory. 

Table 95. Supplemental Resources Technical Potential by Territory 

and Resource Category (Cumulative aMW in 2032)

Resource Rocky Mountain Power Pacific Power PacifiCorp System

CHP 3,227 1,074 4,301

On-Site Solar: PVs 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 totals 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: PVs 43 23 65

On-Site Solar: Water Heating* 2.6 0.7 3.3

Total 168 68 236

* Excludes Oregon

Note: Results may not sum to totals due to rounding.