Prepared by GDS Associates and the Cadmus Group

Page 1 

# E LECTRIC AND 

# N ATURAL 

# G AS 

# E NERGY 

# E FFICIENCY

AND 

# D EMAND 

# R ESPONSE 

# P OTENTIAL FOR 

# T HE



# D ISTRICT OF 

# C OLUMBIAD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page i 

### T ABLE OF 

### C ONTENTS



### 1 E XECUTIVE 

### S UMMARY



### ................................ ................................ ................................ ....... 1

1.1 Background

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

1.2 Cost Effectiveness Findings

................................ ................................ ................................ ....................... 2

1.3 Study Scope

................................ ................................ ................................ ................................ ................... 3

1.4 Report Organization

................................ ................................ ................................ ................................ .... 4

1.5 Summary of Results

................................ ................................ ................................ ................................ ..... 4

1.6 Energy Efficiency Potential Savings Detail

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



### 2 G LOSSARY OF 

### T ERMS



### ................................ ................................ ................................ ......... 9

3 I NTRODUCTION



### ................................ ................................ ................................ ............... 14

3.1 Introduction to Energy Efficiency

................................ ................................ ................................ .......... 14

3.1.1 General B enefits of Energy Efficiency

................................ ................................ ................................ 14

3.2 The Washington DC Context

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

3.2.1 Continuing Customer Growth

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

3.2.2 Energy Efficiency Activity

................................ ................................ ................................ ................ 16

3.2.3 Recent Energy Efficiency Potential Studies in the Mid

- Atlantic Region

................................ ............. 16

3.3 Purpose of this Study

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

3.4 Cost

- effectiveness Findings

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



### 4 C HARACTERIZATION OF 

### W ASHINGTON 

### DC S ERV ICE 

### A REA



### ................................ ............ 19

4.1 Washington DC Member Service Territories

................................ ................................ ........................ 19

4.1.1 Washington DC Geographic and Demographic Characteristics

................................ ......................... 19

4.1.2 Historical Electric Sales and Electrical Customers in Washington DC

................................ ............. 21

4.2 Forecast of Energy Sales & Peak Demand (2013

- 2023 )

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

4.3 Natural Gas Use in Washington DC

................................ ................................ ................................ ....... 23

4.4 Natural Gas Consumption in Washington DC

................................ ................................ ..................... 24

4.4.1 Introduction

................................ ................................ ................................ ................................ ...... 24

4.4.2 Total Gas Sales and Customer Forecast

................................ ................................ ........................... 25

4.5 Current DDOE and DCSEU DS M Offerings

................................ ................................ ...................... 27

4.5.1 Current DDOE Energy Efficiency Programs

................................ ................................ ................... 27

4.5.2 Current Programs Offered by the DC Sustainable Energy Util ity (DCSEU)

................................ .. 28



### 5 P OTENTIAL 

### S TUDY 

### M ETHODOLOGY



### ................................ ................................ ............... 30

5.1 Measure List Development

................................ ................................ ................................ ....................... 30

5.1.1 Measure Characterization

................................ ................................ ................................ ................ 31

5.2 Forecast Disaggregation

................................ ................................ ................................ ............................ 32

5.2.1 Role of Naturally Occurring Conservation

................................ ................................ ........................ 32

5.3 Potential Savings Overview

................................ ................................ ................................ ...................... 3 3

5.4 Technical Potential

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

5.4.1 Core Equation for the Residential Sector

................................ ................................ .......................... 35

5.4.2 Core Equation for the Non

- Residential Sector

................................ ................................ .................. 37

5.5 Economic Potential

................................ ................................ ................................ ................................ .... 38D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page ii 

### 5.6 Determining Cost

- Effectiveness

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

5.6.1 Societal Cost Test

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

5.6.2 Avoided Costs

................................ ................................ ................................ ................................ .. 39

5.7 Achievable Potential

................................ ................................ ................................ ................................ .. 39



### 6 R ESIDENTIAL 

### E LECTRIC AND 

### N ATURAL 

### G AS 

### E NERGY 

### E FFICIENCY 

### P OTENTIAL



### E STIMA

TES



### ................................ ................................ ................................ ....................... 41

6.1 Residential Electric Potential

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

6.1.1 Energy Efficiency Measures Examined

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

6.1.2 Overview of Residential Electric Energy Efficiency Potential

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

6.1.3 Achievable Potential Savings in the Residential Sector

................................ ................................ ...... 45

6.1.4 Residential Savings Summary

................................ ................................ ................................ .......... 51

6.2 Residential Natural Gas Potential

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

6.2.1 Energy Effic

iency Measures Examined

................................ ................................ ............................. 53

6.2.2 Overview of Residential Natural Gas Energy Efficiency Potential

................................ ..................... 53

6.2.3 Achievable Potential S avings in the Residential Sector

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

6.2.4 Residential Savings Summary

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

6.3 Achievable Potential Benefits & Costs

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



### 7 N ON



### - R ESIDENTIAL 

### E LECTRIC 

### A ND 

### N ATURAL 

### G AS 

### E NERGY 

### E FFICIENCY 

### P OTENTIAL



### E STIMATES



### ................................ ................................ ................................ ....................... 64

7.1 Non

- Residential Electric

................................ ................................ ................................ ........................... 64

7.1.1 Electric Energy Efficiency Measures Examined

................................ ................................ ................ 64

7.1.2 Technical and Economic Potential Electric Savings

................................ ................................ ........... 65

7.1.3 Achievable Potential Savings in the Non

- Residential Sector

................................ .............................. 69

7.1.4 Non

- Residential Savings Summary

................................ ................................ ................................ .. 74

7.2 Non

- Residential Natural Gas Potential

................................ ................................ ................................ .. 78

7.2.1 Energy Efficiency Measures Examined

................................ ................................ ............................. 78

7.2.2 Technical and Economic P otential Natural Gas Savings

................................ ................................ .. 79

7.2.3 Achievable Potential Savings in the Non

- Residential Sector

................................ .............................. 82

7.2.4 Non

- Residential Saving s Summary

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

7.3 Achievable Potential Benefits & Costs

................................ ................................ ................................ ... 89



### 8 D EMAND 

### R ESPONSE 

### P OTENTIAL 

### E STIMATES



### ................................ ................................ .. 91

8.1 Introduction to Demand Response

................................ ................................ ................................ ......... 91

8.2 General Benefits of Demand Response

................................ ................................ ................................ . 91

8.3 Demand Response Measures Examined

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

8.4 Demand Response Savings Summary

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

8.5 Achievable Potential Benefits & Costs

................................ ................................ ................................ . 101



### 9 S UMMARY OF 

### R ESULTS



### ................................ ................................ ................................ ... 102

9.1 Technical, Economic and Achievable Savings Potential

................................ ................................ ... 102

9.2 Recommendations

................................ ................................ ................................ ................................ .... 103D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page iii 

## A PPENDICES

A PPENDIX 

### 1: G ENERAL 

### M ODELING 

### A SSUMPTIONS



### A PPENDIX 

### 2: R ESIDENTIAL 

### A SSUMPTIONS



### A PPENDIX 

### 3: N ON



### - R ESIDENTIAL 

### A SSUMPTIONSD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page iv 

## L IST OF 

## F IGURES

Figure 1

- 1: Types of Energy Efficiency Potential

................................ ................................ ................................ .............................. 3

Figure 4

- 1: Map of Washington D.C.

................................ ................................ ................................ ................................ ................. 20

Fig ure 4

- 2: Breakdown of Natural Gas Consumption, Washington D.C., 2010

................................ ................................ ........ 24

Figure 5

- 1: Types of Energy Efficiency Potential

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

Figu re 5

- 2: Residential Sector Savings Methodology

- Bottom Up Approach

................................ ................................ ........... 34

Figure 5

- 3: Generic Example of a Supply Curve

................................ ................................ ................................ .............................. 36

Figure 6

- 1: Summary of Residential Electric Energy Efficiency Potential as a % of 2017 and 2022 Sales Forecasts

......... 43

Figure 6

- 2: Residential Sector 2022 Achievable Potential Savings for the Base Achieva ble Scenario, by End Use

............ 47

F i gu r e 6

- 3: Residential Base Achievable S a v i ngs i n 2022, by Housing Type, Low

- Income Designation and New

Construction Measures

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

Figure 6

- 4: Summary of Residential Energy Efficiency Potential as a % of 2017 and 2022 Sales Forecasts

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

F i gu r e 6

- 5 : Residential S ector 2022 A c h i ev a b l e P o t e ntial S avings f o r the Base Achievable Scenario, by E n d U s e

.............. 57

F i gu r e 6

- 6: Residential Base Achievable S a v i ngs i n 2022, by Housing Type, Low

- Income Designation and New

Construction Measures

................................ ................................ ................................ ................................ ............................... 58

Figure 7

- 1: Summary of Non

- Residential Energy Efficiency Potential as a % of Sales Forecasts

................................ .......... 66

Figure 7

- 2: Non

- Residential Sector 20 22 Base Case Achievable Potential Savings for by End Use

................................ ...... 71

Figure 7

- 3: Non

- Residential Base Case Savings in 2022 by Vintage

................................ ................................ ............................. 71

Figure 7

- 4: Summary of Non

- Residential Energy Efficiency Potential as a % Sales Forecasts

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

Figure 7

- 5: Non

- Residential Sector 2022 Base Case Achievable Potential Savings for by End Use

................................ ...... 83

Figure 7

- 6: Non

- Residential Base Case Achievable Savings in 2022 by Vintage

................................ ................................ ........ 84

Figure 8

- 1: Load Shifting and Peak Clipping Program s

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

F i gu r e 8

- 2: S umma r y of Demand Response P o tent i al as a % of 2017 and 2022 Summer Peak Demand F o r ec as ts

.......... 94

Figure 8

- 3: Reside ntial Sector 2022 Achievable Potential Savings for the Base Achievable Scenario, by Measure

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

Figure 8

- 4: Commercial Sector 2022 Achievable Potential Savings for the Base Achievable Scenario, by Measure

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



## L IST OF 

## E QUATIONS

Equation 5

- 1: Core Equation for Residential Sector Technical Potential

................................ ................................ .................... 35

Equation 5

- 2: Core Equation for Commercial Sector Technical Potential

................................ ................................ ................. 37D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page v 

## L IST OF TABLES

Table 1

- 1: Societal Cost Test Benefit

- Cost Ratios f or Achievable Potential Scenarios For 2013 to 2017 Time Period

....... 2

Table 1

- 2: Societal Cost Test Benefit

- Cost Ratios for Achievable Potential Scenarios For 2013 to 2022 Time Period

....... 3

Table 1

- 3: Summary of Technical, Economic and Achievable Electric Energy Savings for 2017

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

Table 1

- 4: Summary of Technical, Economic and A chievable Electric Energy Savings for 2022

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

Table 1

- 5: Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2017

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

Table 1

- 6: Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2022

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

Table 1

- 7: Achievable Potential Scenarios; Budgets and Acquisit ion Costs Per Unit of Energy Saved

– Electric Savings

. 7

Table 1

- 8: Achievable Potential Scenarios; Budgets and Acquisition Costs Per Unit of Energy Saved

– Natural Gas

Savings

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

Table 1

- 9: Demand Response A ch i ev a b l e S avings P o tent i al i n 2017

– Maximum, Base and Constrained Achievable

Scenarios

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

Table 1

- 10: Demand Resp onse A ch i ev a b l e S avings P o tent i al i n 2022

– Maximum, Base and Constrained Achievable

Scenarios

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

Table 3

- 1: Results of Recent Energy Efficiency Potential Studies in the Northeast and US

................................ ................... 16

Table 3

- 2: Societal Cost Test Benefit

- Cost Ratios for the Maximum Achievable Potential Scenario For 5

- Year and 10

- Year Implementation Periods

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

Table 3

- 3: Societal Cost Test Benefit

- Cost Ratios for the Base Achievable Scenario For 5

- Year, and 10

- Year

Implementation Periods

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

Table 3

- 4: Societal Cost Test Benefit

- Cost Ra tios for the Constrained Achievable Scenario For 5

- Year and 10

- Year

Implementation Periods

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

Table 4

- 1: Washington D.C. Housing Unit Characteristics

................................ ................................ ................................ ............ 20

Table 4

- 2: Historical Washington D.C. GWh Sales to Ultimate Customers by Customer Class (GWh)

– 2001 to 2010

.. 21

Table 4

- 3: Historical Number of Customers by Customer C lass

- 2001 to 2011

................................ ................................ ....... 21

Table 4

- 4: Historical DC Pepco System Peak Load by Season (MW)

– 2007 to 2012

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

Table 4

- 5: GWh Sales For ecast for Washington D.C. (Without Future DSM Impacts)

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

Table 4

- 6: Electric Customer Forecast for Washington D.C.

................................ ................................ ................................ ........ 23

Table 4

- 7 : Pepco Peak Load Forecast for Washington D.C. (Without Future DSM Impacts)

................................ ............... 23

Table 4

- 8: Historical Washington D.C. Trillion BTU Sales to Ultimate Customers by Customer Class (TBTU)

– 2001 to

2011

................................ ................................ ................................ ................................ ................................ ................................ 24

Table 4

- 9: Historical Number of DC Natural Gas Customers by Customer Class

– 2001 to 2011

................................ ....... 25

Table 4

- 10: Forecast of Na tural Gas Consumption by Customer Class 2013

- 2023 (Trillion BTU)

................................ ...... 26

Table 4

- 11: Forecast of Natural Gas Customers by Customer Class, 2013

- 2023 (Trillion BTU)

................................ ........... 26

Table 6

- 1: Mea s u r es a n d P r ogr a ms I n c l uded i n the Electric Residential S ector A n al y s i s

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

Table 6

- 2: Residential Sector Technical Potential Energy Savings by E nd Use

................................ ................................ ......... 44

Table 6

- 3 : Residential S ector Tech n i c a l P o tent i al Demand S avi n gs

................................ ................................ .............................. 44

Table 6

- 4: Residential Sector Economic Potential E nergy Savings by End Use

................................ ................................ ........ 45

Table 6

- 5 : Residential S ector Economic P o tent i al Demand S avi n gs

................................ ................................ ............................ 45

Table 6

- 6: Residential Maximum Ac hievable Energy Savings by End Use

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

Table 6

- 7: Residential Maximum Achievable Potential Demand Savings

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

Table 6

- 8: Residenti al Base Achievable Savings Potential Energy Savings by End Use

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

Table 6

- 9 : Residential Base A ch i ev a b l e P o tent i al Demand S avi n gs

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

Table 6

- 10 : Residential Constrained A ch i ev a b l e S avings P o tent i al Energy S avi n gs by End U s e

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

Table 6

- 11 : Residential Constrained A ch i ev a b l e P o tent i al Demand S avi n gs

................................ ................................ .................. 47

Table 6

- 12: Cumulative Annual Residential Energy Savings in the Maximum Achievable Potential Scenario, by End Use

for Washington D.C.

................................ ................................ ................................ ................................ ................................ .. 49

Table 6

- 1 3: Cumulative Annual Residential Energy Savings in the Base Achievable Potential Scenario, by End Use for

Washington D.C.

................................ ................................ ................................ ................................ ................................ ......... 49D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page vi Table 6

- 14 : Cumu l at

i ve A nn u al Residential E n e r gy S avings i n the Con strained Achievable P o ten t i al S ce n a r i o, by E n d U s e

f o r Washington D.C.

................................ ................................ ................................ ................................ ................................ .. 50

Table 6

- 15 : Breakdown of Residential Cumulative Annual Electric Savings Potential for Technical, Economic and

Achievab le Potential, by E n d U s e f o r Washington D.C.

................................ ................................ ................................ .... 51

Table 6

- 16 : Mea s u r es a n d P r ogr a ms I n c l uded i n the Gas Residential S ector A n al y s i s

................................ .............................. 53

Table 6

- 17: Residential Sector Technical Potential MMBtu Savings by End Use

................................ ................................ ...... 55

Table 6

- 18: Statewide Residential Sector Economic Potential MMBtu Savings by End Use

................................ .................. 55

Table 6

- 19 : Residential A ch i ev a b l e S avings P o tent i al i n 2017

– Maximum, Base and Constrained Achievable Scenarios

. 56

Table 6

- 20 : Residential A ch i ev a b l e S avings P o tent i al i n 2022

– Maximum, Base and Constrained Achievable Scenarios

. 57

Table 6

- 21 : Cumu l at

i ve A nn u al Residential E n e r gy S avings i n the Maximum A c h i ev a b l e P o ten t i al S ce n a r i o, by E n d U s e

f o r Washington D.C.

................................ ................................ ................................ ................................ ................................ .. 59

Table 6

- 22 : Cumu l at

i ve A nn u al Residential E n e r gy S avings i n the Base Achievable P o ten t i al S ce n a r i o, by E n d U s e f o r Washington D.C.

................................ ................................ ................................ ................................ ................................ ......... 59

Table 6

- 23 : Cumu l at

i ve A nn u al Residential E n e r gy S avings i n the Constrained Achievable P o ten t i al S ce n a r i o, by E n d U s e

f o r Washington D.C.

................................ ................................ ................................ ................................ ................................ .. 60

Table 6

- 24 : Br eakdown of Residential Cumulative Annual Gas Savings Potential for Technical, Economic and

Achievable Potential, by E n d U s e f o r Washington D.C.

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

Table 6

- 25 : 5

- Y e a r SCT R a t i os f o r A ch i e va bl e P o tent

i al S ce n a r i o s

– Residential S ector On l y

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

Table 6

- 26 : 10

- Y e a r SCT R a t i os f o r A ch i e va bl e P o tent

i al S ce n a r i o s

– Residential S ector On l y

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

Ta bl e 7

- 1 : Types of Mea s u r es I n c l uded i n the Non

- Residential S ector A n al y s i s

................................ ................................ ........ 64

Table 7

- 2: Institutional Savings as a Percentage of Non

- Residential Sales

................................ ................................ .................. 66

Table 7

- 3: Non

- Residential Sector Technical Potential Savings By End Use

................................ ................................ ............. 67

Table 7

- 4 : Non

- Residential S ector Tech n i c a l P o tent i al Demand S avi n gs

................................ ................................ ..................... 67

Table 7

- 5: Non

- Residential Sector Economic Potential Savings By End Use

................................ ................................ ............ 68

Table 7

- 6 : Non

- Residential S ector Economic P o tent i al Demand S avi n gs

................................ ................................ ................... 68

Table 7

- 7: Non

- Residential Maximum Achievable Energy Savings by End Use

................................ ................................ ....... 69

Table 7

- 8: Non

- Residential Maximum Achievable Demand Savings

................................ ................................ ........................... 69

Table 7

- 9: Non

- Residential Base Achievable Energy Savings by End Use

................................ ................................ ................. 69

Table 7

- 10: Non

- Residential Base Achievable Demand Savings

................................ ................................ ................................ ... 70

Table 7

- 11: Non

- Residential Constrained Achievable Energy Savings by End Use

................................ ................................ .. 70

Table 7

- 12: N on

- Residential Constrained Achievable Demand Savings

................................ ................................ ..................... 70

Table 7

- 13: Cumulative Annual Non

- Residential Energy Savings in Max Achievable Potential Scenario by End Use for

Washington D.C.

................................ ................................ ................................ ................................ ................................ ......... 72

Table 7

- 14: Cumulative Annual Non

- Residential Energy Savings in Base Achievable Potential Scenario by End Use for

Washington D.C.

................................ ................................ ................................ ................................ ................................ ......... 72

Table 7

- 15: Cumulative Annual Non

- Residential Energy Savings in Constrained Achievable Potential Scenario by End

Use for Washington D.C.

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

Table 7

- 16 Electric Potential by End

- Use and Measur e

................................ ................................ ................................ ................. 74

Table 7

- 17: Measures and Programs Included in the Non

- Residential Sector Analysis

................................ ............................ 78

Table 7

- 18: Institutional Savings as a Percentage of Non

- Residential Sales

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

Table 7

- 19: Non

- Residential Sector Technical Potential MMBtu Savings By End Use

................................ ............................ 81

Table 7

- 20: Non

- Residential Sector Economic Potential MMBtu Savings By End Use

................................ .......................... 81

Table 7

- 21: Non

- Residential Achievable Savings Potential in 2017

................................ ................................ ............................. 82

Table 7

- 22: Non

- Residential Achievable Savings Potential in 2022

................................ ................................ ............................. 83

Table 7

- 23: Cumulative Annual Non

- Residential Energy Savings in Max Achievable Potential Scenario by End Us e for

Washington D.C.

................................ ................................ ................................ ................................ ................................ ......... 85

Table 7

- 24: Cumulative Annual Non

- Residential Energy Savings in Base Achievable Potential Scenario by End Use for

Washington D.C.

................................ ................................ ................................ ................................ ................................ ......... 85D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page vii Table 7

- 25: Cumulative Annual Non

- Residential Energy Savings in Constrained Achievable Potential Scenario by End

Use for Washington D.C.

................................ ................................ ................................ ................................ .......................... 86

Table 7

- 26: Natural Ga s Potential by End

- Use and Measure

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

Table 7

- 27: 5

- Year SCT Ratios for Achievable Potential Scenarios

– Non

- Residential Sector Only

................................ ..... 90

Table 7

- 28: 10

- Year SCT Ratios for Achievable Potential Scenarios

– Non

- Residential Sector Only

................................ .... 90

Table 8

- 1: Tech n i c a l P o tent i al MW S avi n gs by Sector

................................ ................................ ................................ .................... 94

Table 8

- 2: Residential Technical Potential MW Savings by Measure

................................ ................................ ........................... 95

Table 8

- 3: Commercial Technical Potential MW Savings by Measure

................................ ................................ ......................... 95

Table 8

- 4: Economic P o tent i al MW S avi n gs by Sector

................................ ................................ ................................ ................... 95

Table 8

- 5: Residential Economic P o tent i al MW S avi n gs by Measure

................................ ................................ ........................... 96

Table 8

- 6: Commercial Economic P o tent i al MW S avi n gs by Measure

................................ ................................ ......................... 96

Table 8

- 7: Demand Response A ch i ev a b l e S avings P o tent i al i n 2017

– Maximum, Base and Constrain ed Achievable

Scenarios

................................ ................................ ................................ ................................ ................................ ....................... 96

Table 8

- 8: Residential Achievable Potential MW Savings by Measure in 2017

– Maximum, Base and Constrained

Achievable Scenarios

................................ ................................ ................................ ................................ ................................ .. 97

Table 8

- 9: Commercial Achievable Potential MW Savings by Measure in 2017

– Maximum, Base and Constrained

Achievable Scenarios

................................ ................................ ................................ ................................ ................................ .. 97

Table 8

- 10 : Demand Response A ch i ev a b l e S avings P o tent i al i n 2022

– Maximum, Base and Constrained Achievable

Scenarios

................................ ................................ ................................ ................................ ................................ ....................... 97

Table 8

- 11: Residential Achievable Potential MW Savings by Measure in 2022

– Maximum, Base and Constraine d

Achievable Scenarios

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

Table 8

- 12: Commercial Achievable Potential MW Savings by Measure in 2022

– Maximum, Base and Constrained

Achievable Scenarios

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

Table 8

- 13 : Cumu l at

i ve A nn u al Demand Response S avings i n the Maximum A c h i ev a b l e P o ten t i al S ce n a r i o, by Measure

f o r Washington D.C.

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

Table 8

- 14: Cumu l at

i ve A nn u al Demand Response S avings i n the Base A c h i ev a b l e P o ten t i al S ce n a r i o, by Measure f o r Washington D.C.

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

Table 8

- 15: Cumulative Annual Demand Response Savings in the Constrained Achievable Poten tial Scenario, by

Measure for Washington D.C.

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

Table 8

- 16: 5

- Year SCT Ratios for Achievable Potential Scenarios

– Demand Response Only

................................ ........... 101

Table 8

- 17: 10

- Year SCT Ratios for Achievable Potential Scenarios

– Demand Response Only

................................ .......... 101

Table 9

- 1: Summary of Technical, Economic and Achievable Electric Energy Savings for 2 017

................................ ........ 102

Table 9

- 2: Summary of Technical, Economic and Achievable Electric Energy Savings for 2022

................................ ........ 102

Table 9

- 3: Summary of Tech nical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2017

............. 103

Table 9

- 4: Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2022

............. 103

Table 9

- 5: Summary of Technical, Economic and Achievable Demand Response Savings for 2017

................................ .. 103

Table 9

- 6: Summary of Technical, Eco nomic and Achievable Demand Response Savings for 2022

................................ .. 103

Table 9

- 7: Top 10 Residential Electric Savings Measures

................................ ................................ ................................ ............. 104

Table 9

- 8: Top 10 Residential Gas Savings Measures

................................ ................................ ................................ ................... 104

Table 9

- 9: Top 10 Non

- Residential Electric Savings Measures

................................ ................................ ................................ ... 104

Table 9

- 10: Top 10 Non

- Residential Gas Savings Measures

................................ ................................ ................................ ....... 105D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 1 

# 1 E X E C U T I V E 

# S U M M A R Y

1.1 B ACKGROUND



### This draft energy efficiency potential study is an essential component of the Comprehensive Energy

Comprehensive Energy Plan (CEP)

. The District Depart ment of the Environment (DDOE) completed

this 2013 study of energy efficiency potential in the District to assist policy makers with developing the

CEP , to identify new energy efficiency initiatives for the District and to refine existing program offerings

and portfolios. An energy efficiency potential study provides a roadmap for policy makers and identifies

the energy efficiency measures having the greatest potential savings and the measures that are the most

cost effective. In addition to technical and e conomic potential estimates, the development of achievable

potential estimates for a range of feasible energy efficiency measures is useful for program planning and

modification purposes. Unlike achievable potential estimates, technical and economic potent ial estimates

do not include customer acceptance considerations of energy efficiency measures, which is often among

the most important factors when estimating the likely customer response to new programs. For this

study, the consultants ( GDS Associates , In c. ) produced the following estimates of energy efficiency

potential:

 

### Technical potential

 

### Economic potential

 

### Achievable potential

Definitions of the types of energy efficiency potential are provided below.

1. 

### T ECHNICAL POTENTIAL 

### is the theoretical maximum amount of energy use that could be

displaced by efficiency, disregarding all non

- engineering constraints such as cost

- effectiveness

and the willingness of end

- users to adopt the efficiency measures. It is often estimated as a

“snapshot” in time assuming i mmediate implementation of all technologically feasible energy

saving measures, with additional efficiency opportunities assumed as they arise from activities

such as new construction.

2. 

### E CONOMIC POTENTIAL 

### refers to the subset of the technical potential that is economically

cost

- effective as compared to conventional supply

- side energy resources. Both technical and

economic potential are theoretical numbers that assume immediate implementation of efficiency

measures, with no regard for the gradual “ramping up” process of real

- life programs. In addition,

they ignore market barriers to ensuring actual implementation of efficiency. Finally, they only

consider the costs of efficiency measures themselves, ignoring any programmatic costs (e.g.,

marketing, analysi s, administration) that would be necessary to capture them.

3. 

### A CHIEVABLE POTENTIAL



### – Achievable potential is the amount of energy use that efficiency

can realistically be expected to displace assuming the different market penetration scenarios. An

aggres sive scenario, for example, could, provide program participants with payments for the

entire incremental cost of more energy efficient equipment). This is often referred to as

“maximum achievable potential”. Achievable potential takes into account real

- wor ld barriers to

convincing end

- users to adopt efficiency measures, the non

- measure costs of delivering

programs (for administration, marketing, tracking systems, monitoring and evaluation, etc.), and

the capability of programs and administrators to ramp up program activity over time. 1



### The purpose of this energy efficiency potential study is to provide a foundation for the CEP and to

determine the remaining opportunities for cost effective electricity and natural gas energy efficiency

savings for the geogra phic region of the District of Columbia. This detailed report presents results of the

1 These definitions are from the November 2007 National Action Plan for Energy Eff iciency “Guide for Conducting Energy

Efficiency Potential Studies”D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 2 

### technical, economic, and achievable potential for electric and natural gas efficiency measures in the

District for two time periods:

 

### The five

- year period from January 1, 2013 through December 31, 2017

 

### The ten

- year period from January 1, 2013 through December 31, 2022

All results were developed using customized residential and non

- residential, or commercial/industrial

(C&I), sector

- level potential assessment analytic mod els and District

- specific cost effectiveness criteria

including the most recent District

- specific avoided cost projections for electricity and natural gas. To

help inform these energy efficiency potential models, up

- to

- date energy efficiency measure data w ere primarily obtained from the following recent studies and reports:

1. Mid

- Atlantic Technical Reference Manual 2.0, July 2011

2. District of Columbia Sustainable Efficiency Utility Technical Reference Manual

3. Northeast Energy Efficiency Partnership (NEEP) Incr emental Cost Study Report, 2011

4. Appliance saturation study conducted by Pepco in 2000

5. 2009 EIA Residential Energy Consumption Survey (RECS)

6. 2007 American Housing Survey (AHS)

7. 2003 EIA Commercial Building Energy Consumption Survey (CBECS)

The above data so urces provided valuable information regarding the current saturation, costs, savings

and useful lives of electric and natural gas energy efficiency measures considered in this study.

The results of this study provide detailed information on energy efficie ncy measures that are the most

cost effective and have the greatest potential electric and natural gas savings for the District of Columbia.

The data used for this report were the best available at the time this analysis was developed. As building

and appl iance codes and energy efficiency standards change, and as energy prices fluctuate, additional

opportunities for energy efficiency may occur while current practices may become outdated.



### 1.2 C OST 

### E FFECTIVENESS 

### F INDINGS



### The Societal Cost Test (SCT, or SC test ) is the cost effectiveness screening test used in this study to

determine whether a measure is cost effective. The SCT is also used by the District of Columbia

Sustainable Energy Utility ( DCSEU ) to determine program and measure cost effectiveness. This en ergy efficiency and demand response potential study concludes that significant cost effective electric and

natural gas energy efficiency potential remains in the District. Table s 1

- 1 and 1

- 2 show the preliminary

SCT present value benefits, costs and benefi t

- cost ratios for the Achievable Potential scenarios examined

in this study.

Table 1

- 1: Societal Cost Test Benefit

- Cost Ratios for Achievable Potential Scenario s For 2013 to 2017 Time

Period

Societal Test Benefit Cost Ratios for 2013 to 2017 Time Period

Achievable Potential Scenarios SCT $ Benefits SCT $ Costs SCT Benefit/Cost

Ratio

Max Achievable Potential $6,605,144,984 $1,440,446,220 4.59

Base Achievable Potential $3,937,727,800 $609,600,088 6.46

Constrained Achievable Potential $3,258,746,270 $47 6,652,583 6.84D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 3 Table 1

- 2 : Societal Cost Test Benefit

- Cost Ratios for Achievable Potential Scenario s For 2013 to 2022 Time

Period

Societal Test Benefit Cost Ratios for 2013 to 2022 Time Period

Achievable Potential Scenarios SCT $ Benefits SCT $ Costs S CT Benefit/Cost

Ratio

Max Achievable Potential $12,670,482,719 $2,541,727,303 4.98

Base Achievable Potential $7,745,717,753 $1,115,231,954 6.95

Constrained Achievable Potential $6,380,955,238 $868,574,226 7.35



### In addition, the consultants calculate d a SCT ratio for each individual energy efficiency measure and each

demand response measure considered in this study. Only measures that had a SCT ratio greater than or

equal to 1.0 were retained in the economic and achievable potential savings estimates.



### 1.3 S TUDY 

### S COPE



### The study examines the potential to reduce electric consumption and peak demand and natural gas

consumption through the implementation of energy efficiency technologies and practices in residential,

commercial, and industrial facilities in the D istrict of Columbia . This study assesses electric and natural

gas energy efficiency potential in the District of Columbia over ten years, from 2 013 through 2022

.

The study had the following main objectives:

 

### Evaluate the electric and natural gas energy eff iciency technical, economic and achievable

potential savings in the District of Columbia ;

 

### Calculate the Societal Cost Test (“ SCT ”) benefit

- cost ratio for the achievable potential savings

scenarios.

As noted above, t he scope of this study distinguishes am ong three types of energy efficiency potential;

(1) technical, (2) economic, and (3) achievable potential. The definitions used in this study for energy

efficiency potential estimates were obtained directly from a 2007 National Action Plan for Energy

Effic iency (NAPEE) report

. Figure 1

- 1 below provides a graphical representation of the relationship of

the various definitions of energy efficiency potential.

Figure 1

- 1: Types of Energy Efficiency Potential 2

2 Reproduced from “Guide to Resource Planning with Energy Efficiency” November 2007. US EPA. Figure 2

- 1.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 4 

### Limitations to the scope of study: As with any a ssessment of energy efficiency potential, this study necessarily

builds on a large number of assumptions and data sources, including the following:

 

### Energy efficiency measure lives, measure savings and measure costs

 

### The discount rate for determining the ne t present value of future savings

 

### Projected penetration rates for energy efficiency measures

 

### Projections of District

- specific electric and natural gas avoided costs

 

### Future changes to current energy efficiency codes and standards for buildings and equipment

While the consult ants ha ve sought to use the best and most current available data, there are many

assumptions where there may be reasonable alternative assumptions that would yield somewhat different

results. Furthermore, while the lists of energy effici ency measures examined in this study represent most

commercially available measures, these measure lists are not exhaustive. Finally there was no attempt to

place a dollar value on some difficult to quantify benefits arising from installation of some measu res, such as increased comfort or increased safety, which may in turn support some personal choices to

implement particular measures that may otherwise not be cost

- effective or only marginally so. Instead,

the consultants placed a 30% adder to the benefits of measures when performing the measure

- level cost

effectiveness screening.



### 1.4 R EPORT 

### O RGANIZATION



### The remainder of this report is organized in the following nine sections as follows:

Section 1: Executive Summary provides an overview of initial findings fr om the potential study and

outlines the remainder of the report

Section 2: Glossary of Terms defines key terminology used in the report.

Section 3: Introduction highlights the purpose of this study and the importance of energy efficiency.

Section 4: Charac

terization of

Washington DC Service Area provides an overview of the District

and a brief discussion of the historical and forecasted electric and natural gas energy sales by sector as

well as electric peak demand.

Section 5: Potential Study Methodology de tails the approach used to develop the estimates of

technical, economic and achievable potential for electric and natural gas energy efficiency savings.

Section 6: Residential Electric and Natural Gas Energy Efficiency Potential Estimates ( 2013

-

2022 ) provi des a breakdown of the technical, economic, and achievable potential in the residential

sector.

Section 7: Non

- Residential Electric and Natural Gas Energy Efficiency Potential Estimates

( 2013

- 2022 )

– provides a breakdown of the technical, economic, and ac hievable savings potential in the

C&I sectors.

Section 8 : Demand Response Potential Estimates

Section 9 : Summary of Results presents the final discussion regarding potential for energy efficiency

and demand response savings through 2023.



### 1.5 S UMMARY OF 

### R ESUL TS



### This study examined 775 energy efficiency measures in the residential, commercial and industrial sectors

combined

. 554 total measures were included in the residential sector energy efficiency potential analysis.

There are 458 electric measures and 245 n atural gas measures, with some of these measures savings both

fuels. 221 total measures were included in the non

- residential sector energy efficiency potential analysis

. There are 153 electric measures and 68 gas measures. Of these 775 measures, 673 were found to be cost

effective according to the SCT

.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 5 

### Tables 1

- 3 and 1

- 4 below show that cost effective electric energy efficiency resources can play a

significantly expanded role in the District’s energy resource mix over the next five and ten years. For th e

District overall , the maximum achievable cost effective potential for electricity savings in 20 22 is 29.4 %

of forecast kWh sales for 2022. Tables 1

- 3 and 1

- 4 present the electric energy efficiency savings for

economic potential and achievable potential f or 2017 and 2022.

Table 1

- 3 : Summary of Technical, Economic and Achievable Electric Energy Savings for 2017

Summary of Technical, Economic and Achievable Electric Energy Efficiency Savings for 2017

Energy Demand

Energy

(MWh) % of 2017

Sales Winter

MW % of 2017

Winter Peak Summer

MW % of 2017

Summer

Peak

ALL SECTORS COMBINED

Technical Potential 3,544,474 28.8% 789 41.7% 668 25.6%

Economic Potential 3,413,829 27.7% 771 40.7% 643 24.7%

Max Achievable Potential 2,212,680 18.0% 486 25.7% 403 15.4%

Base Achievable Potential 1,560,081 12.7% 313 16.5% 289 11.1%

Constrained Achievable

Potential 1,342,525 10.9% 244 12.9% 215 8.2%

RESIDENTIAL SECTOR

Technical Potential 998,677 45.0% 339 71.4% 245 35.8%

Economic Potential 974,647 43.9% 339 71.5% 238 34.8%

Max Achievable Potential 478,083 21.6% 179 37.8% 115 16.8%

Base Achievable Potential 327,693 14.8% 130 27.3% 76 11.0%

Constrained Achievable

Potential 258,463 11.7% 111 23.4% 64 9.3%

NON

- RESIDENTIAL SECTOR

Technical Potential 2,545,797 25.2% 451 31.8% 423 22.0%

Economic Potential 2,439,182 24.2% 432 30.4% 405 21.0%

Max Achievable Potential 1,734,597 17.2% 307 21.7% 288 15.0%

Base Achievable Potential 1,232,388 12.2% 183 12.9% 213 11.1%

Constrained Achievable

Potential 1,084,062 10.7% 133 9.4% 151 7 .8%

Table 1

- 4 : Summary of Technical, Economic and Achievable Electric Energy Savings for 2022

Summary of Technical, Economic and Achievable Electric Energy Efficiency Savings for 2022

Energy Demand

Energy

(MWh) % of 2022

Sales Winter

MW % of 2022

Win ter Peak Summer

MW % of 2022

Summer

Peak

ALL SECTORS COMBINED

Technical Potential 5,759,943 44.7% 1,216 61.3% 1,051 38.4%

Economic Potential 5,537,521 43.0% 1,181 59.5% 1,011 36.9%

Max Achievable Potential 3,781,942 29.4% 836 42.1% 703 25.7%

Base Achi evable Potential 2,715,397 21.1% 548 27.6% 511 18.6%

Constrained Achievable

Potential 2,340,833 18.2% 495 25.0% 438 16.0%

RESIDENTIAL SECTOR

Technical Potential 1,064,393 44.8% 369 72.7% 264 36.0%

Economic Potential 1,038,615 43.7% 369 72.8% 256 34.9%

Max Achievable Potential 663,229 27.9% 273 53.9% 180 24.6%

Base Achievable Potential 442,342 18.6% 202 39.8% 120 16.3%

Constrained Achievable 356,529 15.0% 177 34.9% 102 14.0%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 6 Summary of Technical, Economic and Achievable Electric Energy Efficiency Savings for 2022

Potential

NON

- RESIDENTIAL SECTOR

Technical Potential 4,695,550 44.7% 848 57 .4% 787 39.3%

Economic Potential 4,498,906 42.9% 812 55.0% 754 37.6%

Max Achievable Potential 3,118,713 29.7% 563 38.1% 523 26.1%

Base Achievable Potential 2,273,055 21.7% 346 23.4% 391 19.5%

Constrained Achievable

Potential 1,984,304 18.9% 318 21.5% 3 36 16.8%



### Tables 1

- 5 and 1

- 6 present the study results for natural gas savings potential. For the District overall, the

maximum achievabl e cost effective potential for gas savings in 2022 is 24 .1 % of forecast MMBtu sales

for 2022.

Table 1

- 5: Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2017

Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2017

Energy

Energy (MMBtu) % of 2017 Sales

ALL SECTORS COMBINED

Technical Potent ial 7,182,714 23.4%

Economic Potential 6,400,319 20.8%

Max Achievable Potential 3,845,186 12.5%

Base Achievable Potential 1,974,923 6.4%

Constrained Achievable Potential 1,645,886 5.4%

RESIDENTIAL SECTOR

Technical Potential 3,538,697 28.5%

Economic Potential 3,125,887 25.2%

Max Achievable Potential 1,090,567 8.8%

Base Achievable Potential 660,596 5.3%

Constrained Achievable Potential 444,561 3.6%

NON

- RESIDENTIAL SECTOR

Technical Potential 3,644,017 19.9%

Economic Potential 3,274,432 17.9%

Max Achievable Potential 2,754,619 15.0%

Base Achievable Potential 1,314,327 7.2%

Constrained Achievable Potential 1,201,325 6.5%

Table 1

- 6 : Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2022

Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2022

Energy

Energy (MMBtu) % of 2022 Sales

ALL SECTORS COMBINED

Technical Potential 10,991,828 34.5%

Economic Potential 9,817,767 30.8%

Max Achievable Potential 7,681,736 24.1%

Base Achievable Potential 3,998,724 12.5%

Constrained Achievable Potential 3,308,069 10.4%

RESIDENTIAL SECTOR

Technical Potential 3,703,794 29.8%

Economic Potential 3,268,903 26.3%

Max Achievable Potential 2,172,498 17.5%

Base Achievable Potential 1,370, 070 11.0%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 7 Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2022

Constrained Achievable Potential 905,419 7.3%

NON

- RESIDENTIAL SECTOR

Technical Potential 7,288,034 37.5%

Economic Potential 6,548,864 33.7%

Max Achievable Potential 5,509,238 28.3%

Base Achievable Potential 2,628,654 13.5%

Constrained Achi evable Potential 2,402,651 12.4%



### The five

- year and ten

- year budgets and acquisition costs for the achievable potential scenarios for electric

and natural gas energy efficiency savings are shown in Table 1

- 7 and 1

- 8.

Table 1

- 7 : Achievab le Potential Scenario s; Budgets and Acquisition Costs Per Unit of Energy Saved

– Electric

Savings

5

- year and 10

- year Acquisition Costs for Electric Achievable Potential

ALL SECTORS COMBINED 5

- Year EE

Budget 10

- Year EE

Budget Acquisition

Cost Per First

Year kWh

Saved

- 5 years Acquisition

Cost Per First

Year kWh

Saved

- 10

years

Max Achievable $1,137,808,982 $2,170,714,809 $0.49 $0.51

Base Achievable $327,791,519 $663,741,337 $0.20 $0.22

Constrained Achievable $202,397,288 $403,523,424 $0.14 $0.15

Table 1

- 8 : Achievable Potential Scenario s; Budgets and Acquisition Costs Per Unit of Energy Saved

– Natural

Gas Savings

5

- year and 10

- year Acquisition Costs for Gas Achievable Potential

ALL SECTORS COMBINED 5

- Year EE

Budget 10

- Year EE

Budget Acquisition

Cost Per First

Year MMBtu

Saved

- 5 years Acquisition

Cost Per First

Year MMBtu

Saved

- 10

years

Max Achievable $686,403,906 $1,384,546,295 $164.71 $165.59

Base Achievable $168,437,071 $346,143,666 $76.88 $76.41

Constr ained Achievable $129,319,185 $266,832,723 $69.85 $69.61



### The consult ants also calculated the demand response potential for the DC metro area. Tables 1

- 9 and 1

-

10 present the demand response achievable potential results. The Max Achievable potential fo r demand

response savings is 6.4% of forecasted summer peak in 2017 and 12.5% of forecasted summer peak in

2022

.

Table 1

- 9 : Demand Response A ch i ev a b l e S avings P o tent i al i n 2017

– Maximum, Base and Constrained

Achievable Scenarios

Summary of Achievable Dem and Response Potential

5

- year Maximum

Achievable Base

Achievable Constrained

Achievable

Total MW Savings 167.8 86.5 40.7

% of Forecast Summer Peak 6.4% 3.3% 1.6%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 8 Table 1

- 10 : Demand Response A ch i ev a b l e S avings P o tent i al i n 2022

– Maximum, Base and Constrained

Achievable Scenarios

Summary of Achievable Demand Response Potential

10

- year Maximum

Achievable Base

Achievable Constrained

Achievable

Total MW Savings 343.4 177.3 83.1

% of Forecast Summer Peak 12.5% 6.5% 3.0%



### 1.6 E NERGY 

### E FFICIENCY 

### P OTENTIAL 

### S AVINGS 

### D ETAIL



### Note that Section 6 of this report (Residential ) and Section 7 (

Non

- Residential) include additional detail

about the electric and natural gas energy efficiency savings potential in the District by 2022

. Section 8 of

the report include s addi tional detail about the demand response savings potential

.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 9 

# 2 G L O S S A R

Y O F 

# T E R M S 3

The following list defines many of the key energy efficiency terms used throughout this energy efficiency

potential study.

Achievable Potential: The November 2007 National Ac tion Plan for Energy Efficiency “Guide for

Conducting Energy Efficiency Potential Studies” defines achievable potential as the amount of energy

use that energy efficiency can realistically be expected to displace assuming the most aggressive program

scenar io possible ( e.g ., providing end

- users with payments for the entire incremental cost of more

efficient equipment). This is often referred to as maximum achievable potential. Achievable potential

takes into account real

- world barriers to convincing end

- user s to adopt efficiency measures, the non

measure costs of delivering programs (for administration, marketing, tracking systems, monitoring and

evaluation, etc.), and the capability of programs and administrators to ramp up program activity over

time.

Appli cability Factor: The fraction of the applicable dwelling units or businesses that is technically

feasible for conversion to the efficient technology from an engineering perspective (e.g., it may not be

possible to install CFLs in all light sockets in a hom e because the CFLs may not fit in every socket in a

home).

Avoided Costs: For purposes of this report, electric avoided costs are defined as the generation,

transmission and distribution costs that can be avoided in the future if the consumption of electr icity can

be reduced with energy efficiency or demand response programs. For a natural gas utility, the avoided

costs include the cost of the natural gas commodity and any other natural gas infrastructure costs that

can be reduced with energy efficiency pr ograms.

Base Achievable Potential: An achievable potential scenario which assumes incentives intended to

represent the current incentive levels offered by the DCSEU.

Base Case Equipment End

- Use Intensity: The electricity or natural gas used per custome r per year by each base

- case technology in each market segment. This is the consumption of the electric or natural

gas energy using equipment that the efficient technology replaces or affects. For example, if the efficient

measure is a high efficiency lig ht bulb (CFL), the base end

- use intensity would be the annual kWh use

per bulb per household associated with an incandescent or halogen light bulb that provides equivalent

lumens to the CFL.

Base Case Factor: The fraction of the market that is applicabl e for the efficient technology in a given

market segment. For example, for the residential electric clothes washer measure, this would be the

fraction of all residential customers that have an electric clothes washer in their household.

Capital Recovery Rate (CRR): The return of invested capital expressed as an annual rate; often applied

in a physical sense to wasting assets with a finite economic life. 4



### Coincidence Factor: The fraction of connected load expected to be “on” and using electricity

coincide nt with the system peak period.

Constrained Achievable : An achievable potential scenario which assumes incentives intended to

represent half of the current incentive levels offered by the DCSEU.

3 Potential definitions taken from National Action Plan for Energy Efficiency (2007) . “Guide for Conducting Energy

Efficiency Potential Studies.” Prepared by Philip Mosenthal and Jeffrey Loiter, Optimal Energy, Inc.

4 Accuval. http://www.accuval.net/insights/glossary/D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 10 

### Cost

- Effectiveness: A measure of the relevant economic ef fects resulting from the implementation of

an energy efficiency measure or program. If the benefits are greater than the costs, the measure is said to

be cost

- effective.

Cumulative Annual: Refers to the overall annual savings occurring in a given year fro m both new

participants and annual savings continuing to result from past participation with energy efficiency

measures that are still in place. Cumulative annual does not always equal the sum of all prior year

incremental values as some energy efficiency measures have relatively short lives and, as a result, their

savings drop off over time.

Commercial Sector: Comprised of non

- manufacturing premises typically used to sell a product or

provide a service, where electricity is consumed primarily for lighting , space cooling and heating, office

equipment, refrigeration and other end uses. Business types are included in Section 5

– methodology.

Demand Response: Refers to demand resources involving dynamic hourly load response to market

conditions, such as curt ailment or load control programs.

Early Replacement: Refers to an energy efficiency measure or efficiency program that seeks to

encourage the replacement of functional equipment before the end of its operating life with higher

efficiency units.

Economic Potential: The November 2007 National Action Plan for Energy Efficiency “Guide for

Conducting Energy Efficiency Potential Studies” refers to the subset of the technical potential that is

economically cost

- effective as compared to conventional supply

- side energy resources as economic

potential. Both technical and economic potential are theoretical numbers that assume immediate

implementation of efficiency measures, with no regard for the gradual “ramping up” process of real

- life

programs. In addition, they ignore market barriers to ensuring actual implementation of efficiency.

Finally, they only consider the costs of efficiency measures themselves, ignoring any programmatic costs

(e.g., marketing, analysis, administration) that would be necessary to capture them

.

End

- Use: A category of equipment or service that consumes energy ( e.g ., lighting, refrigeration, heating,

process heat, cooling).

Energy Efficiency: Using less energy to provide the same or an improved level of service to the energy

consumer in a n economically efficient way. Sometimes “conservation” is used as a synonym, but that

term is usually taken to mean using less of a resource even if this results in a lower service level ( e.g

., setting a thermostat lower or reducing lighting levels).

Ene rgy Use Intensity (EUI): A unit of measurement that describes a building’s energy use. EUI

represents the energy consumed by a building relative to its size. 5



### Free Driver: Individuals or businesses that adopt an energy efficient product or service because of an

energy efficiency program, but are difficult to identify either because they do not receive an incentive or

are not aware of the program.

Free Rider: Participants in an energy efficiency program who would have adopted an energy efficiency

technolo gy or improvement in the absence of a program or financial incentive.

5 See http://www.energystar.gov/index.cfm?fuseaction=buildingcontest.e uiD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 11 

### Gross Savings: Gross energy (or demand) savings are the change in energy consumption or demand

that results directly from program

- promoted actions (e.g., installing energy

- efficient lig hting) taken by

program participants regardless of the extent or nature of program influence on their actions.

Incentive Costs: A rebate or some form of payment used to encourage people to implement a given

demand

- side management (DSM) technology. The i ncentive is calculated as the amount of the

technology costs that must be paid by the utility or program administrator for the participant test ratio to

equal one and achieve the desired benefit/cost ratio to drive the market. 6



### Incremental: Savings or cos ts in a given year associated only with new installations of energy efficiency

or demand response measures happening in that specific year.

Industrial Sector: Comprised of manufacturing premises typically used for producing and processing

goods, where ele ctricity is consumed primarily for operating motors, process cooling and heating, and

space heating, ventilation, and air conditioning (HVAC). Business types are included in section 5

– methodology.

Maximum (or Max) Achievable : An achievable potential sce nario which assumes incentives for

program participants are equal to 100% of measure incremental costs.

Measure: Any action taken to increase energy efficiency, whether through changes in equipment,

changes to a building shell, implementation of control strategies, or changes in consumer behavior.

Examples are higher

- efficiency central air conditioners, occupancy sensor control of lighting, and retro

commissioning. In some cases, bundles of technologies or practices may be modeled as single measures.

For e xample, an ENERGY STAR® TM home package may be treated as a single measure.

MMBtu: A measure of power, used in this report to refer to consumption and savings associated with

natural gas consuming equipment. One British thermal unit (symbol Btu or someti mes BTU ) is a

traditional unit of energy equal to about 1055 joules . It is the amount of energy needed to heat one

pound of water by one degree Fahrenheit. MMBtu is defined as one million BTUs.

MW: A unit of electrical output, equal to one million watts or one thousand kilowatts. It is typically

used to refer to the output of a power plant.

MWh: One thousand kilowatt

- hours, or on e million watt

- hours. One MWh is equal to the use of

1,000,000 watts of power in one hour.

Net

- to

- Gross Ratio: A factor representing net program savings divided by gross program savings that is

applied to gross program impacts to convert them into net pro gram load impacts

Net Savings: Net energy or demand savings refer to the portion of gross savings that is attributable to

the program. This involves separating out the impacts that are a result of other influences, such as

consumer self

- motivation. Given the range of influences on consumers’ energy consumption, attributing

changes to one cause (i.e., a particular program) or another can be quite complex.

Non Incentive Cost: Costs incurred by the utility that do not include incentives paid to the customer

(i.e.: program administrative costs, program marketing costs, data tracking and reporting, program

evaluation, etc.)

6 Independent Energy Producers Association http://www.iepa.com/Glossary.aspD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 12 

### Nonparticipant Spillover

: 

### Savings from efficiency projects implemented by those who did not directly

participate in a program, but which nonetheless occurred due to the influence of the program.

Participant Cost: The cost to the participant to participate in an energy efficiency program.

Participant Spillover : Additional energy efficiency actions taken by program participants as a result of

program influence, but actions that go beyond those directly subsidized or required by the program. 7



### Portfolio: Either a collection of similar programs addressing the same market, technology, or

mechanisms; or the set of all programs conducted by one energy efficiency organization or utility.

Program: A mechanism for encouraging energy efficiency that may be funded by a variety of sources

and pursued by a wide range of approaches (typically includes multiple energy efficiency measures).

Program Poten tial: The November 2007 National Action Plan for Energy Efficiency ‘Guide for

Conducting Energy Efficiency Potential Studies” refers to the efficiency potential possible given specific

program funding levels and designs as program potential. Often, program potential studies are referred

to as “achievable” in contrast to “maximum achievable.” In effect, they estimate the achievable potential

from a given set of programs and funding. Program potential studies can consider scenarios ranging

from a single progr am to a full portfolio of programs. A typical potential study may report a range of

results based on different program funding levels.

Remaining Factor: The fraction of applicable units that have not yet been converted to the electric

energy efficiency me asure; that is, one minus the fraction of units that already have the energy efficiency

measure installed.

Replace

- on

- burnout : An energy efficiency measure is not implemented until the existing technology it

is replacing fails or burns out. An example wo uld be an energy efficient water heater being purchased

after the failure of the existing water heater at the end of its useful life.

Resource Acquisition Costs: The cost of energy savings associated with energy efficiency programs,

generally expressed in costs per first year saved MWh ($/MWh), kWh ($/kWh), or MMB tu ($/ MMB tu)

in this report.

Retrofit: Refers to an efficiency measure or efficiency program that seeks to encourage the replacement

of functional equipment before the end of its operating life w ith higher

- efficiency units (also called “early

retirement”) or the installation of additional controls, equipment, or materials in existing facilities for

purposes of reducing energy consumption (e.g., increased insulation, low flow devices, lighting

occu pancy controls, economizer ventilation systems).

Savings Factor: The percentage reduction in electricity consumption resulting from application of the

efficient technology. The savings factor is used in the formulas to calculate energy efficiency potenti al.

Technical Potential: The theoretical maximum amount of energy use that could be displaced by energy

efficiency, disregarding all non

- engineering constraints such as cost

- effectiveness and the willingness of

end

- users to adopt the energy efficiency mea sures. It is often estimated as a “snapshot” in time assuming

immediate implementation of all technologically feasible energy saving measures, with additional

efficiency opportunities assumed as they arise from activities such as new construction.

7 The definitions of participant and nonparticipant spillover were obtained from the National Action Plan for Energy

Efficiency Report titled “Model Energy Efficiency Program Im pact Evaluation Guide”, November 2007, page ES

- 4.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 13 

### Total Resource Cost Test : The TRC measures the net benefits of the energy efficiency program for a

region or service area as a whole. Costs included in the TRC are costs to purchase and install the energy

efficiency measure and overhead costs of running the ener gy efficiency program. The benefits included

are the avoided costs of energy and capacity.

Societal Cost Test: Measures the net benefits of the energy efficiency program for a region or service

area as a whole. Costs included in the SCT are costs to purc hase and install the energy efficiency measure

and overhead costs of running the energy efficiency program. The SCT may also include non

- energy costs, such as reduced customer comfort levels. The benefits included are the avoided costs of energy

and capac ity, plus environmental and other non

- energy benefits that are not currently valued by the

market.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 14 

# 3 I N T R O D U C T I O N

This report assesses the potential for energy efficiency programs to assist the District of Columbia in

meeting future energy service needs. This section of the report provides the following information:

 Defines the term “energy efficiency”,

 Describes the general benefits of energy efficiency programs

 Provides results of similar energy efficiency potential studies conducted in other states

 D escribes contents of the Sections of this report.

The purpose of this energy efficiency potential study is to provide a detailed assessment of the technical,

economic and achievable potential for electric and natural gas energy efficiency and demand respo nse programs that can be used by the consultants to develop short

- and long

- term energy goals and strategies

for accomplishing the District’s energy goals within the next 10 years. The strategies that will be

developed based on this potential study will al ign the District’s C omprehensive E nergy P lan ( CEP ) with

the Sustainable DC Plan. The CEP consultants will provide a comprehensive set of energy efficiency and

renewable energy goals and recommendations that will guide the District in reducing energy

consum ption, increasing local generation and clean power usage, ensuring energy reliability and

affordability, and creating green jobs for District residents.



### 3.1 I NTRODUCTION TO 

### E NERGY 

### E FFICIENCY



### Efficient energy use, often referred to as energy efficiency, is us ing less energy to provide the same level

of energy service. An example would be insulating a home or business to use less heating and cooling

energy to achieve the same inside temperature. Another example would be installing fluorescent lighting

in place of less efficient halogen or incandescent lights to attain the same level of illumination. Energy

efficiency can be achieved through more efficient technologies and/or processes as well as through

changes in individual behavior.

3.1.1 General Benefits of Energy Efficiency



### There are a number of benefits that accrue to the District of Columbia due to electric and natural gas

energy efficiency programs. These benefits include avoided cost savings, non

- electric benefits such as

water and fossil fuel savings, enviro nmental benefits, economic stimulus, job creation, risk reduction, and

energy security.

Avoided electric energy and capacity costs are based upon the costs an electric utility would incur to

construct and operate new electric power plants or to purchase p ower from another source. These

avoided costs of electricity include both fixed and variable costs that can be directly avoided through a

reduction in electricity usage. The energy component includes the costs associated with the production

of electricity , while the capacity component includes costs associated with the capability to deliver

electric energy during peak periods. Capacity costs consist primarily of the costs associated with building

peaking generation facilities. The forecasts of electric ene rgy and capacity avoided costs and natural gas

avoided costs used in this study were provided to the consultants by the DCSEU. Avoided costs for

natural gas include the avoided costs of the natural gas commodity and any other savings on the natural

gas dis tribution system for operations and maintenance expenses or natural gas infrastructure

expenditures.

At the consumer level, energy efficient products often cost more than their standard efficiency

counterparts, but this additional cost is balanced by low er energy consumption and lower energy bills.

Over time, the money saved from energy efficient products will pay consumers back for their initial

investment as well as save them money on their electric and natural gas bills . Although some energy

efficient technologies are complex and expensive, such as installing new high efficiency windows or aD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 15 

### high efficiency boiler, many are simple and inexpensive. Installing compact fluorescent lighting or low

flow water devices, for example, can be done by most indivi duals.

Although the reduction in electric and natural gas costs is the primary benefit to be gained from

investments in energy efficiency, the electric and natural gas utilities in the District

, their consumers, and

society as a whole can also benefit in other ways. Many electric efficiency measures also deliver non

energy benefits. For example, low

- flow water devices and efficient clothes washers also reduce water

consumption. 8 

### Similarly, weatherization measures that improve the building shell not only sa ve on air

conditioning costs in the summer, but also can save the customer money on space heating fuels, such as

natural gas or propane. Reducing electricity consumption also reduces harmful emissions, such as SO X



### , NO X 

### , CO 2 

### and particulates into the enviro nment. 9



### Energy efficiency programs create both direct and indirect jobs. The manufacture and installation of

energy efficiency products involves the manufacturing sector as well as research and development,

service, and installation jobs. These are skill ed positions that are not easily outsourced to other states and

countries. The creation of indirect jobs is more difficult to quantify, but result from households and

businesses experiencing increased discretionary income from reduced energy bills. These s avings

produce multiplier effects, such as increased investment in other goods and services driving job creation

in other markets.

Energy efficiency reduces risks associated with fuel price volatility, unanticipated capital cost increases,

environmental r egulations, supply shortages, and energy security. Aggressive energy efficiency programs

can help eliminate or postpone the risk associated with committing to large investments for generation

facilities a decade or more before they are needed. Energy effi ciency is also not subject to the same

supply and transportation constraints that impact fossil fuels. Finally, energy efficiency reduces

competition between states and utilities for fuels, and reduces dependence on fuels imported from other

states or coun tries to support electricity production. Energy efficiency can help meet future demand

increases and reduce dependence on out

- of

- state or overseas resources.

Many electric utilities recognize the benefits of reducing greenhouse gases. For example, PPL El ectric’s

web site provides a carbon footprint calculator for customers to use. The introduction to this calculator

states “If we all take a few simple steps to create less greenhouse gases, we can reduce the effects of

climate change.” First Energy also re cognizes the importance of environmental impacts. The First

Energy web site states “ At FirstEnergy, we are committed to protecting the environment while

delivering safe, reliable electricity to six million customers in the Midwest and Mid

- Atlantic regions.

Using a balanced, long

- term approach, we continually look for opportunities to minimize the

environmental impact of our operations.”



### 3.2 T HE 

### W

ASHINGTON 

### DC C ONTEXT



### 3.2.1 Continuing Customer Growth



### The annual kWh sales and electric system peak load for the District of Columbia is projected to increase

over the next decade . From 200 1 to 201 1 , the number of residential electric utility customers for Pepco

8 The ENERGY STAR web site (www.energystar.gov) states that “ ENERGY STAR qualified clothes washers use about 37%

less energy and use over 50% less water than regular washers”.

9 The 2009 ENERGY STAR Annual Report states that “ 2009 was another banner year for EPA’s climate protection

partnerships. More than 19,500 organizations across the country have partnered with EPA and achieved outstanding

results: (1) Preventing 83 million metric tons (in MMTCE2) of GHG s

— equivalent to the emissions from 56 million

vehicles (see Figure 4, p. 6)

— and net savings to consumers and businesses of about $18 billion in 2009 alone. (2)

Preventing more than 1,200 MMTCE of GHGs cumulatively and providing net savings to consumers and businesses of

more than $250 billion over the lifetime of their investments.” See page 2 of this Annual Report.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 16 

### grew at a rate of approximately 1.7 % annually. 10 

### The electric load forecasts for the District developed by

the consu ltants indicate that the number of electric consumers in the District will continue to increase

from 2013 through 202 2 (the timeframe for this study) creating further growth in system electricity sales

and peak demand. Similarly, natural gas sales are proj ected to increase at a rate of .9% per year from

2013 to 2022. This report assesses the potential for electric and natural gas energy efficiency programs to

assist the District in meeting future electric and natural gas energy service needs.

3.2.2 Energy Effici ency Activity



### Making homes and buildings more energy efficient is seen as a key strategy for addressing energy

security, reducing reliance on fossil fuels from other countries, assisting consumers to lower energy bills,

and addressing concerns about clima te change. Faced with rapidly increasing energy prices, constraints in

energy supply and demand, and energy reliability concerns, states are turning to energy efficiency as the

most reliable, cost

- effective, and quickest resource to deploy. 11



### 3.2.3 Recent Energ y Efficiency Potential Studies in the Mid

- Atlantic Region



### Table 3

- 1, below, provides the results from a review of recent energy efficiency potential studies

conducted throughout the Northeast and US. It is useful to examine the results of these studies to

understand if these studies are similar to this latest study for the District

.

Table 3

- 1 : Results of Recent Energy Efficiency Potential Studies in the Northeast and US

State Study Year Author Study Period # of Years Achievable

Potential

Connecticut 2009 KEMA 2009

- 2018 10 20.3%

New Hampshire 2009 GDS 2009

- 2018 10 20.5%

Rhode Island 2008 KEMA 2009

- 2018 10 9.0%

Vermont 2011 GDS/Cadmus 2011

- 2018 10 9.0%

New York 2010 Global Energy Partners 2011

- 2018 8 9.0%

USA 2009 McKinsey & Company 2011

- 2020 10 23.0%

Pennsylvania 2012 Statewide Evaluator 2013

- 2023 10 17.3%



### A 2010 report by the American Council for an Energy Efficient Economy (ACEEE) offers information

regarding the current savings and spending related t o energy efficiency by state. 12 

### Based on self

- reported

data, the top states annually spend more than 2% of electric sales revenue on energy efficiency programs.

The consultants also examined actual energy efficiency savings data for 2010 and 2011 from the US

Energy Information Administration (EIA) on the top twenty energy efficiency electric utilities. These top

twenty utilities saved over 2% of annual kWh sales in 2010 with their energy efficiency programs , and

3.8% of annual kWh sales in 2011. These perce ntage savings are attributable to energy efficiency

measures installed in a one

- year time frame and demonstrate what can be accomplished with full

- scale

and aggressive implementation of programs

.

10 This is the compound average annual growth rate for residential electric customers for Pepco’s DC service area.

11 The December 2008 National Action Plan for Energy Efficiency (NAPEE) “Vision for 2025: A Framework for Change”

states that “the long

- term aspirational goal for the Action Plan is to achieve all cost

- effective energy efficiency by the year

2025. Based on studies, the efficiency resou rce available may be able to meet 50% or more of the expected load growth

over this time frame, similar to meeting 20% of electricity consumption and 10 percent of natural gas consumption. The

benefits from achieving this magnitude of energy efficiency nat ionally can be estimated to be more than $100 billion in

lower energy bills in 2025 than would otherwise occur, over $500 billion in net savings, and substantial reductions in

greenhouse gas emissions.”

12 American Council for an Energy Efficient Economy, “ The 2010 State Energy Efficiency Scorecard”, Report #E107,

October 2010.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 17 

### 3.3 P URPOSE OF THIS 

### S TUDY



### This study provides an analysis of t he technical, economic, achievable and program potential for electric

and natural gas energy efficiency resources in the District as well as demand response programs . This

study has examined a full array of energy efficiency and demand response technologie s and energy

efficient building practices that are technically achievable.



### 3.4 C OST



### - EFFECTIVENESS 

### F INDINGS



### The Societal Cost test cost

- effectiveness screening as implemented by the DC SEU follows the

prescribed methodology detailed in the California Standar d Practice Manual (CA SPM). The California

Standard Practice Manual establishes standard procedures for cost

- effectiveness evaluations for utility

sponsored or public benefits programs and is generally considered to be an authoritative source for

defining cost

- effectiveness criteria and methodology. This manual is often referenced by many other

states and utilities.

The consultants ’ cost effectiveness screening tool used for this study quantifies all of the societal benefits

and costs included in the Socie tal Cost test . Quantified benefits include electric energy and capacity

avoided supply costs, alternative fuel and water savings, and any specified environmental externalities,

risks, or non

- energy benefits. Costs include the specified measure cost (increm ental or full cost , as applicable ), any increase in supply costs (electric or fossil fuel), as well as operation and maintenance

costs. In addition, the consultants ’ screening tool is capable of evaluation of cost

- effectiveness based on

various market repl acement approaches, including replace

- on

- burnout, retrofit, and early retirement.

The current avoided costs incorporated in the consultants ’ model are based on several sources. Electric

generation and capacity avoided costs are based on PEPCO’s filed 2012

- 2014 EmPOWER Maryland

Energy Efficiency Plan . T&D avoided costs were calculated based on PEPCO’s July 2011 filing of the

FERC formula transmission rate update and then adjusted to include assumed distribution costs. The

n atural gas avoided costs obtained from the DCSEU are apparently based on a forecast of natural gas

avoided costs for New England and then adjusted by the historical ratio of the District’s natural gas prices compared to New England gas prices.

In addition, the consultants ’ screening tool currently applies a 30 percent adder (10 percent each for

externalities, risk, and non

- energy benefits) to all quantified avoided cost benefits as specified in the

DCSEU evaluation framework document

.

This energy efficiency and demand response potenti al study concludes that there remains significant

achievable cost effective potential for electric and natural gas energy efficiency and demand response

measures and programs in the District. Table s 3

- 2

, 3

- 3 and 3

- 4 show the Societal Cost test benefit

- cost

ratios for the Maximum Achievable, Base Achievable, and Constrained Achievable potential scenarios,

for the five and ten

- year implementation periods starting in 2013.

Table 3

- 2: Societal Cost Test Benefit

- Cost Ratios for the Maximum Achievable Potential Scenario For 5

- Year

and 10

- Year Implementation Periods

Societal Cost Test Benefit

- Cost Ratios for the Maximum Achievable Potential Scenario For 5

-

Year and 10

- Year Implementation Periods

Achievable Potential Scenarios SCT $ Benefits SCT $ Costs SCT Benefi t/Cost

Ratio

5

- yr period $6,605,144,984 $1,440,446,220 4.59

10

- yr period $12,670,482,719 $2,541,727,303 4.98D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 18 Table 3

- 3: Societal Cost Test Benefit

- Cost Ratios for the Base Achievable Scenario For 5

- Year, and 10

- Year

Implementation Periods

Societal Cos t Test Benefit

- Cost Ratios for the Base Achievable Potential Scenario For 5

- Year and

10

- Year Implementation Periods

Achievable Potential Scenarios SCT $ Benefits SCT $ Costs SCT Benefit/Cost

Ratio

5

- yr period $3,937,727,800 $609,600,088 6.46

10

- yr perio d $7,745,717,753 $1,115,231,954 6.95

Table 3

- 4 : Societal Cost Test Benefit

- Cost Ratios for the Constrained Achievable Scenario For 5

- Year and 10

- Year Implementation Periods

Societal Cost Test Benefit

- Cost Ratios for the Constrained Achievable Potential Scenario For 5

-

Year and 10

- Year Implementation Periods

Achievable Potential Scenarios SCT $ Benefits SCT $ Costs SCT Benefit/Cost

Ratio

5

- yr period $3,258,746,270 $476,652,583 6.84

10

- yr period $6,380,955,238 $868,574,226 7.35



### In addition, the consult ants calculate d a SCT ratio for each energy efficiency measure and each demand

response measure considered in this study. Only measures that had a SCT ratio greater than or equal to

1. 0 were retained in the economic and achievable potential savings estimat es.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 19 

# 4 C H A R

A C T E R I Z A

T I O N O F 

# W

A S H I N G T O N 

# D C S E R V I C E



# A R E A

Energy efficiency potential studies and other market assessment studies are valuable sources of

information for planning energy efficiency programs. In order to develop estimates of electricity and

natura l gas savings potential, it is important to understand the extent to which electricity and natural gas

is used by households and businesses in Washington D.C. This section provides a brief overview of the

economic/demographic characteristics of the Washing ton D.C. service areas. Data are also presented for

historical and forecasted energy sales and system peak demand.



### 4.1 W ASHINGTON 

### DC M EMBER 

### S ERVICE 

### T ERRITORIES



### This section provides information on economic, demographic, geographic and appliance saturation

ch aracteristics of Washington D.C. In order to develop estimates of energy savings potential, it is

important to understand how energy is used by households and businesses. Washington D.C. is an

urban locale with a population of approximately 619,020 person s in 2011, and 298,902 housing units. 13



### The District’s population only grew 5.2% between 2000 and 2010, whereas the population in the entire

US grew 9.7%.

4.1.1 Washington DC Geographic and Demographic Characteristics



### Washington D.C. is the 25 th 

### largest city (i n terms of population) in the US. Despite its sizeable populace,

the District is small in total area (61.05 square miles) when compared to other service areas in the nation.

Delivering energy efficiency services in a small service area like Washington D.C. presents different

challenges than in larger jurisdictions (for example, larger geographic regions such as Alaska, California

or Texas ) . The District is bordered by Montgomery County, Maryland to the northwest, Prince George's

County, Maryland to the east , and Arlington and Alexandria, Virginia to the south and west. The

Potomac River forms the District's border with Virginia and has two major tributaries. The Washington

Metropolitan Area, which includes the District and surrounding suburbs, is the seventh

- largest

metropolitan area in the United States with an estimated 5.7 million residents in 2011 14



### .

As of the 2012 census , the District’s population was 632,323 persons and the population density was 9,856.5 people per square mile. The District population i n 2011 was spread out with 17% under the age

of 18, 71.6% 18 to 65, and 11.4% who were 65 years of age or older. The median age was 33.6 years in

2010. For every 100 females in 2010 there were 89.5 males. For every 100 females age 20 and over in

2010, ther e were 111.4 males. The District’s population in 2012 was 10.5% greater than the population in

2000.

There were 298,90 8 housing units in the District in 2011. 15 

### The housing unit density in 2011 was 4,896

units per square mile. As of 2011, there were 260,13 6 households in the District

, of which 13.4% had

children under the age of 18 living with them, 9.7% were married couples living together, 16.4% had a

female householder with no husband pr esent, and 57.7% were non

- families. 44.3% of all households

were made up of individuals and 20.4% had someone living alone who was 65 years of age or older. The

average household size was 2.11 and the average family size was 3.01. According to the American

Community Survey, 62% of D.C. residents live in multi

- family homes, while single family homes account

for the remaining 38% of the District’s housing stock. Table 4

- 1 provides a detailed breakout of the

13 The Washington D.C. population data for 2010 was obtained from US Census Bureau

.

14 "Table 1. Annual Estimates of the Population of Metropolitan and Micropolitan Stat istical Areas: April 1, 2010 to July 1,

2012" (CSV). 2012 Population Estimates . United States Census Bureau, Population Division.

15 This figure was obtained from the United States Census Bureau, American Community Survey 1

- Year Estimates,

Selected Housing Characteristics.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 20 

### housing distribution in Washington D.C. Figure 4

- 1 s hows a map of the geographic area covered by the

District.

Table 4

- 1 : Washington D.C. Housing Unit Characteristics 16

Housing Type Number of Households Percentage

Total 298,908 100.0%

One unit, detached 36,515 12.2%

On e unit, attached 78,060 26.1%

Multi

- family, 2 units 8,195 2.7%

Multi

- family, 3 or 4 units 20,714 6.9%

Multi

- family, 5 to 9 units 17,252 5.8%

Multi

- family, 10 to 19 35,031 11.7%

Multi

- family, 20 or more 102,714 34.4%

Mobile home 134 0.0%

Boat, RV, van, etc. 293 0.1%



### The economic/demographic data for a state or service area are important to understand when

developing estimates of energy efficiency potential. For example, one needs to know how many housing

units there are in a service ar ea in order to estimate the number of appliances that are plugged into the

electric grid in an area. In addition, the composition (age breakdowns, etc.) of the population is

important for the development of marketing strategies for different types of energ y efficiency programs.

Figure 4

- 1: Map of Washington D.C.

16 This data was obtained from the United States Census Bureau, American Community Survey 1

- Year Estimates, Selected

Housing Characteristics. The web site link for this information is listed below:

http://factfinder2.census.gov/faces/table services/jsf/pages/productview.xhtml?src=bkmkD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 21 

### 4.1.2 Historical Electric Sales and Electrical Customers in Washington DC



### Tables 4

- 2 and 4

- 3 show historical Washington D.C. data for annual GWh sales and electric customers

by class of service. From 2001 to 2010, GWh sales to ultimate electric customers in Washington D.C.

increased at a rate of 0.8% percent per year. From 2001 to 2011, the number of ultimate electric

customers increased at a rate of 1.48% percent per year.

According to 2010 historica l sales data, the residential sector accounts for approximately 90% of total

customers but only 18% of total energy sales while the commercial sector accounts for merely 10% of

total customers but almost 80% of all kWh sales. Not only does the commercial s ector constitute the

greatest portion of total kWh sales, it also consumes the most energy on a per customer basis. The

average commercial facility consumes roughly 348,000 kWh annually. Comparatively, the average

residential consumer uses approximately 9, 300 kWh per year.

Table 4

- 2: Historical Washington D.C. GWh Sales to Ultimate 17 Customers by Customer Class (GWh)

– 2001 to

2010 18

Year Residential Commercial Industrial Total

2001 1,699 8,716 281 10,696

2002 1,790 8,878 282 10,950

20 03 1,754 8,639 267 10,660

2004 1,834 8,994 282 11,110

2005 1,938 9,296 256 11,490

2006 1,822 9,030 240 11,092

2007 1,970 9,519 297 11,786

2008 1,897 9,290 305 11,492

2009 1,859 9,714 305 11,878

2010 2,123 9,209 230 11,562

Compound Annual

Average Ra

te of

Growth 2.51% 0.61%

- 2.20% 0.87%

Table 4

- 3: Historical Number of Customers by Customer Class

- 2001 to 2011 19

Year Residential Commercial Other Total

2001 195,648 26,121 33 221,802

2002 198,667 26,157 33 224,857

2003 200,226 25 ,866 32 226,124

2004 203,536 26,391 32 229,959

2005 208,324 26,689 31 235,044

2006 211,220 26,737 31 237,988

2007 215,170 26,630 33 241,833

2008 220,113 26,679 32 246,824

2009 226,030 26,399 32 252,461

2010 229,242 26,434 33 255,709

2011 230,384 26 ,486 32 256,902

Compound Annual

Average Rate of

Growth 1.65% 0.14%

- 0.31% 1.48%

17 In the utility industry, the term “ultimate customer” refers to a household or business that buys and uses a particular

product, such as electricity or natural gas, at the customer meter level of the energy d istribution system and note at the

wholesale level.

18 EIA, http://www.eia.gov/state/seds/seds

- data

- complete.cfm?sid=dc#Consumption

19 Provided by Pepco.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 22 

### Table 4

- 4 shows historical system peak loads by season for Pepco’s D.C. service area. Pepco’s total

summer peak load has fluctuated little between 2007 and 2012, translating to an overall decrease of only

.01%. Conversely, Pepco has seen a much more substantial change in winter peak load. Both the

residential and commercial sectors have experienced a decline in winter peak load since 2007, leading to

an overall system decreas e of 1.23%.

Table 4

- 4: Historical DC Pepco System Peak Load by Season (MW)

– 2007 to 2012 20

SUMMER PEAK LOAD (MW) WINTER PEAK LOAD (MW)

Year Residential Commercial Total Residential Commercial Total

2007 592 1,739 2,378 435 1,371 1,864

2008 559 1,775 2,398 400 1,220 1,683

2009 558 1,605 2,229 559 1,318 1,952

2010 590 1,662 2,309 397 1,289 1,751

2011 674 1,746 2,465 485 1,278 1,839

2012 611 1,721 2,377 422 1,268 1,752

Compound

Annual

Average Rate

of Growth 0.62%

- 0.22%

- 0.01%

- 0.61%

- 1.56%

- 1.23%



### 4.2 F ORECAST OF 

### E NERGY 

### S ALES 

### & P EAK 

### D EMAND 

### (2013

- 2023) 21



### The PJM load forecast for the Washington D.C. region projects that total kWh sales in the District will

grow at a moderate pace over the next two decades, at a compound average annual growth rate of 0.9%

a year (sales at the customer meter level of the utility grid). 22 

### The number of e lectric customers in

Washington D.C. is projected to grow 1.5% per year with the greatest growth occurring in the residential

sector, as depicted in Table 4

- 6 . Summer and wint er peak load for the District is projected to grow

approximately 1% per year. Table 4

- 5 presents the GWh sales forecast for Washington D.C., and Table

4

- 4 presents the summer and winter peak load forecasts for Pepco’s D.C. service areas. The numbers

shown in Tables 4

- 5 and 4

- 6 exclude the impacts of future DSM programs for the period 2013

- 2023.

Table 4

- 5 : GWh Sales Forecast for Washington D.C. (Without Future DSM Impacts) 23

Year Residential Commercial Industrial Total

2013 2,092 9,533 252 11,877

2014 2,124 9,610 251 11,984

2015 2,155 9,687 249 12,092

2016 2,187 9,766 248 12,201

2017 2,218 9,846 247 12,310

2018 2,250 9,926 246 12,421

2019 2,281 10,007 245 12,533

2020 2,313 10,090 243 12,646

2021 2,345 10,173 243 12,760

2022 2,37 6 10,257 242 12,874

2023 2,408 10,341 241 12,990

Compound Annual

Average Rate of

Growth 1.48% 0.81%

- 0.53% 0.90%

20 Provided by Pepco. Data prior to 2007 not available.

21 The electric load forecast provided in this section covers the time period from 2013 to 2023 so that policy makers will

have a forecast for the year 2013 as well as ten additional years beyond 2013.

22 PJM Load Forecast Report, January 2013. http://www.pjm.com/~/media/documents/reports/2013

- load

- forecast

report.ashx#page=87

23 The consultants utilized a regre ssion model to forecast GWh sales for residential, commercial and industrial sectors.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 23 Table 4

- 6: Electric Customer Forecast for Washington D.C. 24

Year Residential Commercial Other Total

2013 238,039 26,560 32 264,630

2014 241,961 26,596 32 268,589

2015 245,948 26,633 32 272,613

2016 250,000 26,670 32 276,702

2017 254,120 26,707 31 280,859

2018 258,307 26,745 31 285,083

2019 262,563 26,782 31 289,376

2020 266,890 26,819 31 293,740

2021 271,287 26,856 31 298,174

2022 275,757 26,893 31 302,682

2023 280,301 26,931 31 307,263

Compound Annual

Average Rate of

Growth 1.65% 0.14%

- 0.31% 1.50%

Table 4

- 7 : Pepco Peak Load Forecast for Washington D.C. (Without Future DSM Impacts) 25

SUMMER P EAK LOAD (MW) WINTER PEAK LOAD (MW)

Year Residential Commercial Total Residential Commercial Total

2013 646 1,863 2,509 447 1,373 1,820

2014 656 1,878 2,534 454 1,384 1,837

2015 666 1,893 2,559 460 1,395 1,855

2016 675 1,909 2,584 467 1,406 1,873

201 7 685 1,924 2,609 474 1,418 1,891

2018 695 1,940 2,635 480 1,429 1,910

2019 705 1,956 2,661 487 1,441 1,928

2020 714 1,972 2,686 494 1,453 1,947

2021 724 1,988 2,712 501 1,465 1,966

2022 734 2,005 2,739 507 1,477 1,984

2023 744 2,021 2,765 514 1,489 2,003

Compound

Annual

Average Rate

of Growth 1.42% 0.82% 0.97% 1.42% 0.82% 0.97%



### 4.3 N ATURAL 

### G AS 

### U SE IN 

### W ASHINGTON 

### DC

This section provides key background information used by the consultants to determine the economic

and achievable potential for natural gas energy efficiency savings in Washington D.C. It presents

historical natural gas consumption data for the District as well as the consultants ’ forecasts of natural gas

customers and sales broken down by sector. This data provides the foundation for determi ning estimates

of natural gas energy efficiency potential in Washington D.C. It is important to have information on the

current consumption levels and uses of natural gas in the District as a starting point for the energy

efficiency potential study. This i nformation is needed (1) to ensure that projections of achievable energy

efficiency potential do not exceed the amount of natural gas that is consumed in the District and (2) to

facilitate the matching of natural gas energy efficiency measures to applicabl e natural gas end uses in the

District. Thus a key element of a natural gas potential study is a thorough analysis of the saturation of

24 The consultants applied historical customer growth rates to develop the forecast of customers by class of service.

25 The consultants a nalyzed Pepco’s load profile to de velop seasonal load factors for each sector. The load factors were

then applied to the consultant s ’ GWh forecast to develop the peak load forecast.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 24 

### natural gas using equipment, the current energy efficiency levels of such equipment, and the natural gas

usage character istics of such equipment.



### 4.4 N ATURAL 

### G AS 

### C ONSUMPTION IN 

### W ASHINGTON 

### DC

4.4.1 Introduction



### Approximately 154,000 Washington D.C. customers used natural gas in 2011, the most recent year

where detailed natural gas consumption data for Washington D.C. is available. I n total, 33.0 trillion BTU

were consumed. Figure 4

- 2 shows the proportion of natural gas used by various segments of the

Washington D.C. economy in 2011, the last year for which actual data is available. Deliveries to

residential and commercial customers i n the District account for 89% of total gas usage.

Table 4

- 8 : Historical Washington D.C. Trillion BTU Sales to Ultimate Customers by Customer Class (TBTU)

– 2001 to 2011 26



### The number of n atural gas customers grew at a modest rate of 0.55% over the past decade, with the

greatest increase in customers occurring in the transportation sector. The number of transportation

customers has grown 1. 2 % per year since 2001, compared to only a 0.6% per year rise in the number of

residential customers and a correspon ding 1.6% per year decrease in the number of commercial

customers over the same time period. Historical trends in customer counts for each s ector are presented

in Table 4

- 9

.

Figure 4

- 2: Breakdown of Natural Gas Consumption, Washington D.C., 2010 27

26 EIA, http://www.eia.gov/dnav/ng/ng_con s_sum_dcu_SDC_a.htm

27 Ibid.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 25 Tab le 4

- 9: Historical Number of DC Natural Gas Customers by Customer Class

– 2001 to 2011 28



### The table above characterized natural gas usage by residential, commercial and industrial customers

based on the latest historical data available from the U.S. Energ y Information Administration (EIA) and

forecasts of natural gas sales and customers developed by the consultant s for this project. The remainder

of this section describes forecasted natural gas usage for the major customer classes (residential and

commerci al) and other information on natural gas usage in Washington D.C.

4.4.2 Total Gas Sales and Customer Forecast



### The latest available natural gas consumption forecasts for the residential, commercial and industrial

segments of the Washington D

. C

. region indicate t hat natural gas demand will increase from 33 trillion

BTU in 2011 to 37 trillion BTU in 2023 (representing a compound average annual rate of growth of

28 Provided by Washington GasD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 26 

### .9%). 29 

### Table 4

- 10 shows the sales forecast for natural gas in Washington D.C. by customer class, while

Ta ble 4

- 11 shows the forecast of customers for the District. The consultant s used the customer growth

rates actually experienced over the past decade to forecast the growth in the number of natural gas

customers for the next decade. The consultant s plan to f ollow

- up with Washington Gas during June of

2013 to determine if Washington Gas staff believe that a continuation in the decline of the number of

commercial and industrial customers in the District is likely. This follow

- up discussion is necessary to

under stand how natural gas sales to commercial customers can continue to increase at 1.2% per year

while the number of customers continues to decline.

The sales of natural gas to the commercial sector is expected to grow at a much faster pace than the

resident ial sector, with a forecasted average annual growth rate for 2013 to 2023 of 1. 2 %. Growth in

residential natural gas consumption is forecasted to stagnate for the next decade with a forecasted

average annual growth rate of about 0.02%.

Table 4

- 10: Forecas t of Natural Gas Consumption by Customer Class 2013

- 2023 (Trillion BTU) 30

Table 4

- 11 : Forecast of Natural Gas Customers by Customer Class, 2013

- 2023 (Trillion BTU) 31

29 During teleconferences between staff of Washington Gas and the consultants , Washington Gas stated that it does not

make public its forecasts of natural gas consumption forecasts. 29 the consultant s did ask Washington Gas to review the

natural gas consumption forecast prepared for this study. Washington Gas staff representatives did review the forecast

prepared by the consultants and had no suggested changes or comments as of May 31, 2013. Washingto n Gas staff did

suggest that further information on future natural gas sales could be obtained in the Management Discussion section of

the WGL Holdings, Inc. 2012 Corporate Financial Report, which can be located on the Washington Gas website at

www.wglholdings.com under Investor Relations

30 This forecast was developed by the consultants in the spring of 2013 based upon an examination of historical energy

use trends in Washington D.C. and EIA’s 2013 natural gas cons umption forecast for the U.S. and the mid

- Atlantic region.

The electric load forecast provided in this section covers the time period from 2013 to 2023 so that policy makers will

have a forecast for the year 2013 as well as ten additional years beyond 2013

.

31 T he consultants applied historical customer growth rates to develop the forecast of natural gas customers by class of

service.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 27 

### 4.5 C URRENT 

### DDOE AND 

### DCSEU DSM O FFERINGS



### Both DDOE and the DC Sustainable Energy Utilit y ( DCSEU ) offer several energy efficiency programs

for homes and businesses in the District.

4.5.1 Current DDOE Energy Efficiency Programs



### DDOE offers several energy efficiency programs for both the residential and commercial sectors. These

programs cover eff

iciency improvements for space heating, space cooling, water heating, lighting and

other uses of energy. The consultants plan to add a few other DDOE programs to this section as soon

as this information is received from Lance Loncke.

DIY

- Do It Yoursel

f

DDOE recommends that residents use a certified contractor to make major energy efficiency

improvements. If a consumer wishes to make some improvements on his/her own, DDOE has created

a DIY Home Energy Audit section on DDOE website. This resource provides information on home

energy topics including; sealing air leaks, attic insulation, heating equipment and energy

- efficient

appliances.

Free Home Energy Audits

DDOE ’ s Free Home Energy Audits Program promotes energy efficiency assessments for single family

homes in the District. Participants may apply to receive a free energy audit for their home if they live in a

single family home or townhouse that is 4000 square feet or le ss; multi

- family homes do not qualify for

the program. Based on a home energy rating system, auditors suggest specific cost

- effective, energy

efficient improvements that should be done to reduce the home's operational costs and improve

comfort. There are n o household income restrictions for this program.

Discounts on Utility Bills

DDOE's Utility Discount Programs provide low

- income District residents with discounts of up to $240

per year on electric bills to help reduce their utility costs while educating them on everyday energy

efficiency and conservation practices they can employ to further cut down on their energy spending.

Program participants must demonstrate financial need to qualify and must complete a short program

that teaches them how to save ener gy in their home.

Weatherization Assistance Program (WAP)D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 28 

### The Weatherization Assistance Program (WAP), funded by the U.S. Department of Energy, is designed

to help low

- income residents reduce their energy bills by providing technical and financial assista nce to

make their homes more energy efficient. WAP performs energy audits for qualifying families and installs

audit

- recommended energy efficiency measures to help families maintain energy

- efficient, safe and

healthy homes. In the District, WAP is admini stered through selected Community Based Organizations

that hire local contractors to install the energy efficiency measures recommended by the energy audit.

Small Business Energy Efficiency Program (SBEEP)

The Small Business Energy Efficiency Program ( SBEEP) provides up to $7000 in financial assistance to

help qualified small businesses identify and install energy efficient measures that can reduce energy

consumption and overall operating costs. Local contractors are hired to supply and install audit

re commended energy efficient measures, thereby creating employment opportunities for District

residents. In order to qualify for the program, business must have fewer than 15 employees and less than

$1,000,000 in annual revenue.

Condominium and Cooperative Building Energy Efficiency Program (CCBEEP)

The Condominium and Cooperative Building Energy Efficiency Program (CCBEEP) provides technical

and financial incentives to help resident

- owners of condo/coop buildings and their associations identify

and install energy efficient measures in their facilities. CCBEEP provides a comprehensive Retro

commissioning Study (RCx), financial assistance to help correct deficiencies, and follow

- up performance

tracking. CCBEEP specifically targets older condo/coop buildings th at were built before 1978 and

owners that have a demonstrated interest in improving the energy efficiency of their building(s).

Heating System Repair, Replacement, and Tune

- up Program

The Heating System Repair, Replacement, and Tune

- up Program performs h ome energy audits, tune

ups, repairs, and replacements of HVAC systems, hot

- water heaters, and thermostats in low

- income

dwelling units. Participants in this program typically receive an assessment of their heating system as part

of whole

- house weatherizat ion audit, except when heating systems are replaced or repaired on an

emergency basis because there is no heat in the home or as a health and safety measure. Program

eligibility is based on federal low

- income guidelines.

4.5.2 Current Programs Offered by the D C Sustainable Energy Utility (DCSEU)



### Listed below are descriptions of the energy efficiency programs offered by the Sustainable Energy Utility

(DCSEU).

DC SEU Home Performance with ENERGY STAR Program

Home Performance with ENERGY STAR is a national program sponsored by the U.S. Department of

Energy that incentivizes homeowners to identify and install energy efficiency improvements in their

homes. The DCSEU is the local implementer of the Home Performance with ENERGY STAR program

for the District of Columbia . DC SEU Home Performance offers a $500 incentive to District residents

living in single family homes or row homes who successfully complete a minimum of $1500 worth of

approved improvements. The DCSEU also offers an additional $500 incentive for homeowners who

work with their contractor to complete qualifying duct sealing work on their heating/cooling system.

Low

- Income Comprehensive Multifamily Program (LIMF)

The DCSEU offers financial incentives and technical assistance to affordable housing developers a nd

property owners who work together with the DCSEU to incorporate energy

- efficient systems and

measures in the new development, redevelopment, or substantial rehabilitation of affordable housing in

the District . To qualify for incentives, developers must demonstrate that at least 66% of their residentialD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 29 

### units per building are designated for or inhabited by households with incomes at or below 60% Area

Median Income.

Low

- Income Multifamily Implementation Contractor Direct Installation Program (ICDI)

The DC SEU offers no cost energy

- efficient Compact Fluorescent Light (CFL) bulbs and water saving

devices to owners and property managers of qualified affordable housing units. The program works in

the following manner: qualifying affordable housing owners and pr operty managers submit a request for

participation to the DCSEU, upon which the DCSEU provides resident education on the equipment

being installed and hires contractors to install the equipment at no cost to building owners or residents.

Business Energy

Rebates Program

The DCSEU ’s Business Energy Rebates program provides District businesses and institutions with

financial rebates for installing energy

- efficient equipment. Qualifying measures include lighting, HVAC,

compressed air, refrigeration, and food service and vending. Rebates are available for a maximum of 100

fixtures and/or $5,000 in rebates, per location, per fiscal year.

Commercial and Institutional Custom Program

The DCSEU Commercial and Institutional Custom Program is designed to target own ers of large

buildings in the District who are replacing old equipment, renovating an existing building, or beginning a

new construction project. Virtually any measure or operational improvement leading to cost

- effective

energy savings is eligible for cons ideration to receive incentivized services from the program. Program

services may include financial incentives, technical and design assistance, and coordinating services to

assist consumers, design professionals, vendors, and contractors in overcoming the barriers to installing

energy

- efficient equipment.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 30 

# 5 P O T E N T I A

L 

# S T U D Y 

# M E T H O D O L O G Y

This section describes the overall methodology that was utilized by the consultants to conduct the energy efficiency potential study for the District. The main objectiv e of this energy efficiency potential study is

to quantify the technical, economic and achievable potential for electric and natural gas energy efficiency

in Washington D

. C. This report provides estimates of the potential kWh and kW electric savings and

MM Btu gas savings for each level (technical, economic and achievable potential) of energy efficiency

potential. This document describes the general steps and methods that were used at each stage of the

analytical process necessary to produce the various esti mates of energy efficiency potential

.

Energy efficiency potential studies involve a number of analytical steps to produce estimates of each type

of energy efficiency potential : technical, economic, and achievable . This study utilize s benefit/cost

screeni ng tools for the residential and non

- residential sectors to assess the cost effectiveness of energy

efficiency measures. These cost effectiveness screening tools are Excel

- based models that integrate

technology

- specific impacts and costs, customer characte ristics, utility avoided cost forecasts and more.

Excel was used as the modeling platform to provide transparency to the estimation process and allow for

simple customization based on the District’s unique characteristics and the availability of specific m odel

input data. The major analytical steps and an overview of the potential savings are summarized below,

and specific changes in methodology from one sector to another have been noted throughout this

section.

 

### Measure List Development

 

### Measure Characteriza tion

 

### Load Forecast Development and Disaggregation (for the non

- residential sector)

 

### Potential Savings Overview

 

### Technical Potential

 

### Economic Potential

 

### Measure Cost

- Effectiveness Screening

 

### Achievable Potential



### 5.1 M EASURE 

### L IST 

### D EVELOPMENT



### The e nergy efficiency a nd demand response measure included in this study cover measures form the

DCSEU energy efficiency programs, additional measures included in the Mid

- Atlantic Technical

Reference Manual (TRM), as well as other measures based on the consultants ’ existing kno wledge and

current databases of electric and natural gas end

- use technologies and energy efficiency /demand

response measures

. The study scope includes measures and practices that are currently commercially

available as well as emerging technologies

. The co mmercially available measures are of the most

immediate interest to DSM program planners in Washington D

. C

. However, a small number of well

documented emerging technologies were considered for each sector. Emerging technology research was

focused on measur es that are commercially available but may not be widely accepted at the current time.

In April 2013, the consultants provided the energy efficiency measure lists for each sector to DDOE

staff for review and comment. These measure lists were then reviewed, discussed and updated as

necessary.

In addition, this study includes measures that could be relatively easily substituted for

, or applied to

, existing technologies on a retrofit or replace

- on

- burnout basis. Replace

- on

- burnout applies to equipment

replace ments that are made normally in the market when a piece of equipment is at the end of its useful

life. A retrofit measure is eligible to be replaced at any time in the life of the equipment or building.

Replace

- on

- burnout measures are generally characteriz ed by incremental measure costs and savings ( e.g. the costs and savings of a high

- efficiency versus standard efficiency air conditioner); whereas retrofit

measures are generally characterized by full costs and savings (e.g. the full costs and savings assoc iated

with adding ceiling insulation into an existing attic ). For new construction, energy efficiency measuresD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 31 

### can be implemented when each new home or building is constructed, thus the rate of availability is a

direct function of the rate of new construct ion.

5.1.1 Measure Characterization



### A significant amount of data is needed to estimate the kWh, kW and MMBtu savings potential for

individual energy efficiency and demand response measures or programs across the entire existing

res idential and non

- residential sectors in Washington D

. C

. The consultants used District specific data

wherever it was available and up

- to

- date. C onsiderable effort was expended to identify, review, and

document all available data sources

. 32 

### This review has allowed the development of reas onable and

supportable assumptions regarding : measure lives ; measure installed incremental or full costs ( as appropriate) ; and electric and natural gas savings and saturations for each mea sure included in the final

list of measures in this study.

Costs and savings for new construction and replace on burnout measures are calculated as the

incremental difference between the code minimum equipment and the energy efficiency measure. This

approach is utilized because the consumer must select an efficiency l evel that is at least the code

minimum equipment. The incremental cost is calculated as the difference between the cost of high

efficiency and standard (code compliant) equipment. However, for retrofit measures, the measure cost

and savings were considered to be the “full” cost of the measure, as the baseline scenario assumes the

consumer would do nothing.



### Savings: Estimates of annual measure savings as a percentage of base equipment usage were developed

from a variety of sources, including:

 

### DCSEU TRM

 

### Mi d

- Atlantic Technical Reference Manual (TRM)

 

### Existing deemed savings databases

 

### Building energy simulation software (such as the REM/Rate model) and engineering analyses

 

### Secondary sources such as the American Council for an Energy

- Efficient Economy (“ ACEEE ”)

, Department of Energy (“ DOE ”)

, Energy Information Administration (“ EIA ”)

, ENERGY

STAR, Air Conditioning Contractors of America (“ACCA”) and other technical potential studies



### Measure Costs: Measure costs represent either incremental or full cost s , and typ ically include the

incremental cost of measure ins tallation. For purposes of this study, nominal measures costs were held

constant over time. This general assumption is being made due to the fact that historically many measure

costs (e.g., CFL bulbs, Energ y Star appliances, etc.) have declined over time, while some measure costs

have increased over time (e.g., fiberglass insulation). Cost estimates were obtained from the following

types of data sources :

 

### Existing deemed savings databases

 

### Secondary sources su ch as ACEEE, ENERGY STAR, NREL, NEEP Incremental Cost Study

Report, and other technical potential studies

 

### Retail store pricing (such as web sites of Home Depot and Lowe’s) and industry experts



### Measure Life: Represents the number of years that energy

- using equipment is expected to operate. Useful

life estimates have been obtained from the following data sources :

 

### Mid

- Atlantic TRM

 

### Manufacturer data

 

### Savings calculators and l ife

- cycle cost analyses

32 The appendices and supporting databases to this report provide the data sources used by the consultants to obtain up

to

- da te data on energy efficiency measure costs, savings, useful lives and saturations.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 32 

###  

### Secondary sources such as ACEEE, ENERGY STAR, and other techn ical potential studies

 

### The California Database for Energy Efficient Resources (“ DEER ”) database

 

### Evaluation reports

 

### O ther consultant research or technical reports



### Baseline and Efficient Technology Saturations: In order to assess the amount of electric and natural gas

energy efficiency savings and demand response savings still available, estimates of the current saturation

of baseline equipment and energy efficiency measures , or for the non

- residential sector the amount of

energy use that is associated with a specific end use (such as HVAC) and percent of that energy use that

is associated with energy efficient equipment are necessary. Up

- to

- date measure saturation data were primarily obtained from the following recent studies:

 2009 EIA Residential Energy Con sumption Survey (RECS)

 2007 American Housing Survey (AHS)

 2006 EIA Manufacturing Energy Consumption Survey (MECS)

 2003 EIA Commercial Building Energy Consumption Survey (CBECS)

 2000 Pepco Appliance Saturation Survey

 Maryland residential and commercial base line studies

Further detail regarding the development of measure assumptions for energy efficiency in the residential

and non

- residential sectors are provided in this report in later sections . Additionally, the appendices of

the report provide a comprehen sive listing of all energy efficiency measure assumptions and sources.



### 5.2 F ORECAST 

### D ISAGGREGATION



### For the non

- residential sector, the baseline load forecast was disaggregated by combining inputs from a

Maryland commercial sector baseline study and forecast s of electric and natural gas sales for the District

to obtain average consumption estimates by customer segment and end use, and summed up to the

sector level. This disaggregation effort was conducted by the consultants as this level of detail was not

ava ilable in the historical or forecast sales data provided by PEPCO or Washington Gas. The

disaggregated forecast data provides the foundation for the development of energy efficiency potential

estimates for the non

- residential sector. It was not necessary t o develop a disaggregated residential sales

forecast because a bottom

- up approach was used for the residential sector.

5.2.1 Role of Naturally Occurring Conservation



### Naturally occurring conservation exists through government intervention, improved manufacturin g

efficiencies, building energy codes, market demand, and increased energy efficient implementation

through early fore

- runners, who will implement measures without explicit monetary incentives. The

impacts of new Federal government mandated energy efficien cy standards have already been reflected in

the baseline data for equipment unit energy consumption being used for this potential study. These new

government standards, such as the new standards included in the Federal government’s December 2007

Energy Ind ependence and Security Act (EISA) 33



### , can significantly increase naturally occurring potential

through tax incentives, stimulus f u nding or stricter manufacturing standards. These forces cause certain

sector end

- use energy consumption values to improve across the baseline forecast . It is important to

account for these forces as thoroughly as possible to ensure the energy efficiency potential is not double

counted, by over

- stating the potential that could occur for end

- uses where codes and standards are

reducin g baseline unit energy consumption. In addition, the consultants ha ve reflected the impacts of

new EISA lighting standards that will go into effect starting in 2012, as well as changes to other federal

33 PUBLIC LAW 110

– 140

— DEC. 19, 2007. Energy Independence and Security Act of 2007D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 33 

### baseline standards across a variety of end uses. These adjustments reduce energy efficiency potential

starting in the years these standards come into effect, and in subsequent years.



### 5.3 P OTENTIAL 

### S AVINGS 

### O VERVIEW



### Potential studies often distinguish between several types of energy efficiency potential: technical

, economic, and achievable. However, because there are often important definitional issues between

studies, it is important to understand the definition and scope of each potential estimate as it applies to

this analysis.

Figure 5

- 1: Types of Energy Effici ency Potential 34



### The first two types of potential, technical and economic, provide a theoretical upper bound for energy

savings from energy efficiency measures. Still, even the best designed portfolio of programs is unlikely to

capture 100 percent of the technical or economic potential. Therefore, achievable potential attempts to

estimate what may realistically be achieved, when it can be captured, and how much it would cost to do

so. Figure 5

- 1 above illustrates the three most common types of energy effi ciency potential.



### 5.4 T ECHNICAL 

### P OTENTIAL



### The consultants used the energy efficiency potential definitions included on page 2

- 4 of the November

2007 National Action Plan for Energy Efficiency (NAPEE) Guide for Conducting Energy Efficiency

Potential Studies. T echnical potential is the theoretical maximum amount of energy use that could be

displaced by efficiency, disregarding all non

- engineering constraints such as cost

- effectiveness and the

willingness of end

- users to adopt the efficiency measures. It is often estimated as a “snapshot” in time

assuming immediate implementation of all technologically feasible energy saving measures, with

additional efficiency opportunities assumed as they arise from activities such as new construction. 35



### In general, this study utilizes a “bottom

- up” approach in the residential sector to calculat e the potential

of an energy efficiency or demand response measure or set of measures as illustrated in Figure 5

- 2 below

. A bottom

- up approach was used for the residential sector due to t he amount of data available for this

sector from Federal government surveys and research done in nearby states. A bottom

- up approach first

starts with the savings and costs associated with replacing one piece of equipment with its high efficien cy

counterpa rt, and then multiplies these values by the number of measures available to be installed

throughout the life of the program. The bottom

- up approach is applicable in the residential sector

because of better secondary data availability and greater homogeneit y of the building and equipment

stock to which measures are applied, compared to the non

- residential sector. However, this methodology

was not utilized in the non

- residential sector. For the non

- residential sector, a “top

- down” approach was

used for develo ping the technical potential estimates . The “top down” approach builds an energy use

profile based on estimates of kWh sales by business segment and end use. S avings factors for energy

efficiency measures are then applied to applicable end use energy estim ates after assumptions are made

34 Reproduced from “Guide to Resource Planning with Energy Efficiency” November 2007. US E PA. Figure 2

- 1.

35 National Action Plan for Energy Efficiency, “Guide for Conducting Energy Efficiency Potential Studies”, page 2

- 4D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 34 

### regarding the fraction of sales that are associated with inefficient equipment and the

technical/engineering feasibility of each energy efficiency measure.

Figure 5

- 2: Residential Sector Savings Methodology

- Bottom Up App roach



### As shown in Figure 5

- 2, the methodology starts at the bottom based on the number of residential

customers (splitting them into single

- family and multi

- family customers as well as existing vs. new

construction). From that point, estimates of the si ze of the eligible market in the District are developed

for each energy efficiency measure. For example, energy efficiency measures that affect electric space heating are only applicable to those homes in the District that have electric space heating.

As noted previously, t o obtain up

- to

- date appliance and end

- use saturation data, the study made

extensive use of the 2007 American Housing Survey (AHS), the 2009 Residential Energy Consumption

Survey (RECS), the 2000 PEPCO appliance saturation survey and the Maryland energy efficiency

baseline study. The surveys collected detailed data on the current saturation of electricity and natural gas

consuming equipment in the District and the energy efficiency level of HVAC equipment, appliances,

and building shell c haracteristics. Estimates of energy efficient equipment saturations were based on

several sources, including data collected from the 2009 RECS and the Maryland baseline study.

The goal of the approach is to determine how many households that a specific me asure applies to (base

case factor), then of that group, the fraction of households/buildings which do not have the energy

efficient version of the measure being installed (remaining factor). In instances where technical reasons

do not permit the installa tion of the efficient equipment in all eligible households an applicability factor

is used to limit the potential. Alternative water heating technologies (efficient water heater tanks and/or

heat pump water heaters) are then utilized to meet the remaining market potential. The last factor to be

applied is the savings factor, which is the percentage savings achieved from installing the efficient

measure over a standard measure.

In developing the overal l potential electricity savings, the analysis account s for the interactive effects of

measures designed to impact the same end

- use. For instance, if a home were to properly seal all

ductwork, the overall space heating and cooling consumption in that home would decrease. As a result,

the remaining potential f

or energy savings derived from a heating/cooling equipment upgrade would be

reduced. In instances where there are two (or more) competing technologies for the same electrical (or

natural gas) end use, such as heat pump water heaters, water heater efficienc y measures and high

efficiency electric storage water heaters, in most cases an equal percent age of the available population isD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 35 

### assigned to each measure using the applicability factor 36 

### . In the event that one of the competing

measures is not found to be cos t

- effective, the homes /buildings assigned to that measure are

transitioned over any of the remaining cost effective alternative s

.

The savings estimates per base unit are determined by comparing the high

- efficiency equipment to

current installed equipmen t for existing construction retrofits or to current equipment code standards for

replace

- on

- burnout and new construction scenarios.

5.4.1 Core Equation for the Residential Sector



### The core equation used in the residential sector energy efficiency technical pote ntial analysis for each

individual efficiency measure is shown below in Equation 5

- 1 below

.

Equation 5

- 1 : Core Equation for Residential Sector Technical Potential



### Where:

 

### Total Number of Households = the number of househo lds in the market segment (e.g. the

number of households living in detached single

- family buildings)

 

### Base Case Equipment End

- use Intensity = annual gas consumption (MMB t u) used per

customer, per year, by each base

- case technology in each market segment. Th is is the

consumption of natural gas

- using equipment that efficient technology replaces or affects. This

variable fully accounts for any known building characteristics in the service area, such as average

square footage.

 

### Saturation Share = this variable has two parts: the first is the fraction of the end use gas energy

that is applicable for the efficient technology in a given market segment. For example, for

residential water heating, this would be the fraction of all residential gas customers that have gas water heating in their household; the second is the share of the end use gas energy that is

applicable for the efficient technology that has not yet been converted to an efficient technology.

 

### Applicability Factor = this factor ensures that a househol d cannot receive two of the same type

of measure. For example, if we assume there are two tiers of efficient gas furnaces, one which

yields 10% savings and another which yields 20% savings, a household that needs to replace its

inefficient furnace could ei ther receive the unit which yields 10% savings or the unit which yields

20% savings, but could not receive both units. In general, the consultants appl y an even distribution to the same type of measure across eligible households when applying this factor.

T he consultants may, in some cases, assign unbalanced applicability factors, if it believes an even

distribution is inappropriate 37 

### . The applicability factor also captures the fraction of applicable

units technically feasible for conversion to the efficient technology from an engineering

perspective (e.g., it may not be possible to add wall insulation in all homes because the original

construction of some homes does not allow for wall insulation to be installed without requiring

major reconstruction of the h ouse, which would be an additional cost that does not yield any

energy benefits).

36 The consultants used its professional judgment in some cases to assign unequal applicability factors to attempt to avoid

ov erstating or understating the potential of the set of competing technologies.

37 For example, if historical data indicates a technology has been able to garner a large share of the market the consultants

may assign a higher applicability factor to this tech nology in order to properly reflect this knowledge.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 36  

### Savings Factor = the percentage of gas consumption reduction resulting from applications of

the efficient technology. The savings factor is a general term used to illustrate the calculation of a

measures technical potential. The model use d fully integrate d the necessary assumptions to

determine the measure

- level savings, given the Base Case Equipment End

- use Intensity , and

the expected savings of each technology.

Technical en ergy efficiency potential in the residential sector is calculated in two steps. In the first step,

all measures are treated independently ; that is, the savings of each measure are not reduced or otherwise

adjusted for overlap between competing or interacti ng measures. By analyzing measures independently,

no assumptions are made about the combinations or order in which they might be installed in customer

buildings. However, the cumulative technical potential cannot be estimated by adding the savings from

the individual savings estimates because some savings would be double

- counted. For example, the

savings from a measure that reduces heat loss from a building, such as insulation, are partially dependent

on other measures that affect the efficiency of the syst em being used to heat the building, such as a high

efficiency furnace; the more efficient the furnace, the less energy saved from the installation of the

insulation. In the second step, adjustments are made to account for such interactive effects.

Finally

, the consultants ha ve developed a supply curve to show the amount of energy efficiency savings

available at different cost levels. The residential sector supply curve is included in an appendix of this

report. A generic example of a sup ply curve is shown in Figure 5

- 3 . As shown in the figure, a supply

curve typically consists of two axes; one that captures the cost per unit of saving a resource (e.g., dollars

per lifetime kWh or MMBtu saved) and another that shows the amount of savings that could be

achiev ed at each level of cost. The curve is typically built up across individual measures that are applied

to specific base

- case practices or technologies by market segment. Savings measures are sorted based on

a metric of cost. T otal savings available at vario us levels of cost are calculated incrementally with respect

to measures that precede them. Supply curves typically, but not always, end up reflecting diminishing

returns, i.e., costs increase rapidly and savings decrease significantly at the end of the cur ve.

Figure 5

- 3: Generic Example of a Supply Curve



### As noted above, the cost portion of this energy efficiency supply curve is represented in dollars per unit

of lifetime energy savings. Cost are annualized (often referred to as levelized) in supply curv es. ForD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 37 

### example, electric energy efficiency supply curves usually present levelized costs per kWh saved by

multiplying the initial investment in an efficient technology or program by the capital recovery rate

(CRR) , and then dividing that amount by annual kWh savings :

Therefore,

Levelized Cost per kWh Saved = Initial Cost x CRR/Annual kWh Savings

5.4.2 Core Equation for the Non

- Residential Sector



### The core equation utilized in the commercial sector technical potential analysis for each individual

efficiency meas u re is shown below in Equation 5

- 2

. The forecast of commercial square footage

information was developed by the consultants . The information used by the consultants on the total

square footage by business type is available from the consultants upon request.

Equation 5

- 2 : Core Equation for Commercial Sector Technical Potential



### Where:

 

### Total end

- use kWh sales by industry type = the forecasted electric sales level for a given end

use (e.g., space heating) in a commercial or industrial industry type (e.g., office buildings or

fabricated metals).

 

### Base Case factor = the fraction of end

- use energy applicable for the efficient technology in a

given industry type. For example, with fluorescent lighting, this would be the fraction of all

lighting kWh in a given industry type that is associated with fluorescent fixtures.

 

### Remaining factor = the fraction of applicable kWh sales associated with equipment not yet

converted to the electric energy

- efficiency measure; that is, one minus the fraction of the

industry type with energy

- efficiency measures already installed.

 

### Convertible factor = the fraction of the equipment or practice that is technically feasible for

conversion to the efficient technology from an engineering perspective (e.g., it may not be

possible to install variable

- frequency drives (VFDs) on all motors.

 

### Savings factor = the fraction of electric consumption reduced by application of the efficient

technology.

For the non

- residential sector, the development of the energy effic iency technical potential estimate

begins with a disaggregated energy sales forecast over the ten year forecast horizon (2013 to 2022). The

non

- residential sales forecast is broken down by building type, then by electric end use. Then a savings

factor is a pplied to end use electricity sales to determine the potential electricity savings for each end use.

The commercial sector

, as defined in this analysis

, is comprised of the following business segments:

 Warehouse

 Retail

 Grocery

 Office

 Lodging

 Healthcare

 R estaurantD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 38 

###  Institutional, including education

 Other

Similar to the residential sector, technical electric energy efficiency savings potential in the non

residential sector is calculated in two steps. In the first step, all measures are treated independentl y ; that is,

the savings of each measure are not reduced or otherwise adjusted for overlap between competing or

synergistic measures. By treating measures independently, their relative economics are analyzed without

making assumptions about the order or com binations in which they might be implemented in customer

buildings. However, the total technical potential across measures cannot be estimated by summing the

individual measure potentials directly because some savings would be double

- counted. For example, the

savings from a weatherization measure, such as low

- e ENERGY STAR windows, are partially dependent

on other measures that affect the efficiency of the system being used to cool or heat the building, such as

high

- efficiency space heating equipment or hig h

- efficiency air conditioning systems; the more efficient

the space heating equipment or electric air conditioner, the less energy saved from the installation of

low

- e ENERGY STAR windows. Accordingly, the second step is to rank the measures based on a

met ric of cost

- effectiveness (using the SC test) and adjust savings for interactive effects so that total

savings are calculated incrementally with respect to measures that precede them.



### 5.5 E CONOMIC 

### P OTENTIAL



### Economic potential refers to the subset of the techn ical potential that is economically cost

- effective

(based on screening with the SC test (or SCT) as compared to conventional supply

- side energy resources.

The consultants ha ve calculated the SC benefit/cost ratios for this study according to the DC Sustain able

Energy Utility Measurement and Verification Framework

. Both technical and economic potential are

theoretical numbers that assume immediate implementation of energy efficiency measures, with no

regard for the gradual “ramping up” process of real

- life p rograms. In addition, they ignore market

barriers to ensuring actual implementation of energy efficiency. Finally, they only consider the costs of

efficiency measures themselves, ignoring any programmatic costs (e.g., marketing, analysis,

administration , p rogram evaluation, etc. ) that would be necessary to capture them.

The consultants pre

- screened possible energy efficiency technologies for several reasons. Measure pre

screening removed measures that were not commercially available, were already at curre nt code, or were

not applicable to the District. Furthermore, all measures that were not found to be cost

- effective based

on the results of the societal cost test were excluded from the economic and achievable potential. Then

allocation factors were readju sted and applied to the remaining measures that were cost effective. The

societal cost test is defined in greater detail in Section 5.6 below.



### 5.6 D ETERMINING 

### C OST



### - E FFECTIVENESS



### The consultants utilized the DC Sustainable Energy Utility Measurement and Verifi cation Framework to

determine cost

- effectiveness for energy efficiency measures in this potential study. The cost effectiveness

test that was used is the Societal Cost Test (SC).

5.6.1 Societal Cost Test



### The S C test aims to quantify the impact of an energy effi ciency program on society as a whole, and

therefore, measures the net costs and benefits of a demand

- side management or energy efficiency

measure or program as a resource option based on the total costs of the measure/ program, including

both the participan ts' and the utility's costs. In order to determine the overall benefit to society of a

measure/program, the SC test places particular emphasis on societal and environmental effects of a

program typically not considered by other cost effectiveness tests. Fo r example, the SC test aims to

quantify positive program externalities such as:

 

### The environmental benefits of avoided transmission and distribution costsD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 39 

###  

### The environmental benefits of avoided generation costs

 

### The benefit of increased system reliability

 

### No n

- energy benefits (water, waste, etc.)

 

### Low

- income or elderly population benefits

 

### Benefits of fuel diversity

In general, t he costs in the SC test (incremental or full cost depending on whether the measure was

replaced on burnout or is an early replacement) are the program costs paid by the utility (or program

administrator) and the participants

. Thus all equipment costs, installation, operation and maintenance,

cost of removal and administration costs, no matter who pays for them, are included in this test.

According to the National Action Plan for Energy Efficiency Guide titled “Understanding Cost

Effectiveness of Energy Efficiency Programs”, a ny tax credits are considered transfer payments for the

SC test , and therefore, are excluded from the analysis

. For purposes of this study, administrative costs

were not included for the measure cost effectiveness screening conducted to develop the estimates of

economic potential. Administrative program costs are included in SC tests for achievable potential.

5.6.2 Avoided C osts



### The avoided cost forecasts utilized to measure cost

- effective screening and for reporting potential

benefits were based on the DC Sustainable Energy Utility Measurement and Verification Framework

, including energy, transmission, distribution, and capa city avoided costs. The discount rate used in the

calculation of the District S C Test is the 10

- year treasury rate . Avoided energy costs are time and

seasonally differentiated where possible.



### 5.7 A CHIEVABLE 

### P OTENTIAL



### Achievable potential was determined as the amoun t of energy and demand that can realistical ly be saved

assuming an aggressive program marketing strategy and with three program incentive scenarios

. Achievable potential takes into account barriers that hinder consumer adoption of energy efficiency

m easures such as financial, political and regulatory barriers , and the capability of programs and

administrators to ramp up activity over time. The potential study evaluates three achievable potential

scenarios:

 

### The Maximum Achievable potential scenario is based on incentives equal to 100% of measure

incremental costs

 

### The Base Achievable potential scenario is based on incentive levels comparable to current

DCSEU spending levels

 

### The Constrained Achievable potential scenario is a scaled down version the Base Achievable

potential scenario in which the incentives offered are significantly lower than current DCSEU

spending levels. In general, the incentives assumed in this scenario are half of those assumed in

the Base Achievable potential scenario.

While many different incentive scenarios could be modeled, the number of achievable potential scenarios

that could be developed was limited to three scenarios due to the available budget for this potential

study. The consultants analyzed the three selected achievable potential scenarios with different

anticipated penetration curves or market acceptance mo dels for each incentive level. In each of the

achievable potential scenarios , the penetration curves are based on an expected market adoption given

the level of incen tives associated with each scenario. For the residential sector, the consultants estimated

the market adoption using the results of a survey of multifamily building property managers which

ascertained the property managers’ willingness to participate in hy pothetical energy efficiency programs

at given levels of incentives for a variety of end use measures 38



### . T he consultants chose to use this

38 Massachusetts Multifamily Market Characterization and Potential Study Volume 1, May 2012. The Cadmus Group, et. al.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 40 

### approach in order to use the results of actual survey data and to differentiate the anticipated market

adoption across measures and end

- uses, in lieu of assuming a universal market adoption rate across all

measures or groups of measures, which would be based solely on professional judgment. The chosen

approach provides real data in conjunction with professional judgment, which was used to verify the

reasonableness of the assumed market adoption rates across the various end uses. For the non

- residential

sector, the consultants used a similar approach based on data collected from surveys of businesses in the

state of Maine. These three penetration scenarios contain uncertainty based on consumer’s actual

willingness to participate in programs offered by the DCSEU

.

For new construction, energy efficiency measures can be implemented when each new home or building

is construc ted, thus the rate of availability is a direct function of the rate of new construction. For

existing buildings, determining the annual rate of availability of savings is more complex. Energy

efficiency potential in the existing stock of buildings can be c aptured over time through three principal

processes:

1) A s equipment replacements are made normally in the market when a piece of equipment is at the

end of its effective useful life ( referred to as “replace

- on

- burnout”)

2) A t any time in the life of the equip ment or building ( referred to as “retrofit”)

3) When a new home or building is constructed

For the replace

- on

- burnout measures, existing equipment is assumed to be replaced with high

- efficiency

equipment at the time a consumer is shopping for a new appliance or other energy consuming

equipment, or if the consumer is in the process of building or remodeling. Using this approach, only

equipment that needs to be replaced in a given year is eligible to be upgraded to energy efficient

equipment. For the retrofit m easures, savings can theoretically be captured at any time; however, in

practice, it takes many years to retrofit an entire stock of buildings, even with the most aggressive of

energy efficiency programs. For new construction, savings are achieved at the t ime the building is

completed.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 41 

# 6 R E S I D E N T I A

L 

# E L E C T R I C A

N D 

# N A T U R A L 

# G A S 

# E N E R G Y



# E F F I C I E N C Y 

# P O T E N T I A L 

# E S T I M A T E S

This section provides electric and natural gas energy efficiency potential estimates for the residential

sec t or in Washington D.C. which includes all residential buildings. Estimates of technical, econom i c and

a c hievable potential are provided

. Electric and natural gas potential are presented as separate sections,

but interactive effects and measures that yield both electric and natural gas saving s are fully accounted

for in the analysis.



### 6.1 R ESIDENTIAL 

### E LECTRIC 

### P OTENTIAL



### According to 2010 historical sales data, the residential sector accounts for approximately 90% of total

customers and 18% of total energy sales

. T he average residential consumer use s approximately 9,300

kWh per year. From 2001

- 201 1 , the residential sect or in DC grew at a compound rate of 2.51 %. For

this study, residential MWh sales are estimated to increase 1

. 48 % annually based upon the January 2013

PJM Load Forecast Report 39



### . The r esidential electric potential calculations are based upon these

approximate consumption values and sales forecast figures over the time horizon covered by the study.

The potential is calculated for the entire residential sector and includes breakdowns of t he potential

associated with each end use, such as water heating and appliances.

6.1.1 Energy Efficiency Measures Examined



### For the residential s e ctor, there were 458 total electric savings measures in c luded in the potential ener g y

savin g s analysis 40 

### . Table 6

- 1 p rovides a br i ef desc r iption of the t y p e s of measures included f or each end

use in t h e residential model. T h e list of me a sures was d eveloped ba s ed on a review of t he

DCSEU TRM and m e asures found in other residential potential studie s and TRMs fr om regions near

Washington DC

. Measure data includes incremental costs, electricity energy and demand savings, gas and

water savings, a n d m easure life.

Table 6

- 1: Mea s u r es a n d P r ogr a ms I n c l uded i n the Electric Residential S ector A n al y s i s

End Use Type End Use Description Measures Included

HVAC

Envelope Building Envelope Upgrades • Air/duct Sealing

• Improved Insulation (Wall, Ceiling, and

Floor)

• Efficient Windows

• Radiant Barrier

• Low Income Weatherization Package

• New Construction Package (ENERGY

STAR home)

HVA C

Equipment Heating/Cooling/Ventilation Equipment

• Existing Central AC / ASHP Tune

- Up

• Efficient Air

- Source Heat Pumps

• Geothermal Heat Pumps

• Ductless Minisplit Heat Pumps & ACs

• Efficient Central AC Systems

• Programmable Thermostats

• Efficient Room Air Conditi oners

39 PJM Load Forecast Report, January 2013. http://www.pjm.com/~/media/documents/reports/2013

- load

- forecast

report.ashx#page=87

.

40 This total represents the number of unique energy efficiency measures and all permutations of these unique measures. For example, there are 17 permutations of the “Improved Duct Sealing” measure to account for the various housing types,

heating/cooling combinations, and construction types.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 42 End Use Type End Use Description Measures Included

• Efficient Furnace Fans

Water Heating Domestic Hot Water • Heat Pump Water Heater

• Solar Water Heater

• Low Flow Showerhead/Faucet Aerator

• Pipe Wrap

• Tank Wrap

Lighting Interior/Exterior Lighting

• Specialty CFLs

• Standard CFLs

• LED Lighting

Appliances High

- Efficiency Appliances / Retirement of

Inefficient Appliances • ENERGY STAR Clothes Washers

• ENERGY STAR Refrigerator

• ENERGY STAR Freezers

• ENERGY STAR Dishwashers

• ENERGY STAR Dehumidifiers

• Secondary Refrigerator Turn

- In

Electronics High Efficiency Consumer E lectronics • Controlled Power Strips

• ENERGY STAR Desktops

• Efficient Laptops

• Efficient Televisions

• LCD Monitors

Behavioral Consumer Response to Feedback from Utility • Direct (Real

- Time) Feedback

• Indirect Feedback

Other Efficient Pool Equipment • Variable Speed /Two

- Speed Pool Pump

and Motor

6.1.2 

### Overview of Residential Electric Energy Efficiency Potential



### This section presents esti m ates for electric technical, econom i c, and a chievable potential for the

residential sector. Each of the ta b les in the technical, econo mic and achievable sections pr e sent the

respective poten ti al for efficiency savin g s expressed as cumulative energy s a vings (MWh), percentage o f

savings by end use, and savings as a percentage of forecast sales. Data is provided on a 5

- year and 10

- year time hori z on f

or Washington D.C

.

This energy efficiency p o tential study considers t h e impacts of the Energy and Independence and

Security Act (EI S A) as an improving code s t andard f or the residential sec t or. The EISA improves t h e

baseline efficiency of several types of lighting products, including co m pact fluorescent l amps (C F L ).

Other known increases to federal minimum efficiency standards over the time period studied

have also been accounted for in the analysis. These included changes to the efficiency standa rds

of room and central air conditioners, heat pumps, electric water heaters, and appliances.

There are a variety of factors which contribute to uncertainty surrounding the savings estimates

produced by this energy efficiency potential study. These factor s can include the following:

 Uncertainty about economic and fuel price forecasts used as inputs to the electric and

natural gas sales forecasts

 The accuracy of results generated by building energy simulation modeling software

 The lack of availability of up

- to

- date baseline and efficiency saturation data for the

District

 Changes to codes and standards in the future which cannot be anticipated at the present

time

 Unknown future funding levels for the DCSEUD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 43 

###  Uncertainty regarding the future adoption of energy efficiency technologies which have

minimal market share at the present time, such as LED lighting.

T he consultants have addressed the areas of uncertainty as robustly as possible given the time

and budget constraints of this project. For example, no sal es forecast of either residential or

commercial gas consumption or electric consumption was provided to the consultants by the

utilities serving Washington D.C., which created a need for the consultants to develop these

forecasts using the best available s econdary data.



### S U MM A RY O F 

### F I ND I NG S



### Figure 6

- 1 illustrates the estimated savings potential f or each of the scenarios included in this study.

Figure 6

- 1: Summary of Residential Electric Energy Efficiency Potential as a % of 2017 and 2022 Sales

Forecasts



### The potential estimates are expressed as cumulati v e 5

- year and 10

- year savings, as percentages of the

respective 2017 and 2022 sector sales. The technical pot e ntial is 45.0 % in 2017 and 44.8 % in 2022. The

5

- year and 10

- year e c onomic pot ential is 43.9 % and 43 .7 %

. The slight drop from technical potential to

economic potential indicates that most measures are cost

- effective. The 5

- year and 10

- year ach i evable

potential savings are: 21.6 % and 27.9 % for the Maximum Achievable s cenario; 14.8 % a nd 1 8 .6% for

the Base Achievable scenario ; and 11. 7 % and 15.0 % for the Constrained Achievable s cenario . The

Maximum Achievable s cenario assumes 100% incentives, the Base Achievable scenario assumes

approximately 35% incentives, and the Constrained Achievab le s cenario assumes approximately 18%

incentives 41



### , with a cap of 25% of incremental cost for all non

- early

- retirement measures.

41 To the extent possible, the consultants used the current incentives po sted on the DCSEU website for the Base

Achievable scenario. The consultants identified incentive amounts for duct sealing, clothes washers, refrigerators and LED

lighting measures. The consultants assumed $10/bulb incentive for LED lighting (the website in dicated the rebates for

LED lighting are either $5 or $10). However, for all remaining measures, the consultants assumed a 35% incentive based

on limited information regarding the Home Performance program. For the Constrained Achievable scenario, in genera l,

the consultants assumed incentives equal to half of the Base Achievable scenario. Refer to Section 6.1.3 for further

discussion on the Constrained Achievable scenario incentives.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 44 

### T E C H N I C AL 

### P O T E N TI AL



### Technic a l poten t

ial repre s ents the quant

i ficati o n of savings that can be real i zed if all technologicall y

available energ

y

- e fficien c y measures are immediately adopted in all feasible inst a nces, re g ardless of cost.

Table 6

- 2 shows that i t is tec h ni c ally feasible to save nearly 1 million MWh in th e residential

sector between 2013 to 2017, as well as approximate ly 1.1 million MWh during the 10 year period from

2013 to 2022 across Washington D.C., represent i ng 45% of 5

- year residential sale s

, and 44.8% of 10

- year residential sales. Lig h t i ng represents the greatest contributor to the potential at 27% of savings,

wh ile the HVAC Envelope and HVAC Equipment end uses each contribute more than 20% of the

savings. Table 6

- 3 shows the demand savings potential in 2017 and 2022. The five and ten year summer

peak demand savings potential is 245 MW and 264 MW, respectively, wh ich is 35.8% and 36.0% of the

peak forecast. The five and ten year winter peak demand savings potential is 339 MW and 369 MW,

respectively, which is 71.4% and 72.7% of the peak forecast.

Table 6

- 2: Residential Sector Technical Potential Energy Savings by End Use

Residential Technical Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Appliances 73,743 7% 78,510 7%

Electronics 136,166 14% 154,126 14%

Lighting 271,517 27% 292 ,294 27%

Water Heating 57,706 6% 62,751 6%

Other 2,169 0% 2,355 0%

HVAC (Envelope) 200,060 20% 207,053 19%

HVAC (Equipment) 219,933 22% 227,465 21%

Behavioral Programs 37,384 4% 39,838 4%

Total 998,677 100% 1,064,393 100%

% of Annual Sales

Forecast 45.0% 44.8%

Table 6

- 3 : Residential S ector Tech n i c a l P o tent i al Demand S avi n gs

Residential Technical Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 245 264 339 369

% of Peak 35. 8% 36.0% 71.4% 72.7%



### E CONO MI C 

### P O T E N TI AL



### Economic potential is a s u bset of technical potential, which only accounts for measures that are cos t

effective, based on a screening using the Societal Cost Test (SCT), when calculati n g the savings p o tenti a l.

The SCT was used for this study because it is mandated by the District to be the cost

- effectiveness test

used when considering energy efficiency programs in Washington D

. C. The test includes a 30% adder to

electric and natural gas benefits. 89% of all measure s that were included in the electric potential analysis

passed the SCT.

Table 6

- 4 indicates that the economic potential is nearly 1 mi l lion MWh d uring the 5 year period from

2013 to 2017, and the economic potential increases to slightly more than 1 millio n M W h during the 10

year period from 2013 t o 2022. This represents 43.9 % a nd 43 .7 % of residential sales across the

respective 5

- year and 10

- year timeframes. Similar to the technical potential scenario, l ighting represents

the greatest contributor to the po tential at more than 25% of savings, while the HVAC Envelope and the

HVAC Equipment end use s each contribute approximately 20% of the savings

. Table 6

- 5 shows theD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 45 

### demand savings potential in 2017 and 2022. The five and ten year summer peak demand savings

p otential is 245 MW and 264 MW, respectively, which is 35.8% and 36.0% of the peak forecast. The five

and ten year winter peak demand savings potential is 339 MW and 369 MW, respectively, which is 71.4%

and 72.7% of the peak forecast.

Table 6

- 4: Residentia l Sector Economic Potential Energy Savings by End Use

Residential Economic Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Appliances 73,743 8% 78,510 8%

Electronics 137,202 14% 155,347 15%

Lighting 271,517 28% 292,294 28%

Water Heating 58,538 6% 63,658 6%

Other 2,169 0% 2,355 0%

HVAC (Envelope) 196,527 20% 203,518 20%

HVAC (Equipment) 197,568 20% 203,094 20%

Behavioral Programs 37,384 4% 39,838 4%

Total 974,647 100% 1,038,615 100%

% of Annual Sales

Forecast 43.9% 43.7%

Table 6

- 5 : Residential S ector Economic P o tent i al Demand S avi n gs

Residential Economic Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 238 25 6 339 369

% of Peak 34.8% 34.9% 71.5% 72.8%



### 6.1.3 Achievable Potential Savings in the Residential Sector



### Achievable potential is an estimate of energy savings that can feasibly be achiev e d given market barriers

and equipment replacement cycles. T h is study est imated achievable potential for three scenari o s correspond i ng to varying incent i ve levels p r ovided to end

- use c onsu m ers. The Maximum A chievable

p otential scenario is based on the assumption that incentives are equal to 100% of incremental costs.

The Base A chievable p otential scenario is based on the assumption that incentives are equal to the

current level of incentives offered by the DCSEU. Low

- income measures are assumed to have 100%

incentives in the Base Achievable scenario . The Constrained Achievable p otential scenario is based on

the assumption that incentives are equal to half of the Base Achievable scenario. Exceptions to this

assumption include: low

- income measures are still assumed to be eligible for 100% incentives ; the

incentive amount is capped at 25% of incremental cost in the Constrained Achievable scenario for all

non

- low

- income measures.

Tables 6

- 6 through Table 6

- 11 show the estimated savings for the achievable scenarios over 5 and 10

year time horizons. The 5

- year and 10

- year Maximum Achi evable potential savings estimates are

approximately 4 78 thousand MWh and 6 63 thousand MWh . This equates to 21.6 % and 2 7 .9% of sector

sales in 2017 and 2022. The respective 5

- year and 10

- year Base Achievable potential savings estimates are

approximately 32 8 thousand MWh and 442 thousand MWh . This equates to 14.8 % and 1 8 .6% of sector

sales in 2017 and 2022. The respective 5

- year and 10

- year Constrained Achievable potential savings

estimates are approximately 258 thousand MWh and 357 thousand MWh . This equate s to 11. 7 % and

15.0 % of sector sales in 2017 and 2022 . The ten year demand savings estimates in the Base Achievable

scenario are 120 MW in the summer and 202 MW in the winter, which represents 16.3% and 39.8% of

the peak demand forecast for the respective summer and winter seasons in 2022.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 46 Table 6

- 6: Residential Maximum Achievable Energy Savings by End Use

Residential Maximum Achievable Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Applianc es 28,219 6% 53,497 8%

Electronics 98,879 21% 107,658 16%

Lighting 183,634 38% 204,830 31%

Water Heating 26,957 6% 49,915 8%

Other 921 0% 1,858 0%

HVAC (Envelope) 69,019 14% 138,645 21%

HVAC (Equipment) 39,491 8% 75,777 11%

Behavioral Programs 30,9 64 6% 31,050 5%

Total 478,083 100% 663,229 100%

% of Annual Sales

Forecast 21.6% 27.9%

Table 6

- 7: Residential Maximum Achievable Potential Demand Savings

Residential Maximum Achievable Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 115 180 179 273

% of Peak 16.8% 24.6% 37.8% 53.9%

Table 6

- 8: Residential Base Achievable Savings Potential Energy Savings by End Use

Residential Base Achievable Potential Savings by End Use

201 7 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Appliances 17,480 5% 32,876 7%

Electronics 58,111 18% 69,100 16%

Lighting 146,587 45% 148,654 34%

Water Heating 13,117 4% 26,841 6%

Other 390 0% 840 0%

HVAC (Envelope) 47, 299 14% 96,911 22%

HVAC (Equipment) 17,333 5% 39,667 9%

Behavioral Programs 27,377 8% 27,452 6%

Total 327,693 100% 442,342 100%

% of Annual Sales

Forecast 14.8% 18.6%

Table 6

- 9 : Residential Base A ch i ev a b l e P o tent i al Demand S avi n gs

Residential Base A chievable Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 76 120 130 202

% of Peak 11.0% 16.3% 27.3% 39.8%

Table 6

- 10 : Residential Constrained A ch i ev a b l e S avings P o tent i al Energ y S avi n gs by End U s e

Residential Constrained Achievable Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Appliances 13,663 5% 24,714 7%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 47 Residential Constrained Achievable Potential Savings by End Use

Electronics 46,346 18% 57,121 16%

Lighting 110,630 43 % 115,944 33%

Water Heating 12,361 5% 24,895 7%

Other 331 0% 701 0%

HVAC (Envelope) 34,114 13% 69,985 20%

HVAC (Equipment) 16,385 6% 36,658 10%

Behavioral Programs 24,633 10% 26,510 7%

Total 258,463 100% 356,529 100%

% of Annual Sales

Forecast 11.7 % 15.0%

Table 6

- 11 : Residential Constrained A ch i ev a b l e P o tent i al Demand S avi n gs

Residential Constrained Achievable Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 64 102 111 177

% of Peak 9.3% 14.0% 23.4% 34.9%



### Figure 6

- 2 shows t h e percentage of savings by each end use for the Base Achievable p otential scenario.

The light i ng e nd use shows the la r gest p otenti a l for s avings with 34% of total savings, followed by the

HVAC Envelop e end use at 22% of total s avings.

Figure 6

- 2: Residential Sector 2022 Achievable Potential Savings for the Base Achievable Scenario, by End Use



### Figure 6

- 3 shows the bre a kdown of estimated savi ng s in 2022 by housing type, low

- income designation

and new construction measures, for t h e Base Achievable potential scenari o

. The savings are largely

coming from existing/tu r nover measures, meaning energy e f ficient equipment is installed in replacement

of existing equipment that has failed

. The existing single

- fa mily attached housing and existing multi

family housing type s lead the way with 3 2 % of savings each , followed b y and 2 1 % coming from existing

single

- family detached homes. New construction measures account for 8% of total savings and low

income measures ac count for 7 % of total savings. The low

- income measures represent only those

measures which apply strictly to low

- income households, and do not represent the “low

- income

potential” in the District . There is also low

- income potential that is subsumed by the other 93% of the

savings associated with the “non

- low

- income” measures . This report does not provide an estimate of the

low

- income potential.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 48 F i gu r e 6

- 3 : Residential Base Achievable S a v i ngs i n 2022, by Housing Type, Low

- Income Designation and New

Construc tion Measures



### Table 6

- 12

, Table 6

- 13 and Table 6

- 14 s hows cumulative energy sa vings for all three achievab l e potential scenarios for each year across the 10

- year time hor i zon for the study, broken out b y end use.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 49 Table 6

- 12: Cumulative Annual Residenti al Energy Savings in the Maximum Achievable Potential Scenario, by End Use for Washington D.C.

Cumulative Annual MWh Savings

- Maximum Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Appliances 5,613 11,241 16,885 22,544 28,219 33,911 39,620 45,348 49,413 53,497

Electronics 22,777 45,611 68,501 91,448 98,879 106,352 106,668 106,992 107,321 107,658

Lighting 37,842 75,750 111,119 147,079 183,634 216,241 220,848 227,571 216,469 204,830

Water Heating 5,358 10,730 16,123 21 ,531 26,957 31,747 36,265 40,797 45,347 49,915

Other 184 367 551 736 921 1,108 1,294 1,481 1,670 1,858

HVAC (Envelope) 13,760 27,540 41,344 55,169 69,019 82,896 96,795 110,719 124,670 138,645

HVAC (Equipment) 7,873 15,758 23,657 31,567 39,491 47,379 54, 457 61,549 68,656 75,777

Behavioral

Programs 22,458 26,693 30,932 30,948 30,964 30,981 30,997 31,015 31,032 31,050

Total 115,864 213,690 309,110 401,022 478,083 550,614 586,945 625,472 644,579 663,229

% of Annual Sales

Forecast 5.5% 10.1% 14.3% 18.3% 21 .6% 24.5% 25.7% 27.0% 27.5% 27.9%

Table 6

- 13: Cumulative Annual Residential Energy Savings in the Base Achievable Potential Scenario, by End Use for Washington D.C.

Cumulative Annual MWh Savings

– Base Achievable by End Use

End Use 2013 2014 2015 201 6 2017 2018 2019 2020 2021 2022

Appliances 3,243 6,621 10,135 13,754 17,480 21,214 24,957 28,708 30,789 32,876

Electronics 9,690 21,247 34,696 48,187 58,111 66,700 67,869 68,591 68,842 69,100

Lighting 26,172 56,418 87,023 117,080 146,587 172,859 175,142 170,951 159,507 148,654

Water Heating 1,788 4,130 7,022 10,021 13,117 15,951 18,551 21,209 23,972 26,841

Other 70 144 222 304 390 478 567 658 748 840

HVAC (Envelope) 9,214 18,555 28,014 37,597 47,299 57,090 66,965 76,920 86,899 96,911

HVAC (Equipment ) 2,667 5,737 9,204 13,062 17,333 21,864 25,891 30,217 34,813 39,667

Behavioral

Programs 8,683 15,918 24,207 26,314 27,377 27,391 27,406 27,420 27,437 27,452

Total 61,528 128,769 200,524 266,319 327,693 383,546 407,348 424,673 433,008 442,342

% of Annua

l Sales

Forecast 2.9% 6.1% 9.3% 12.2% 14.8% 17.0% 17.9% 18.4% 18.5% 18.6%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 50 Table 6

- 14 : Cumu l at i ve A nn u al Residential E n e r gy S avings i n the Constrained Achievable P o ten t i al S ce n a r i o, by E n d U s e f o r Washington D.C.

Cumulative Annual MWh Savings

– Const rained Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Appliances 2,581 5,245 7,995 10,800 13,663 16,532 19,407 22,288 23,499 24,714

Electronics 7,837 16,930 27,305 38,015 46,346 53,932 55,650 56,639 56,877 57,121

Light ing 17,863 40,371 64,342 87,760 110,630 130,686 135,013 132,892 124,183 115,944

Water Heating 1,722 3,941 6,669 9,476 12,361 14,987 17,369 19,797 22,304 24,895

Other 62 125 191 259 331 403 476 550 625 701

HVAC (Envelope) 6,665 13,407 20,234 27,135 34,1 14 41,169 48,300 55,510 62,739 69,985

HVAC (Equipment) 2,581 5,515 8,786 12,410 16,385 20,576 24,222 28,142 32,285 36,658

Behavioral

Programs 8,089 14,248 21,011 22,820 24,633 25,849 26,465 26,480 26,495 26,510

Total 47,399 99,781 156,534 208,676 258,46 3 304,134 326,901 342,297 349,006 356,529

% of Annual Sales

Forecast 2.3% 4.7% 7.3% 9.5% 11.7% 13.5% 14.3% 14.8% 14.9% 15.0%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 51 

### 6.1.4 Residential Savings Summary



### Table 6

- 15 provides a n end

- use breakdown of the residential savings potential estimates for techn ical

and economic potential, and each of the three achievable potential scenarios. The table indicates how the

savings potential decreases systematically from the technical potential scenario to the Constrained

Achievable potential scenario as additional l imiting factors such as cost

- effectiveness requirements and

anticipated market adoption at given funding levels are introduced.

Table 6

- 15 : Breakdown of Residential Cumulative Annual Electric Savings Potential for Technical, Economic

and Achievable Potent ial, by E n d U s e f o r Washington D.C.

End Use Technical

Potential

(MWh) Economic

Potential

(MWh) Max.

Achievable

Potential

(MWh) Base

Achievable

Potential

(MWh) Constrained

Achievable

Scenario

(MWh)

Appliances

ENERGY STAR

Refrigerators 30,067 30,067 20, 365 8,948 4,188

ENERGY STAR Freezers 2,308 2,308 1,559 1,186 1,125

ENERGY STAR Clothes

Washers 23,043 23,043 16,785 8,176 5,153

ENERGY STAR

Dishwashers 823 823 650 570 458

ENERGY STAR

Dehumidifiers 1,015 1,015 723 580 375

2nd Re frigerator Turn

- In 21,253 21,253 13,416 13,416 13,416

Electronics

Controlled Power Strips 71,548 71,548 51,040 16,708 12,376

Efficient Desktop PCs 12,699 12,699 8,919 6,371 5,878

Efficient Laptop PCs 1,941 3,162 2,015 1,728 764

Eff icient Televisions 66,460 66,460 44,769 43,421 37,434

Efficient LCD Monitors 1,478 1,478 916 873 669

Lighting

Specialty CFL Bulbs 132,244 132,244 95,390 83,364 63,670

Standard Screw

- In CFL

Bulbs 68,535 68,535 32,589 32,589 24,676

L ED Screw

- In Bulbs 46,867 46,867 44,951 3,409 1,547

Exterior Lighting 35,651 35,651 25,610 23,002 20,112

Water Heating

Heat Pump Water Heater 21,399 32,093 25,302 6,562 5,349

Solar Water Heating 9,788 0 0 0 0

Tank Wrap 2,197 2,197 1,734 1,734 1,734

Pipe Wrap 9,017 9,017 7,115 5,599 5,387

Low Flow Showerheads 15,760 15,760 12,439 10,594 10,327

Low Flow Faucet Aerators 4,591 4,591 3,324 2,353 2,098

Other

Efficient Pool Pump

Motors 2,355 2,355 1,858 840 701

HVAC (Envelope)

Ceiling/Attic Insulation 22,693 19,158 15,832 15,189 7,373D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 52 End Use Technical

Potential

(MWh) Economic

Potential

(MWh) Max.

Achievable

Potential

(MWh) Base

Achievable

Potential

(MWh) Constrained

Achievable

Scenario

(MWh)

Wall Insulation 32,414 32,414 26,619 25,600 14,934

Floor Insulation 4,619 4,619 3,656 1,693 1,543

Air Sealing 23,656 23,656 18,664 9,837 6,589

Duct Sealing 17,062 17,062 13,466 6,882 3,949

ENERGY STAR Windows 51,655 51,655 17,024 6,534 5,406

Radiant Barriers 9,876 9,876 7,797 988 159

Low Income

Weatherization Package 37,806 37,806 29,845 29,845 29,845

New Homes Construction

Package 7, 274 7,274 5,743 343 189

HVAC (Equipment)

ENERGY STAR Air Source

Heat Pumps 87,537 90,139 32,856 12,700 11,453

Geothermal Heat Pumps 12,860 11,382 2,709 935 818

ENERGY STAR Central

Air Conditioners 7,600 0 0 0 0

ENERGY STAR Room Air

Conditioners 18,069 22,678 9,446 6,953 6,556

Tune

- Up 1,948 386 243 195 183

Ductless Mini

- Split

Systems 51,161 33,183 14,996 8,253 7,668

Programmable

Thermostats 5,859 2,895 1,549 1,027 882

Efficient Furnace Fan

Motors 42,431 42,43 1 13,978 9,605 9,098

Behavioral Programs

Direct Feedback (In

- Home

Energy Display) 16,119 16,119 12,768 11,205 10,796

Indirect Feedback

(Monthly Energy Use

Reports) 23,719 23,719 18,281 16,247 15,713

Total 1,064,393 1,038,615 663,229 442,3 42 356,529

% of Annual 2022 Sales

Forecast 44.8% 43.7% 27.9% 18.6% 15.0%

Note: Measures in the above Table with “0” achievable potential are ones that did not pass the SCT Test.



### 6.2 R ESIDENTIAL 

### N ATURAL 

### G AS 

### P OTENTIAL



### T he consultants generated natural gas co nsumption forecasts for the residential, commercial and

institutional segments of the District economy indicate that natural gas demand will increase from 33

trillion BTU in 2011 to 37 trillion BTU in 2023 (representing a compound average annual rate of gr owth

of .9%) 42 

### . The residenti al sector is expected to grow more slowly compared to the commercial sector and

institutional sector , with a forecasted average annual growth rate for 20 11 to 2023 of 0.02 %

. These

forecasts are based on EIA Annual Energy Outlook growth rates

. The residential gas potential

calculations are based upon these approximate consumption values and sales forecast figures over the

time horizon covered by the study. The potential is calculated for the entire residential sector and

includes breakdowns of the potential associated with each end use, such as water heating and appliances

.

42 The consultants generated these forecasts because the utility did not pr ovide a forecast of their own.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 53 

### 6.2.1 Energy Efficiency Measures Examined



### For the residential s e ctor, there were 251 natural gas savings measures in c luded in the potential gas

savin g s analysis 43



### . Ta ble 6

- 1 6 provides a br i ef desc r iption of the t y p e s of measures included f or each end

use in t h e residential model. T h e list of me a sures was d eveloped ba s ed on a review of t he

DCSEU . TRM and m e asures found in other residential potential studie s a nd TRMs from regions near

Washington D

. C

. Measure data includes incremental costs, electricity energy and demand savings, gas

and water savings, a n d m easure life.

Table 6

- 1 6 : Mea s u r es a n d P r ogr a ms I n c l uded i n the Gas Residential S ector A n al y s i s

End Use Ty pe End Use Description Measures Included

HVAC

Envelope Building Envelope Upgrades • Air/duct Sealing

• Improved Insulation (Wall, Ceiling, and

Floor)

• Efficient Windows

• Radiant Barrier

• Low Income Weatherization Package

• New Construction Package (ENERGY

STAR hom e)

HVAC

Equipment Heating/Cooling/Ventilation Equipment

• Existing Gas Furnace/Boiler Tune

- up

• Efficient Gas Furnaces

• Efficient Gas Boilers

• Programmable Thermostats

Water Heating Domestic Hot Water • Efficient Gas Storage Tank WH

• Tankless Gas WH

• Low Flow Show erhead/Faucet Aerator

• Pipe Wrap

• Tank Wrap

Appliances High

- Efficiency Appliances / Retirement of

Inefficient Appliances • ENERGY STAR Clothes Washers

• ENERGY STAR Dishwashers

Behavioral Consumer Response to Feedback from Utility • Direct (Real

- Time) Feedback

• Indirect Feedback

6.2.2 

### Overview of Residential Natural Gas Energy Efficiency Potential



### This section presents esti m ates for gas technical, econom i c, and a chievable potential for the residential

sector. Each of the ta b les in the technical, econom i c and achieva ble sections pr e sent the respective

poten ti al for efficiency savin g s expressed as cumulative energy s a vings (MMBtu) percentage of savings

by end use , and savings as a percentage of forecast sales

. Data is provided on a 5

- year and 10

- year time

hori z on f or W ashington D.C

.

This energy efficiency p o tential study considers t h e impacts of the Energy and Independence and

Security Act (EI S A) as an improving code s t andard f or the residential sec t or. The EISA improves t h e

baseline efficiency of several types of ligh ting products, including co m pact fluorescent l amps (C F L ).

Other known increases to federal minimum efficiency standards over the time period studied

have also been accounted for in the analysis. These included changes to the efficiency standards

of room a nd central air conditioners, heat pumps, electric water heaters, and appliances.

43 This total represents the number of unique energy efficiency measures and all permutations of these unique measures.

For example, there are 6 permutations of the “Programmable Thermostat” measure to account for the various housing

types, heating/cooling combinations, and construction types.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 54 

### S U MM A RY O F 

### F I ND I NG S



### Figure 6

- 4 illustrates the estimated savings potential f or each of the scenarios included in this study.

Figure 6

- 4: Summary of Residential Energy Effic iency Potential as a % of 2017 and 2022 Sales Forecasts



### The potential estimates are expressed as cumulati v e 5

- year and 10

- year savings, as percentages of the

respective 2017 and 2022 sector sales. The technical pot e ntial is 28. 5 % in 2017 and 29.8 % in 2022. The

5

- year and 10

- year e c onomic potential is 25.2 % and 26.3 %

. The slight drop from technical potential to

economic potential indicates that most measures are cost

- effective based on the SCT measure

- level

screening. The 5

- year and 10

- year ach i evable potential savings are: 8.8 % and 17.5 % for the Maximum

Achievable s cenario; 5.3 % and 11.0 % for the Base Achievable scenario ; and 3.6 % and 7.3 % for the

Constrained Achievable s cenario . The Maximum Achievable scenario assumes 100% incen tives, the

Base Achievable scenario assumes approximately 35% incentives, and the Constrained Achievable

scenario assumes approximately 18% incentives 44



### , with a cap of 25% of incremental cost for all non

early

- retirement measures.



### T E C H N I C AL 

### P O T E N TI AL



### Technical potential represents the quantification of savings that can be realized if all technologically

available energy

- efficiency measures are immediately adopted in all feasible instances, regardless of cost.

Table 6

- 17 shows that it is technically f easible to save about 3.5 million MMBtu in the residential sector

between 2013 and 2017 and approximately 3.7 million MMBtu during the 10 year period from 2013 to

2022 across Washington D.C., representing more than 28 % of 5

- year residential sales, and near ly 30 % of

10

- year residential sales. The HVAC Envelope end use represents the greatest contributor to the

potential at 59 % of 10

- yr savings, while the Water Heating end use contributes 27% of the 10

- yr savings,

and the HVAC Equipment end use contribute s 16 % of the 10

- yr savings. The lighting end use yields an

8% gain in consumption. While there is significant potential for electric savings in the lighting end use,

44 To the extent possible, the consultants used the current incentives posted on the DCSEU website for the Base

Achievable scenario. the consultants identified incentive amounts for duct s ealing, clothes washers, refrigerators and LED

lighting measures. The consultants assumed $10/bulb incentive for LED lighting (the website indicated the rebates for

LED lighting are either $5 or $10. However, for all remaining measures, the consultants ass umed a 35% incentive based

on limited information regarding the Home Performance program. For the Constrained Achievable scenario, in general,

the consultants assumed incentives equal to half of the Base Achievable scenario. Refer to Section 6.1.3 for furt her

discussion on the Constrained Achievable scenario incentives.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 55 

### this potential would produce a negative impact on natural gas potential, due to increased heat ing

requirements associated with efficiency lighting. 45

Table 6

- 17: Residential Sector Technical Potential MMBtu Savings by End Use

Residential Technical Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Savings (MM Btu) Savings Savings (MMBtu) Savings

Appliances 72,459 2% 79,140 2%

Electronics 0 0% 0 0%

Lighting

- 289,578

- 8%

- 312,039

- 8%

Water Heating 931,490 26% 995,522 27%

Other 0 0% 0 0%

HVAC (Envelope) 2,106,656 60% 2,186,048 59%

HVAC (Equipment) 564,598 16% 592,000 16%

Behavioral Programs 153,073 4% 163,124 4%

Total 3,538,697 100% 3,703,794 100%

% of Annual Sales

Forecast 28.5% 29.8%



### E CONO MI C 

### P O T E N TI AL



### Economic potential is a s u bset of technical potential, which only accounts for measures that are c os t

effective, based on a screening using the Societal Cost Test (SCT), when calculati n g the savings p o tenti a l.

The SCT was used for this study because it is mandated by the District to be the cost

- effectiveness test

used when considering energy efficiency programs in Washington DC. The test includes a 30% adder to

electric and natural gas benefits. 87% of all measures that were included in the gas potential analysis

passed the SCT.

Table 6

- 1 8 indicates that the economic potential is more than 3 mi l lion MM Btu d uring the 5 year period

from 2013 to 2017, and the economic potential increases to nearly 3.3 million MMBtu during the 10

year period from 2013 t o 2022. This represents 25.2 % a nd 26.3 % of residential sales across the

respective 5

- year and 10

- year time frames. Similar to the technical potential scenario, the HVAC

Envelope end use represents the greatest contributor to the potential at 64 % of the 10

- yr savings, while

the Water Heating end use contributes 24% of the 10

- yr savings, and the HVAC Equipment en d use

contribute s 14 % of the 10

- yr saving s

.

Table 6

- 18: Statewide Residential Sector Economic Potential MMBtu Savings by End Use

Residential Economic Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Savings (MMBtu) Savings Savings (M MBtu) Savings

Appliances 72,459 2% 79,140 2%

Electronics 0 0% 0 0%

Lighting

- 289,578

- 9%

- 312,039

- 10%

Water Heating 734,792 24% 785,710 24%

Other 0 0% 0 0%

HVAC (Envelope) 2,017,113 65% 2,096,492 64%

HVAC (Equipment) 438,029 14% 456,476 14%

Behav ioral Programs 153,073 5% 163,124 5%

Total 3,125,887 100% 3,268,903 100%

% of Annual Sales Forecast 25.2% 26.3%

45 High efficiency lighting reduces the amount of waste heat that is released during hours of lighting operation. The

reduction in waste heat places a greater burden on heating equipment (ele ctric and gas) to meet the winter heating load

requirements.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 56 

### 6.2.3 Achievable Potential Savings in the Residential Sector



### Achievable potential is an estimate of energy savings that can feasibly be achiev e d g iven market barriers

and equipment replacement cycles. T h is study estimated a chievable potential for three scenari o s correspond i ng to varying incent i ve levels p r ovided to end

- use c onsu m ers. The Maximum Achievable

potential scenario is based on the assumpti on that incentives are equal to 100% of incremental costs.

The Base Achievable potential scenario is based on the assumption that incentives are equal to the

current level of incentives offered by the DCSEU 46 

### . Low

- income measures are assumed to have 100%

in centives in the Base Achievable scenario . The Constrained Achievable potential scenario is based on

the assumption that incentives are equal to half of the Base Achievable scenario. Exceptions to this

assumption include: low

- income measures are still assu med to be eligible for 100% incentives; the

incentive amount is capped at 25% of incremental cost in the Constrained Achievable scenario for all

non

- low

- income measures.

Tables 6

- 1 9 and Table 6

- 20 show the estimated savings for the achievable scenarios ov er 5 and 10 year

time horizons. The 5

- year and 10

- year Maximum achievable potential savings estimates are

approximately 1.1 mill i on MMBtu and 2. 2 million MMBtu

. This equates to 8.8 % a nd 17.5% of sector

sales in 2017 and 2022. The respective 5

- year and 10

- y ear Base Achievable potential savings estimates are

approximately 660 thousand MMBtu and 1.4 million MMBtu . This equates to 5.3 % and 11.0 % of sector

sales in 2017 and 2022. The respective 5

- year and 10

- year Constrained Achievable potential savings

estimate s are approximately 440 thousand MMBtu and 900 thousand MMBtu . This equates to 3.6% and

7.3% of sector sales in 2017 and 2022.

Table 6

- 1 9 : Residential A ch i ev a b l e S avings P o tent i al i n 2017

– Maximum, Base and Constrained Achievable

Scenarios

Summary of Ach ievable Gas Efficiency Potential

Maximum Achievable Base Achievable Constrained Achievable

End Use Energy

Savings

(MMBtu) % of Total Energy

Savings

(MMBtu) % of Total Energy

Savings

(MMBtu) % of Total

Appliances 28,612 3% 13,039 2% 6,897 2%

Electronic s 0 0% 0 0% 0 0%

Lighting

- 192,195

- 18%

- 154,823

- 23%

- 113,904

- 26%

Water Heating 277,808 25% 96,866 15% 81,134 18%

Other 0 0% 0 0% 0 0%

HVAC (Envelope) 743,080 68% 541,402 82% 325,290 73%

HVAC (Equipment) 106,474 10% 51,793 8% 44,029 10%

Behavioral Programs 126,788 12% 112,318 17% 101,114 23%

Total 1,090,567 100% 660,596 100% 444,561 100%

% of Annual Sales

Forecast 8.8% 5.3% 3.6%

46 To the extent possible, the consultants used the current incentives posted on the DCSEU website for the Base

Achievable scenario. The consultants identified incentive amounts for duct sealing, clothes washers, refrigerators and LED

lighting measures. The consultants assumed $10/bulb incentive for LED lighting (the website indicated the rebates for

LED lighting are either $5 or $10). However, for all remaining measures, the consultants assumed a 35% incentive based

on limited information regarding the Home Performance program. For the Constrained Achievable scenario, in general,

the consultants assumed incentives equal to half of the Base Achievable scenario. Refer to Section 6.1.3 for further

dis cussion on the Constrained Achievable scenario incentives.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 57 Table 6

- 20 : Residential A ch i ev a b l e S avings P o tent i al i n 2022

– Maximum, Base and Constrained Achievable

Scenarios

Summary of Achievable Gas Efficiency Potential

Maximum Achievable Base Achievable Constrained Achievable

End Use Energy

Savings

(MMBtu) % of Total Energy

Savings

(MMBtu) % of Total Energy

Savings

(MMBtu) % of Total

Appliances 57,803 3% 27,616 2% 14,808 2%

Electronics 0 0% 0 0% 0 0%

Lighting

- 217,904

- 10%

- 152,774

- 11%

- 116,517

- 13%

Water Heating 524,781 24% 188,672 14% 158,352 17%

Other 0 0% 0 0% 0 0%

HVAC (Envelope) 1,492,986 69% 1,099,417 80% 661,455 73%

HVAC (Equipment) 187,694 9% 94,510 7% 78 ,498 9%

Behavioral Programs 127,139 6% 112,628 8% 108,823 12%

Total 2,172,498 100% 1,370,070 100% 905,419 100%

% of Annual Sales

Forecast 17.5% 11.0% 7.3%



### Figure 6

- 5 shows t h e est

i mated 10

- year cumulative e fficiency savings for the Base Achievable p o tential

scenario, broken out by end use across the e n tire residential sector. The HVAC Envelope end use shows

the la r gest p otenti a l for s avings by a wide margin at nearly 1.1 million MMBtu, or 80% of total s avings.

F i gu r e 6

- 5 : Residential S ector 2022 A c h i ev a b l e P o t e ntial S avings f o r the Base Achievable Scenario, by E n d U s e



### Figure 6

- 6 shows the bre a kdown of estimated savi ng s in 2022 by housing type, low

- income designation

and new construction measures, for t h e Base Achievable potential scenari o

. The savi ngs are largely

coming from existing/tu r nover measures, meaning energy e f ficient equipment is installed in replacement

of existing equipment that has failed

. The existing single

- family attached housing type leads the way with

39 % of savings, followed by 26 % of savings coming from existing single

- family detached homes, and

13 % coming from existing multi

- family homes. New construction measures account for 2 % of total

savings and low

- income measures account for 20 % of total savings

. The low

- income measures rep resent

only those measures which apply strictly to low

- income households, and do not represent the “low

-D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 58 

### income potential” in the District . There is also low

- income potential subsumed by the other 80% of the

savings associated with the “ non

- low

- income ” meas ures . This report does not provide an estimate of the

low

- income potential

.

F i gu r e 6

- 6 : Residential Base Achievable S a v i ngs i n 2022, by Housing Type, Low

- Income Designation and New

Construction Measures



### Table 6

- 21

, Table 6

- 22 and Table 6

- 23 s how s cumula tive energy sa vings for all three achievab l e potential scenarios for each year across the 10

- year time hor i zon for the study, broken out b y end use.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

. Page 59 Table 6

- 2 1 : Cumu l at i ve A nn u al Residential E n e r gy S avings i n the Maximum A c h i ev a b l e P o ten t i al S ce n a r i o, by E n d U s e f o r Washington D.C.

Cumulative Annual MMBtu Savings

– Maximum Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Appliances 5,681 11,381 17,103 22,848 28,612 34,405 40,220 46,062 51,922 57,803

Electronics 0 0 0 0 0 0 0 0 0 0

Lighting

- 39,767

- 79,605

- 116,423

- 153,952

- 192,195

- 231,791

- 237,343

- 245,466

- 231,916

- 217,711

Water Heating 55,238 110,632 166,185 221,910 277,808 326,857 376,076 425,471 475,040 524,781

Other 0 0 0 0 0 0 0 0 0 0

HVAC

(Envelope) 148,094 2 96,456 445,062 593,935 743,080 892,490 1,042,169 1,192,146 1,342,411 1,492,986

HVAC

(Equipment) 21,225 42,487 63,784 85,111 106,474 122,587 138,795 155,053 171,348 187,694

Behavioral

Programs 91,958 109,298 126,655 126,722 126,788 126,856 126,922 126,994 127,066 127,139

Total 282,429 490,650 702,365 896,573 1,090,567 1,271,404 1,486,839 1,700,260 1,935,871 2,172,692

% of Annual

Sales Forecast 2.3% 4.0% 5.7% 7.2% 8.8% 10.2% 12.0% 13.7% 15.6% 17.5%

Table 6

- 22 : Cumu l at i ve A nn u al Residential E n e r gy S avi ngs i n the Base Achievable P o ten t i al S ce n a r i o, by E n d U s e f o r Washington D.C.

Cumulative Annual MMBtu Savings

– Base Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Appliances 2,326 4,794 7,405 10,153 13,039 15,933 18,839 21,754 24,681 27,616

Electronics 0 0 0 0 0 0 0 0 0 0

Lighting

- 29,220

- 61,879

- 93,536

- 124,517

- 154,823

- 183,707

- 184,928

- 179,786

- 165,825

- 152,580

Water Heating 14,476 32,202 53,231 74,779 96,866 115,440 133,898 152,251 170,511 188,672

Other 0 0 0 0 0 0 0 0 0 0

HVAC

(Envelope) 106,684 214,325 322,663 431,686 541,402 652,007 763,199 874,999 986,969 1,099,417

HVAC

(Equipment) 9,087 18,816 29,106 40,143 51,793 59,911 68,272 76,825 85,582 94,510

Behavioral

Programs 35,600 65,289 99,305 107,956 112,31 8 112,376 112,437 112,497 112,564 112,628

Total 138,952 273,545 418,174 540,200 660,596 771,959 911,718 1,058,541 1,214,482 1,370,263

% of Annual

Sales Forecast 1.1% 2.2% 3.4% 4.4% 5.3% 6.2% 7.3% 8.5% 9.8% 11.0%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

. Page 60 Table 6

- 23 : Cumu l at i ve A nn u al Resident ial E n e r gy S avings i n the Constrained Achievable P o ten t i al S ce n a r i o, by E n d U s e f o r Washington D.C.

Cumulative Annual MMBtu Savings

– Constrained Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Appliances 1,197 2,490 3,87 3 5,339 6,897 8,462 10,036 11,621 13,212 14,808

Electronics 0 0 0 0 0 0 0 0 0 0

Lighting

- 19,359

- 43,082

- 67,365

- 90,970

- 113,904

- 135,700

- 139,645

- 137,024

- 126,394

- 116,334

Water Heating 12,429 27,462 45,104 63,000 81,134 96,806 112,325 127,696 143,0 41 158,352

Other 0 0 0 0 0 0 0 0 0 0

HVAC

(Envelope) 63,977 128,414 193,590 259,213 325,290 391,768 458,650 525,953 593,660 661,455

HVAC

(Equipment) 7,736 16,054 24,810 34,135 44,029 50,579 57,266 64,197 71,312 78,498

Behavioral

Programs 33,172 58,462 86,233 93,665 101,114 106,110 108,640 108,700 108,761 108,823

Total 99,153 189,800 286,245 364,381 444,561 518,024 607,271 701,141 803,592 905,601

% of Annual

Sales Forecast 0.8% 1.5% 2.3% 2.9% 3.6% 4.2% 4.9% 5.6% 6.5% 7.3%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 61 6.2.4 

### Residential Savings Summ ary



### Table 6

- 24 provides a n end

- use breakdown of the residential natural gas savings potential estimates for

technical and economic potential, and each of the three achievable potential scenarios. The table

indicates how the savings potential decreases syst ematically from the technical potential scenario to the

Constrained Achievable potential scenario as additional limiting factors such as cost

- effectiveness

requirements and anticipated market adoption at given funding levels are introduced.

Table 6

- 24 : Br eakdown of Residential Cumulative Annual Gas Savings Potential for Technical, Economic and

Achievable Potential, by E n d U s e f o r Washington D.C.

End Use Technical

Potential

(MMBtu) Economic

Potential

(MMBtu) Max.

Achievable

Potential

(MMBtu) Base

Achievabl e

Potential

(MMBtu) Constrained

Achievable

Scenario

(MMBtu)

Appliances

ENERGY STAR

Clothes Washers 76,905 76,905 56,038 26,086 13,639

ENERGY STAR

Dishwashers 2,236 2,236 1,766 1,530 1,169

Lighting

Specialty CFL

Bulbs (160,788) (160,788) (115 ,979) (101,358) (77,413)

Standard Screw

- In

CFL Bulbs (83,329) (83,329) (39,624) (39,624) (30,002)

LED Screw

- In

Bulbs (56,983) (56,983) (54,654) (4,145) (1,881)

Common Area

Lighting (10,939) (10,939) (7,648) (7,648) (7,221)

Exterior Lighting 0 0 0 0 0

Water Heating

Heat Pump Water

Heater (36,194) (54,283) (42,794) (11,102) (9,051)

Solar Water

Heating 216,714 0 0 0 0

Gas Water Heater 546,020 571,012 358,466 54,919 37,547

Tank Wrap 0 0 0 0 0

Pipe Wrap 63,431 63,431 50,064 30,62 0 27,510

Low Flow

Showerheads 156,378 156,378 123,418 93,980 88,826

Low Flow Faucet

Aerators 49,172 49,172 35,628 20,255 13,520

HVAC (Envelope)

Ceiling/Attic

Insulation 323,661 234,105 189,364 178,422 60,831

Wall Insulation 508,727 5 08,727 410,645 394,351 187,570

Floor Insulation 101,382 101,382 80,032 27,737 22,304

Air Sealing 328,365 328,365 258,298 132,534 51,384

Duct Sealing 97,144 97,144 76,660 38,473 20,857

ENERGY STAR

Windows 373,397 373,397 121,621 42 ,945 36,103

Radiant Barriers 10,958 10,958 8,648 1,096 163D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 62 End Use Technical

Potential

(MMBtu) Economic

Potential

(MMBtu) Max.

Achievable

Potential

(MMBtu) Base

Achievabl e

Potential

(MMBtu) Constrained

Achievable

Scenario

(MMBtu)

Low Income

Weatherization

Package 356,815 356,815 280,164 280,164 280,164

New Homes

Construction

Package 85,599 85,599 67,553 3,694 2,078

HVAC (Equipment)

Tune

- Up 49,969 41,5 95 26,508 23,975 21,915

Programmable

Thermostats 44,432 35,000 18,710 11,636 8,783

Efficient Furnaces 354,164 295,271 112,102 45,532 38,571

Efficient Boiler 143,434 84,610 30,373 13,367 9,229

Behavioral Programs

Direct Feedback

(In

- Home Energy

Display) 66,004 66,004 52,282 45,977 44,327

Indirect Feedback

(Monthly Energy

Use Reports) 97,120 97,120 74,856 66,651 64,496

Total 3,703,794 3,268,903 2,172,498 1,370,070 905,419

% of Annual 2022

Sales Forecast 29.8% 26.3% 17.5% 1 1.0% 7.3%

Note: Measures in the above Table with “0” achievable potential are ones that did not pass the SCT Test.



### 6.3 A CHIEVABLE 

### P OTENTIAL 

### B ENEFITS 

### & C OSTS



### The societal cost test (SCT) measures the net ben e fits of the en e rgy efficie n cy program for a region o r

service area as a whole. C o sts included in t h e SCT a r e costs to purcha s e and in s tall t h e e nergy e f ficiency

measure and overhead co s ts of running the energy efficiency program. The b e nefits included are the

avoided costs of energy and capacity, as well as a 30% benefits adder to account for externalities such as

improved health and reduced environmental degradation

. Tables 6

- 25 and 6

- 2 6 below provide the

present value of benefits and c osts of t he Societal Cost Test for the 5

- year a nd 1 0

- year perio d s for

all three achievable potential s cenarios.

Table 6

- 25 : 5

- Y e a r SCT R a t i os f o r A ch i e va bl e P o tent i al S ce n a r i o s

– Residential S ector On l y

5

- year SCT Benefits SCT Costs SCT Ratio

Maximum Achievable $1,205,331,346 $309,119,646 3.90

Base Achievable $770,900,69 1 $173,244,109 4.45

Constrained Achievable $565,905,304 $139,995,197 4.04

Table 6

- 2 6 : 10

- Y e a r SCT R a t i os f o r A ch i e va bl e P o tent i al S ce n a r i o s

– Residential S ector On l y

10

- year SCT Benefits SCT Costs SCT Ratio

Maximum Achievable $2,445,641,800 $559,704,04 2 4.37

Base Achievable $1,613,767,915 $327,224,535 4.93

Constrained Achievable $1,192,219,514 $266,337,151 4.48D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 63D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 6 4 

# 7 N O N



# - R

E S I D E N T I A L 

# E L E C T R I C 

# A N D 

# N A T U R A L 

# G A S



# E N E R G Y 

# E F F I C I E N C Y 

# P O T E N T I A L 

# E S T I M A T E S

This section provides electric and natural gas energy effic iency potential estimates for the n o n

residential sec t or in Washington D.C. which includes all commercial and institutional buildings.

Estimates of technical, econom i c and a c hievable potential are first presented for the entire non

residential sector and t hen an estimate of institutional sector savings potential is presented. Separate

sections are listed below for electric and natural gas.



### 7.1 N ON



### - R ESIDENTIAL 

### E LECTRIC



### According to 2010 historical sales data, the residential sector accounts for approximately 9 0% of total

customers but only 18% of total energy sales while the commercial sector accounts for only 10% of total

customers but almost 80% of all kWh sales. Not only does the commercial sector constitute the greatest

portion of total annual kWh sales, it also consumes the most energy on a per customer basis. The

average commercial facility consumes roughly 348,000 kWh annually. Comparatively, the average

residential consumer uses approximately 9,300 kWh per year. From 2001

- 2010, the commercial section

in the District grew at a compound rate of 0.61%. For this study, commercial MWh is estimated to

increase 0.81% annually based upon the January 2013 Load Forecast Report. 47



### 7.1.1 Electric Energy Efficiency Measures Examined



### For the n o n

- residential s e ctor, there we re 129 unique energy efficiency measure s in c luded in the ener g y

savin g s potential analysis. Table 7

- 1 provides a br i ef desc r iption of the t y p e s of measures included f or

each end use in t h e non

- residential sector

. T h e list of me a sures was d eveloped ba s ed on a review

of t he DCSEU TRM and m e asures found in other no n

- residential potential studie s

. For each measure,

the analysis considered incremental costs, e n ergy a nd demand savings, a n d useful m easure life.

Ta bl e 7

- 1 : Types of Mea s u r es I n c l uded i n the Non

- Residential S ector A n al y s i s

End Use Type End Use Description Measures Included

Compressed Air Compressor Equipment

 Air

- Entraining Air Nozzles

 Low Pressure Drop

- Filters

 Receiver Capacity Addition

 Efficient Air Compressors

 Automatic Drains

 Cycling D ryers

Computers & Office Equipment Equipment Improvements

 High Efficient Office Equipment

Cooking Cooking Equipment Improvements

 Efficient Cooking Equipment

 Demand Ventilation Control

Lighting Lighting Improvements

 Efficient Lighting Equipment

 Fixture R etrofits

 Ballast Replacement

 Premium Efficiency T8 and T5

 High Bay Lighting Equipment

 LED Fixtures

 CFL Retrofits

47 PJM Load Forecast Report, January 2013. http://www.pjm.com/~/media/documents/reports/2013

- l oad

- forecast

report.ashx#page=87

.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 65 End Use Type End Use Description Measures Included

 Lighting Controls

 Efficient Design for New Construction

Pools  Solar Water Heating

 Heat Pump Heaters and Controls

 Efficient Equipment

Refri geration Refrigeration Improvements

 Anti

- Sweat Heat Controls

 Refrigerated Case Covers

 Upgrades Motors and Controls

 High Efficiency Equipment

 Variable Frequency Drives on Motors

 Efficient Lighting

 Vending Misers

 Compressors

 Heat Recovery

 Economizers

Space Cooling Cooling System Upgrades

 Cooling Equipment Upgrades

 Improved Controls

 Building Shell Upgrades

 Economizers

 Re

- Commissioning

 Duct Sealing

Space Heating Heating System Improvements

 Building Envelope Improvements

 Thermostat Upgrades

 Heating Equipment U pgrades

 Duct Sealing

Transformers Transformer Equipment

 Efficient Transformers

Ventilation Ventilation Equipment

 Variable Speed Drive Controls

 Dual Enthalpy Economizer

 Demand

- Controlled Ventilation

 Electronically

- Commutated Permanent

 Magnet Motors (ECPM s

 Improved Duct Sealing

 High Volume Low Speed Fans

Water Heating Water Heating Improvements

 High Efficiency Equipment

 Low Flow Equipment

 Heat Recovery Units

 Solar Water Heaters



### 7.1.2 Technical and Economic Potential Electric Savings



### This section presents esti m ates for electric technical, econom i c, and a chievable savings potential for the

no n

- res i denti a l sector (commercial and i nstitutional combined). Each of the ta b les in the technical,

econom i c and achievable sections pr e sent the respective poten ti al for effi ciency savin g s expressed as

cumulative s a

vings (MWh) and percentage o f sales. Data is provided for a 5 and 10

- year hori z on f or Washington D.C

.

This energy efficiency p o tential study considers t h e impacts of the Energy and Independence and

Security Act (EI S A) as an improving code s t andard f or the no n

- resid e ntial sec t or. EISA improves t h eD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 66 

### baseline efficiency of co m pact fluorescent l amps (C F L )

, general servi c e fluores c ent lamps (GSFL )

, hi g h

intensity disch a rge (H I D) l amps and ballasts a nd mo t ors, all a p plicab le i n the n o n

- residential se c tor.



### S U MM A RY O F 

### F I ND I NG S



### Figure 7

- 1 illustrates the estimated savings potential in Washington D.C. f or each of the scenarios

included in this study.

F i gu r e 7

- 1: S umma r

y of N o n

- Re si dential E n e r gy Effic i e n cy P o tent i al as a % of S a l es F or ec as ts



### Expressed as the cumulati v e 5

- year savings, the theo re tical technical s avings pot e ntial is 25 % of

forecasted 2017 non

- residential sale s . 5

- year economic potential scenario s a vings is 24.2% and the Max

Achievabl e potential (100% incentive levels) is 17. 2 % of sect o r sales. The Base Achievable and

Constrained Achievable scenarios 5

- year potential are 12.2% and 10.7% of sales respectively. The 10

-

y e ar savings technical poten tial is 44. 7 % of s ector sales. E c onomic potential is 42.9 % of sales ; Max

Achievable potential is 29. 7 %, while Base Achievable potential scen a rio is est i mated to be 21. 7 % ba s ed

on an i n cent

i ve level of 50 percent

. Constrained Achievable potential is 18.9% of sect o r sales based on

an incentive lev el of 50 percent with a 25% of incremental cost cap

.

Table 7

- 2 shows the savin g s from the In s titution a l se c tor as a percent a ge of total no n

- residential sales f o r

the three scenarios that were modeled. The 5

- yr technical potential for the I nstit u tional sec tor is 5.5%

, and the 10

- yr technical potential is 9.8%

.

Ta bl e 7

- 2 : I ns t i tuti o n a l S avi n gs as a Pe r ce n tage of N on

- Re si dential Sales

Institutional Electric Savings

5 yr. Inst. Savings

(MWh) 5 yr % of

Sales 10 yr. Inst.

Savings

(MWh) 10 yr %

of Sales

Te chnical 556,639 5.5% 1,026,683 9.8%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 67 Institutional Electric Savings

Economic 533,294 5.3% 983,624 9.4%

Max Achievable 370,395 3.7% 683,168 6.5%

Base Case Achievable 267,613 2.7% 493,595 4.7%

Constrained Achievable 232,745 2.3% 429,281 4.1%

Non

- Res Sales 10,092,409 10,498,148



### T E C H N I C AL 

### P O T E N TI AL



### Technic a l poten t

ial repre s ents the quant

i ficati o n of savings that can be real i zed if energ y

- e fficien c y

measures passing the qua l i t ative screening are a pplied in all feasible inst a nces, re g ardless of cost. Tab l e 7

-

3 shows that i t is tec h ni c ally feasible to more than 2 .5 million MWh i n th e no n

- residential sector

between 2013 to 201 7, and approximately 4.7 million MWh during the 10 year period from 2013 to 2022

across Washington D.C., represent i ng 25 % of 5

- year no n

- resident i al sale s

, and 44 % of 10

- year non

residential sales. Lig h t

i ng represents the majority of the potential at 41 % of 10

- yr savings

, while water

heating, cooking and other repres e nt the smallest share s, each with less than 1 percent of 10

- yr savings

. Table 7

- 4 shows the demand sa vings potential in 2017 and 2022. The five and ten year summer peak

demand savings potential is 423 MW and 787 MW, respectively, which is 22.0 % and 39.3 % of the peak

forecast. The five and ten year winter peak demand savings potential is 451 MW and 848 MW,

respectively, which is 31.8 % and 57.4 % of the peak forecast

.

Table 7

- 3 : Non

- Residential Sector Technical Potential S avings By End Use

Non

- Residential Technical Potential Savings by End Use

End Use 2017 Energy

Savings (MWh) % of

2017

Total 2022 Energy

Sa vings (MWh) % of 2022

Total

Lighting 944,290 37% 1,917,912 41%

Ventilation 310,334 12% 1,098,849 23%

Refrigeration 54,388 2% 56,832 1%

Space Cooling 689,436 27% 865,906 18%

Office Equipment 131,468 5% 124,390 3%

Space Heating 357,713 14% 412,561 9%

Water Heating 0 0% 140,924 3%

Process 41,896 2% 39,289 1%

Other 10,155 0% 24,201 1%

Cooking 6,116 0% 14,685 0%

Total 2,545,797 100% 4,695,550 100%

% of Annual Sales Forecast 25.2% 44.7%

Table 7

- 4 : Non

- Residential S ector Tech n i c a l P o tent i al Demand S avi n gs

Non

- Residential Technical Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 423 787 451 848

% of Peak 22.0% 39.3% 31.8% 57.4%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 68 

### E CONO MI C 

### P O T E N TI AL



### Economic potential is a subset of technical potential, which only accounts for measures that are cost

effective, based on a screening using the Societal Cost Test (SCT), when calculating the savings potential.

The SCT was used for this study because it is mandated by the Distric t to be the cost

- effectiveness test

used when considering energy efficiency programs in Washington D

. C. The test includes a 30% adder to

electric and natural gas benefits

.

Table 7

- 5 s h ows that it is economically f e asi b le to s a

ve slightly less than 2.5 mi l lion MWh d uring the 5

-

year period from 2013 to 2017 and to save just under 4.5 million M W h during the 10

- year period from

2013 t o 2022, representing 24.2% a nd 4 2

. 5 % of non

- resi d ent i al sales respectively. L

ight i ng

, space cooling

and space heating make up a majority of the savi n gs

. Table 7

- 6 shows the demand savings potential in

2017 and 2022. The five and ten year summer peak demand savings potential is 405 MW and 754 MW,

respectively, which is 21.0 % and 37.6 % of the peak forecast. The five and ten year wint er peak demand

savings potential is 432 MW and 812 MW, respectively, which is 30.4 % and 55.0 % of the peak forecast

Table 7

- 5: Non

- Residential Sector Economic Potential Savings By End Use

Non

- Residential Economic Potential Savings by End Use

End Use 2017 Energy

Savings (MWh) % of

2017

Total 2022 Energy

Savings (MWh) % of 2022

Total

Lighting 904,745 37% 1,817,196 40%

Ventilation 297,337 12% 1,096,520 24%

Refrigeration 52,110 2% 55,913 1%

Space Cooling 660,563 27% 809,855 18%

Office Equipment 125,963 5% 120,085 3%

Space Heating 342,733 14% 383,387 9%

Water Heating 0 0% 139,876 3%

Process 40,142 2% 39,289 1%

Other 9,730 0% 24,201 1%

Cooking 5,860 0% 12,583 0%

Total 2,439,182 100% 4,498,906 100%

% of Annual Sales Forecast 24.2% 42.9%

Table 7

- 6 : Non

- Residential S ector Economic P o tent i al Demand S avi n gs

Non

- Residential Economic Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 405 754 432 812

% of Peak 21.0% 37.6% 30.4% 55.0%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 69 

### 7.1.3 Achievable Potential Savings in the Non

- Residential Sector



### Achievable potential is an estimate of energy savings that can feasibly be achieved given market barriers

and equipment replacement cycles. This study estimated achievable potential for th ree scenarios

corresponding to varying incentive levels provided to end

- use consumers. The Maximum Achievable

potential scenario is based on the assumption that incentives are equal to 100% of incremental costs.

The Base Achievable potential scenario is ba sed on the assumption that incentives are equal to the

current level of incentives offered by the DCSEU. The Constrained Achievable potential scenario is

based on the assumption that incentives are equal to half of the Base Achievable scenario. An e xceptio n to this assumption is an assumed incentive cap of 2 5% of incremental cost in the Constrained

Achievable scenario.

Table 7

- 7 and Table 7

- 8 show the estimated savings for the achievable scenarios over 5 and 10 year

horizons. Under the Max Achievable sce n a rio it is feasib l e to save 1.7 mill i on MWh during the 5 year

period from 2013 to 2017 across t he region, r epresenting 17.2% of sector sales. Base Case achievable

scenario can save 1.2 MWh at 12.2% of sector sales. Under the Constrained Achievable scenario it is

feasible to save j u st over 1.0 milli o n MWh bas e d on the lower in c entive l evel. The 10

- year savings for

achievable potential scenario is 29.5%, 21.5% and 18.8% of s e ctor sales for each of the achievable

scenarios respecti v el y

. The ten year demand savi ngs estimates in the Base Achievable scenario are 391

MW in the summer and 346 MW in the winter, which represents 19.5 % and 23.4 % of the peak demand

forecast for the respective summer and winter seasons in 2022

.

Table 7

- 7 : Non

- Residential Maximum Achievab le Energy Savings by End Use

Non

- Residential Maximum Achievable Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Lighting 629,511 36% 1,248,152 40%

Ventilation 430,194 25% 766,334 25%

Refri geration 33,108 2% 51,791 2%

Space Cooling 374,517 22% 605,489 19%

Office Equipment 65,883 4% 110,493 4%

Space Heating 101,861 6% 167,042 5%

Water Heating 64,983 4% 108,750 3%

Process 21,752 1% 36,226 1%

Other 7,898 0% 14,657 0%

Cooking 4,890 0% 9,7 81 0%

Total 1,734,597 100% 3,118,713 100%

% of Annual Sales

Forecast 17.2% 29.7%

Table 7

- 8 : Non

- Residential Maximum Achievable Demand Savings

Non

- Residential Maximum Achievable Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 288 523 307 563

% of Peak 15.0% 26.1% 21.7% 38.1%

Table 7

- 9 : Non

- Residential Base Achievable Energy Savings by End Use

Non

- Residential Base Achievable Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Lighting 457,119 37% 912,529 40%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 70 Non

- Residential Base Achievable Potential Savings by End Use

Ventilation 361,744 29% 659,351 29%

Refrigeration 26,329 2% 41,502 2%

Space Cooling 252,681 21% 428,065 19%

Office Equipment 63,642 5% 106,165 5%

Space Hea ting 9,846 1% 17,870 1%

Water Heating 32,869 3% 59,426 3%

Process 20,281 2% 33,287 1%

Other 4,916 0% 8,940 0%

Cooking 2,961 0% 5,922 0%

Total 1,232,388 100% 2,273,055 100%

% of Annual Sales

Forecast 12.2% 21.7%

Table 7

- 10 : Non

- Residential Base Achievable Demand Savings

Non

- Residential Base Achievable Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 213 391 183 346

% of Peak 11.1% 19.5% 12.9% 23.4%

Table 7

- 11 : Non

- Resid ential Constrained Achievable Energy Savings by End Use

Non

- Residential Constrained Achievable Potential Savings by End Use

2017 % of 2017 2022 % of 2022

End Use Energy (MWh) Savings Energy (MWh) Savings

Lighting 353,506 33% 706,175 36%

Ventilation 3 41,101 31% 623,637 31%

Refrigeration 25,848 2% 40,709 2%

Space Cooling 252,438 23% 426,413 21%

Office Equipment 56,119 5% 91,170 5%

Space Heating 193 0% 276 0%

Water Heating 29,904 3% 53,856 3%

Process 18,661 2% 30,080 2%

Other 3,676 0% 6,755 0%

Co oking 2,617 0% 5,233 0%

Total 1,084,062 100% 1,984,304 100%

% of Annual Sales

Forecast 10.7% 18.9%

Table 7

- 12 : Non

- Residential Constrained Achievable Demand Savings

Non

- Residential Constrained Achievable Potential Savings Demand Savings

Summer Peak Demand Winter Peak Demand

2017 2022 2017 2022

Summary MW MW MW MW

Total 151 336 133 318

% of Peak 7.8% 16.8% 9.4% 21.5%



### Figure 7

- 2 shows t h e est

i mated 10

- year cumula t

ive e fficiency savings p otential broken out by end use

across the e n tire no n

- r e si d ential sector. The light i ng e nd use shows the la r

gest p otenti a l for s avings by a

wide margin at just over 0.9 million MWh, or 4 0 % of total s avings , in the Base Achievable scenario

.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 71 Figure 7

- 2: Non

- Residential Sector 2022 Base Case Achievable Potenti al Savings for by End Use



### Figure 7

- 3 shows the bre a kdown of estimated savi ng s in 2022 by vintage for t h e Base Achievable

scenario. The vast m a jority of savings come from existing/tu r nover measures, meaning energy e f ficient

equipment is installed in repla cement of existing equipment that has failed, wi t h less than 4% of savings

potenti a l coming from new c o nstru c tion. The institutional savings represent all District and US

Government building and their respective contributions to each building types. The b uilding types

shown in this figure are Non

- Institutional Office properties.

Figure 7

- 3: Non

- Residential Base Case Savings in 2022 by Vintage



### Table 7

- 13 , Table 7

- 14 and Table 7

- 15 s how cumulative energy sa vings for all achievab l e scenari os

for each year across the 10

- year hor i zon for the study, broken out b y end use.D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 72 Table 7

- 13: Cumulative Annual Non

- Residential Energy Savings in Max Achievable Potential Scenario by End Use for Washington D.C.

Cumulative Annual MWh Savings

– Maximum Achi evable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Lighting 123,457 249,630 377,163 504,695 629,511 754,326 877,782 1,001,239 1,124,696 1,248,152

Ventilation 64,876 153,267 253,414 353,561 430,194 506,828 571,704 636,581 701,457 766,334

Refrigeration 3,376 10,358 19,143 27,929 33,108 38,287 41,663 45,039 48,415 51,791

Space Cooling 42,606 121,098 217,533 313,968 374,517 435,066 477,671 520,277 562,883 605,489

Office

Equipment 8,390 22,099 38,466 54,834 65,883 76,933 85,323 93, 713 102,103 110,493

Space Heating 12,119 33,408 59,283 85,157 101,861 118,565 130,685 142,804 154,923 167,042

Water Heating 8,223 21,750 37,929 54,108 64,983 75,858 84,081 92,304 100,527 108,750

Process 2,713 7,245 12,687 18,129 21,752 25,375 28,088 30, 801 33,513 36,226

Other 1,323 2,931 4,682 6,433 7,898 9,364 10,687 12,011 13,334 14,657

Cooking 978 1,956 2,934 3,912 4,890 5,868 6,847 7,825 8,803 9,781

Total 268,061 623,743 1,023,234 1,422,726 1,734,597 2,046,469 2,314,530 2,582,591 2,850,652 3,118,7 13

% of Annual

Sales Forecast 2.7% 6.3% 10.3% 14.2% 17.2% 20.1% 22.6% 25.0% 27.4% 29.7%

Table 7

- 14: Cumulative Annual Non

- Resident ial Energy Savings in Base Achievable Potential Scenario by End Use for Washington D.C.

Cumulative Annual MWh Savings

– Bas e Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Lighting 91,039 182,506 274,186 365,866 457,119 548,372 639,411 730,450 821,489 912,529

Ventilation 57,918 131,870 213,840 295,809 361,744 427,679 485,597 543,515 601,433 659,351

Refrigeration 2,756 8,300 15,239 22,178 26,329 30,479 33,234 35,990 38,746 41,502

Space Cooling 33,144 85,613 147,744 209,874 252,681 295,487 328,632 361,776 394,921 428,065

Office

Equipment 7,977 21,233 37,129 53,026 63,642 74,259 82,235 90,212 98,188 106,165

Space Heating 1,559 3,574 5,817 8,059 9,846 11,633 13,192 14,752 16,311 17,870

Water Heating 5,154 11,885 19,406 26,927 32,869 38,812 43,965 49,119 54,273 59,426

Process 2,419 6,657 11,805 16,953 20,281 23,610 26,029 28,448 30,867 33,287D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 73 Cumulative Annual MWh Savings

– Bas e Achievable by End Use

Other 783 1,788 2,905 4,022 4,916 5,810 6,592 7,375 8,158 8,940

Cooking 592 1,184 1,776 2,369 2,961 3,553 4,145 4,737 5,329 5,922

Total 203,341 454,611 729,847 1,005,082 1,232,388 1,459,693 1,663,034 1,866,374 2,069,715 2,273,055

% of Annual

Sales For ecast 2.1% 4.6% 7.3% 10.0% 12.2% 14.4% 16.2% 18.1% 19.9% 21.7%

Table 7

- 15 : Cumulative Annual Non

- Residential Energy Savings in Constrained Achievable Potential Scenario by End Use for Washington D.C.

Cumulative Annual MWh Savings

– Constrained Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Lighting 70,513 141,235 212,062 282,888 353,506 424,123 494,636 565,149 635,662 706,175

Ventilation 55,043 124,727 201,732 278,737 341,101 403,464 458,507 513,550 568,594 623,637

Ref rigeration 2,697 8,142 14,960 21,777 25,848 29,919 32,617 35,314 38,012 40,709

Space

Cooling 32,833 85,283 147,540 209,797 252,438 295,079 327,913 360,746 393,579 426,413

Office

Equipment 6,484 18,234 32,618 47,002 56,119 65,236 71,719 78,203 84,687 91,1 70

Space

Heating 14 55 111 166 193 221 235 249 263 276

Water

Heating 4,642 10,771 17,645 24,518 29,904 35,290 39,931 44,573 49,214 53,856

Process 2,103 6,016 10,835 15,653 18,661 21,669 23,772 25,875 27,977 30,080

Other 601 1,351 2,176 3,000 3,676 4,35 1 4,952 5,553 6,154 6,755

Cooking 523 1,047 1,570 2,093 2,617 3,140 3,663 4,187 4,710 5,233

Total 175,453 396,861 641,246 885,631 1,084,062 1,282,492 1,457,945 1,633,398 1,808,851 1,984,304

% of Annual

Sales

Forecast 1.8% 4.0% 6.5% 8.8% 10.7% 12.6% 14.2 % 15.8% 17.4% 18.9%D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 74 

### 7.1.4 Non

- Residential Savings Summary



### Table 7

- 16 below shows the Electric potential breakdown by measure for technical, economic and all

three achievable scenarios.

Table 7

- 16 Electric Potential by End

- Use and Measure

End Use Technical

Pot ential

(MWh) Economic

Potential

(MWh) Max.

Achievable

(MWh) Base

Achievable

(MWh) Constrained

Achievable

(MWh)

Building Envelope

Energy Efficient Windows 239,961 239,961 69,341 67,475 66,685

Roof Insulation to R

- 18 28,106 0 0 0 0

Ceiling insulation t o R32 25,685 0 0 0 0

Wall Insulation to R12 19,439 0 0 0 0

Below Grade Insulation to R6 11,996 0 0 0 0

Integrated Building Design 44,803 44,803 14,099 8,131 4,937

Compressed Air

Air

- Entraining Air Nozzles 18,937 18,937 17,665 17,665 17,582

Automatic Drains 11,707 11,707 10,678 10,503 7,978

Efficient Air Compressors 3,278 3,278 2,990 2,899 2,460

Cycling Dryers 2,832 2,832 2,580 0 0

Receiver Capacity Addition 1,955 1,955 1,783 1,693 1,578

Low Pressure Drop

- Filters 580 580 530 526 524

Cooking

Energ y Star HE Steamer 4,930 4,930 3,749 3,631 3,564

Energy Star HE Holding Cabinet 4,045 4,045 3,076 609 34

Demand Ventilation Control 1,682 0 0 0 0

HE Combination Oven 1,384 1,384 1,263 0 0

Energy Star High Efficiency Griddle 1,299 1,299 988 988 981

Ener gy Star HE Fryer 670 670 509 499 461

Induction Cooktops 419 0 0 0 0

Energy Star Electric convection oven 256 256 194 194 193

HVAC Controls

EMS install 176,189 176,189 165,167 5,766 5,271

Programmable Thermostats 107,353 107,353 99,496 98,830 98,732

EMS Optimization 11,702 11,702 10,941 0 0

Hotel Guest Room Occupancy Control

System 909 909 570 353 222

Lighting

LED Screw In 293,970 293,970 185,003 181,166 169,558

LED Wallpack 160,493 160,493 101,002 88,264 56,206

Low Glare Recessed T5/HP T8 (repla cing 124,527 124,527 77,346 160 160D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 75 End Use Technical

Pot ential

(MWh) Economic

Potential

(MWh) Max.

Achievable

(MWh) Base

Achievable

(MWh) Constrained

Achievable

(MWh)

T12)

New Fluorescent Fixtures T5/HP T8

reduced wattage (replacing T8) 110,448 110,448 67,397 59,554 18,965

CFL Screw

- in 106,636 106,636 100,590 100,279 99,862

Low Glare Recessed T5/HP T8 Reduced

Wattage (replacing T8) 98,262 98,262 59,961 24 11

High Efficiency Fluorescent Fixture (HP T8

Troffer Replacing T12) 91,139 91,139 56,608 56,121 55,794

LED Outdoor Area Fixture 87,245 87,245 54,905 49,462 35,310

Fluorescent Fixture with Reflectors 83,445 83,445 60,470 46,830 5,010

Lamp & Ballast Retrofit (HPT8 Reduced

Wattage Replacing Standard T8) 68,797 68,797 48,440 13,731 6

High Efficiency Fluorescent Fixture (HP T8

Reduced Wattage Replacing T8) 65,387 65,387 39,900 39,433 38,816

Lamp & Ballast Retrofit (HPT8 Replacing

T12) 61,820 61,820 38,398 37,563 27,425

New Fluorescent Fixtures T5/HP T8

(replacing T12) 55,000 55,000 34,162 71 71

LED Pin Based Lamp 47,043 47,043 29,605 29,243 28,047

High Intensity Fluorescent Fixture

(replacing HID) 40,993 40,993 29,704 7,067 4,90 7

LED Exit Sign 25,368 25,368 15,735 9,699 855

LED Downlight 24,760 24,760 15,582 15,582 11,432

CFL Fixture 10,576 10,576 6,651 6,600 6,229

LED Parking Garage Fixture 9,321 9,321 5,866 5,799 3,693

Induction Fluorescent 23W 2,544 2,544 2,386 1,916 1,26 1

Halogen Infra

- Red Bulb 1,178 1,178 1,105 1,093 1,081

Integrated Ballast MH 25W 850 850 798 788 765

Cold Cathode Downlight 597 597 490 462 390

Ceramic Metal Halide 565 565 353 274 136

Metal Halide Track 565 565 530 230 16

HID Fixture Upgrade

- Puls e Start Metal

Halide 0 0 0 0 0

Pendant Mounted Indirect Fluorescent

Fixtures 115 0 0 0 0

LED Traffic / Pedestrian Signals 0 0 0 0 0

Daylight Dimming 100,601 0 0 0 0

Remote Mounted Occupancy Sensor 60,417 60,417 56,924 53,611 50,653

Switch Mounted Occu pancy Sensor 60,417 60,417 56,924 51,896 43,613

Controls for H.I.F. 45,673 45,673 42,904 20,474 13,079

Controls for HID (Hi/Lo) 18,352 18,352 17,239 3,062 1,093

15% More Efficient Design

- New

Construction 16,871 16,871 10,538 10,313 10,199D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 76 End Use Technical

Pot ential

(MWh) Economic

Potential

(MWh) Max.

Achievable

(MWh) Base

Achievable

(MWh) Constrained

Achievable

(MWh)

30% More Ef

ficient Design

- New

Construction 33,974 33,974 21,230 20,780 20,552

Daylight Dimming

- New Construction 9,963 9,963 9,403 980 980

Space Cooling

Centrifugal Chiller, 0.51 kW/ton, 300 tons 57,767 57,767 21,179 20,232 19,316

Centrifugal Chiller, 0.51 kW /ton, 500 tons 57,767 57,767 21,179 20,232 19,316

Chiller Tune Up/Diagnostics

- 300 ton 22,209 22,209 19,726 19,375 19,322

Chiller Tune Up/Diagnostics

- 500 ton 22,209 22,209 19,726 19,377 19,326

Centrifugal Chiller, Optimal Design, 0.4

kW/ton, 500 tons 7,549 7,549 2,768 2,644 2,524

Improved Duct Sealing 106,162 106,162 49,001 48,408 48,296

High Efficiency AC

- Unitary & Split Systems

(CEE Tier 2) 86,664 86,664 53,885 53,331 53,265

High Efficiency AC

- Unitary & Split Systems

(CEE Tier 1) 65,562 65,56 2 40,217 39,773 39,729

Ductless (mini split) 58,729 58,729 55,081 54,172 53,508

HVAC Advanced Tune

- Up 27,986 27,986 24,857 24,142 22,842

PTAC 1,686 1,686 1,048 709 470

Hotel Guest Room Occupancy Control

System 1,525 1,525 957 949 948

Ventilation

Dual Enthalpy Economizer

- from Fixed

Damper 340,593 340,593 228,386 210,445 199,898

Dual Enthalpy Economizer

- from Dry Bulb 247,704 247,704 166,099 164,178 161,894

Demand

- Controlled Ventilation 113,627 113,627 69,787 61,783 55,454

Variable Speed Drive Co ntrol, 40 HP 85,345 85,345 79,993 74,738 73,074

Variable Speed Drive Control, 5 HP 85,345 85,345 79,993 26,043 17,969

Variable Speed Drive Control, 15 HP 80,181 80,181 75,152 59,563 55,369

Improved Duct Sealing 27,727 27,727 12,798 9,303 6,986

Electron ically

- Commutated Permanent

Magnet Motors (ECPMs) 9,836 9,836 5,125 4,889 4,697

High Volume Low Speed Fans 2,329 0 0 0 0

Space Heating

Hydronic Heat Pump 96,045 96,045 59,059 9,776 0

Ductless (mini split) 85,754 85,754 80,428 276 276

High Efficiency H eat Pump 20,876 20,876 12,806 394 0

Pools

Energy Efficient Pool Pump with controls 5,249 5,249 4,858 4,082 3,000

Heat Pump Pool Heater 2,496 2,496 2,310 1,695 963

Solar Pool Heating 573 573 540 533 529

High efficiency spas/hot tubs 245 245 230 3 1D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 77 End Use Technical

Pot ential

(MWh) Economic

Potential

(MWh) Max.

Achievable

(MWh) Base

Achievable

(MWh) Constrained

Achievable

(MWh)

Wa ter Heating

Heat Pump Water Heater 67,487 67,487 45,362 41,241 37,166

Solar Water Heating System 39,413 39,413 37,094 2,195 2,195

Drain water Heat Recovery Water Heater 5,993 5,993 2,811 10 10

Faucet Aerators 5,880 5,880 5,222 5,131 5,127

Low Flow Pre

- Rinse Spray Nozzle (included

in 2006 Federal Standards) (Electric HW) 5,162 5,162 4,818 4,789 4,785

Commercial Clothes washers

- Water

Heating Savings 3,672 3,672 3,312 0 0

Ozone Commercial laundry System 2,592 2,592 2,230 1,405 656

High Efficiency Ele ctric Water Heater 2,251 2,251 1,271 696 115

Hot Water Circulation Pump Time

- Clock 1,662 1,662 1,507 1,487 1,484

Commercial Dishwasher (Under Counter Hi

Temp, Electric DHW) 1,529 1,529 1,412 1,389 1,375

Booster Water Heater 1,413 1,413 1,331 100 100

Po int of Use Water Heating 1,048 0 0 0 0

Hot Water (DHW) Pipe Insulation 542 542 502 298 158

Commercial Clothes washers

- Non

- Water

Heating Savings 507 507 457 0 0

Commercial Dishwasher (Single Tank

Conveyor Hi

- Temp,

- Electric DHW) 494 494 213 211 210

L ow

- Flow Showerheads 383 383 340 332 331

Refrigeration

H.E. Evaporative Fan Motors 17,109 17,109 16,092 15,928 15,829

Vending Miser for Soft Drink Vending

Machines 7,558 7,558 6,995 6,909 6,891

Zero

- Energy Doors 4,138 4,138 3,907 3,818 3,768

ECM case f

an motors 4,109 4,109 3,849 3,674 3,506

LED Lighting in Refrigeration 3,721 3,721 3,513 383 383

Evaporator Fan Motor Controls 3,042 3,042 2,872 313 313

Discus and Scroll Compressors 2,346 2,346 1,668 51 0

Refrigeration Heat Recovery 2,249 2,249 2,108 109 109

Door Heater Controls 2,214 2,214 2,063 2,038 2,036

Floating Head Pressure Control 1,899 1,899 1,793 1,589 1,288

Commercial Reach

- In Freezer

- Tier 2 1,809 1,809 1,681 1,676 1,664

Commercial Reach

- In Cooler

- Tier 2 1,472 1,472 1,367 1,352 1,31 8

Refrigeration Heat Recovery 1,403 1,403 1,325 144 144

Commercial Ice

- makers 1,287 1,287 1,191 1,191 1,166

Commercial Reach

- In Freezer

- Tier 1 1,140 1,140 1,060 1,060 1,050

Refrigeration Economizer 919 0 0 0 0D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 78 End Use Technical

Pot ential

(MWh) Economic

Potential

(MWh) Max.

Achievable

(MWh) Base

Achievable

(MWh) Constrained

Achievable

(MWh)

Commercial Reach

- In Cooler

- Tier 1 8 50 850 790 790 771

Refrigerated Case Covers 667 667 625 620 620

Efficient low

- temp compressor 303 303 217 0 0

Refrigeration Heat Recovery 0 0 0 0 0

Transformers

Energy Efficient Transformers

- CEE Tier 1 9,429 9,429 2,964 266 266

Energy Efficient Tra nsformers

- CEE Tier 2 2,440 2,440 767 69 69

Computers & Office Equipment

Energy Star office equipment including

computers, monitors, copiers, multi

- function

machines. 62,286 62,286 57,309 53,365 38,570

Energy Efficient "Smart" Power Strip for

PC/Monit or/Printer 57,799 57,799 53,184 52,799 52,668

EZ Save Monitor Power Management

Software 4,305 0 0 0 0

Energy Star Compliant Single Door

Refrigerator 3,261 3,261 2,532 2,292 1,927

Total 4,695,550 4,498,906 3,118,713 2,273,055 1,984,415

% of Annual Sales Forecast 44.7% 42.9% 29.7% 21.7% 18.9%

Note: Measures in the above Table with “0” achievable potential are ones that did not pass the SCT Test.



### 7.2 N ON



### - R ESIDENTIAL 

### N ATURAL 

### G AS 

### P OTENTIAL



### The consultants ’ natural gas consumption forecasts for the residential , commercial and institutional

segments of the District economy indicate that natural gas demand will increase from 33 trillion BTU in

2011 to 37 trillion BTU in 2023 (representing a compound average annual rate of growth of .9%). The

commercial sector is expected to grow at a much faster pace than the residential sector, with a forecasted

average annual growth rate for 2013 to 2023 of 1.18%.

7.2.1 

### Energy Efficiency Measures Examined



### Table 7

- 1 7 provides a br i ef desc r iption of the t y p e s of measures included f or e ach end use in t h e

commercial model. T h e list of me a sures was d eveloped ba s ed on a review of t he DCSEU TRM

and m e asures found in other no n

- residential potential studie s

. Measure data includes incremental costs,

e n ergy a nd demand savings, a n d m ea sure life with persis t ence discounting.

Ta bl e 7

- 1 7 : Mea s u r es a n d Pr ogr a ms I n c l uded i n the Non

- Residential S ector A n al y si s

End Use Type End Use Description Measures/Programs Included

Building Envelope Building Insulation & Air Sealing

 Improved Wall and Ro of/Ceiling

Insulation

 Air Sealing

 Integrated Building Design

 Envelope Only (30% > code)

 Energy Efficient Windows (with triple

glazing and low emissivity)

Cooking Cooking

- Broiling/Frying/Steaming

 High Efficiency Gas Broilers, Fryers andD ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 79 End Use Type End Use Description Measures/Programs Included

Steamers

Cookin g

- Ovens & Ranges

 High Efficiency Gas Rack, Convection,

Combination and Conveyer Ovens and

Power Burner Range

HVAC Controls Building Systems Management

 Retrocommissioning

 Commissioning

 EMS Install

Cross

- Cutting HVAC Controls

 Programmable Thermostat

 Zo ning

 EMS Optimization

Space & Water Heating High Efficiency Boiler, Furnaces &

Unit Heaters  High Efficiency Furnaces, Steam

Boilers, Hot Water Boilers, Infrared

Heaters and Gas Unit Heaters

Space Heating Boiler Controls & Maintenance

 Boiler Reset and O 2 Trim Controls

 Circulation Pump Time Clocks

 Boiler Tune

- Up

Heat Recovery

 Heat Recovery from Air to Air

 Boiler Blowdown Heat Exchanger

(steam)

 Stack Heat Exchanger

 Heat Recovery Water Heater

 Graywater Heat Exchanger/GFX

Hot Water/Steam Pipe Insulation &

Maintenance  Boiler and Water Heater Pipe Insulation

 Steam Trap Replacement

Ventilation & Fans

 Destratification Fans

 Demand Controlled Ventilation and

Exhaust Hood Makeup Air

Water Heating Efficient Hot Water Use

 Faucet Aerator

 Ozone Commercial Laundry System

(Gas HW)

 Wastewater

 Filtration/Reclamation

 Low flow Shower Head

 High Efficiency Clothes Washer

 Low Flow Pre

- Rinse Spray Nozzle

High Efficiency Water Heaters

 High Efficiency Stand Alone

 Indirect

 On

- Demand Tankless

 Combination Water Heaters

Pool Water Heating

 Pool Cover

 High Efficient Gas

 Solar Pool Heater

7.2.2 

### Technical and Economic Potential Natural Gas Savings



### This section presents esti m ates for natural gas technical, econom i c, and a chievable potential for the no n

res i denti a l sector (commercial and i nstitutional combined). Each of the ta b les in the technical, econom i c

and achievable sections pr e sent the respective poten ti al for efficiency savin g s expressed as cumulativeD ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 80 

### s a vings (MMBtu) and percentage o f sales. Data is provided for a 5 and 10

- year hori z on f or Washington

D.C

.



### S U MM A RY O F 

### F I ND I NG S



### Figure 7

- 4 illustrates the estimated savings potential f or each of all the scenarios included in this study.

Figure 7

- 4: Summary of Non

- Residential Energy Efficiency Potential as a % Sales Forecasts



### Exp ressed as the cumulati v e 5

- year savings, the theo re tical technical s avings pot e ntial is 19.9 % of

forecasted 2017 non

- residential sale s . 5

- year economic potential scenario s a vings is 17.9% and the Max

Achievable potential (100% incentive levels) is 15.0 % of sect o r sales. The Base Achievable and

Constrained Achievable scenarios 5

- year potential are 7.2% and 6.5% of sales respectively. The 10

-

y e ar savings technical poten tial is 37.5 % of s ector sales. E c onomic potential is 33.7 % of sales

, Max

Achievable poten tial is 28.3 %, while Base Achievable potential is est i mated to be 13.5 % ba s ed on an

i n cent i ve level of 50 percent. Constrained Achievable is 12.4% of sect o r sales based on an incentive

level of 50 percent with a 25% of incremental cost cap

.

Table 7

- 18 sho ws the savin g s from the In s titution a l se c tor as a percent a ge of total non

- residential sales

for the three scenarios that were modeled. The 5

- yr technical potential for the Institutional sector is

5. 1 %, and the 10

- yr technical potential is 9. 7 %.

Ta bl e 7

- 1 8 : I ns t i tuti o n a l S avi n gs as a Pe r ce n tage of N on

- Residential Sales

Institutional Savings

5

- yr Savings

(MMBtu) % of Sales 10

- yr Savings

(MMBtu) % of Sales

Technical 939,603 5.1% 1,879,207 9.7%

Economic 838,774 4.6% 1,677,548 8.6%

Max Achievable 702,354 3.8% 1,404,708 7.2%

Base Case Achievable 320,024 1.7% 640,048 3.3%

Constrained Achievable 289,560 1.6% 579,119 3.0%D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 81 Institutional Savings

Non

- Res Sales 18,341,033 19,451,555



### T E C H N I C AL 

### P O T E N TI AL



### Technic a l poten t

ial repre s ents the quant

i ficati o n of savings that can be real i zed if energ y

- e fficien c y

measures passing the qua l i t ative screening are a pplied in all feasible inst a nces, re g ardless of cost. Tab l e 7

-

1 9 shows that i t is tec h ni c ally feasible to save more than 3. 6 million MMBtu in th e no n

- residential

sector between 2013 to 2017 and approximately 7. 3 million MMBtu during the 10 year period from 2013

to 2022 a cross Washington D.C., represent i ng just fewer t h an 20% of 5

- year no n

- resident i al sale s

, and 37 .5 % of 10

- year non

- residential sales

. Space heating represents the majority of the potential at 45%

of 10

- yr savings, while cooking and space & water heating repres e nt the smallest share each with less

than 2 percent of 10

- yr savings

.

Ta bl e 7

- 1 9 : N o n

- R esi dential S ector Tech ni c a l P o tent i al MMBtu S avi n gs By End U s e

Non

- Re sidential Technical Potential Savings by End Use

End Use 2017 Energy

Savings (MMBtu) % of 2017

Total 2022 Energy

Savings (MMBtu) % of 2022

Total

Space Heating 1,631,062 45% 3,262,123 45%

Building Envelope 712,444 20% 1,424,888 20%

Water Heating 596,650 16% 1,193,300 16%

HVAC Controls 566,992 16% 1,133,985 16%

Space & Water

Heating 73,985 2% 147,971 2%

Cooking 62,884 2% 125,768 2%

Total 3,644,017 100% 7,288,034 100%

Percent of Annual

Sales Forecast 19.9% 37.5%



### E CONO MI C 

### P O T E N TI AL



### Economic potent

ial is a s u bset of technical potential, which only accounts for measures that are cos t

effective, based on cost effectiveness screening using the Societal Cost Test (SCT). The SCT was used

for this study because it is mandated by the District to be the cos t

- effectiveness test used when

considering energy efficiency programs in Washington D

. C. 48 

### The test includes a 30% adder to electric

and natural gas benefits.

Table 7

- 20 s h ows that it is economically f e asi b le to s a

ve nearly 3 .3 mi l

lion MMBtu d uring the 5 year period from 2013 to 2017, and more than 6 .5 million M MBtu during the 10 year period from 2013 t o 2022, representing 17. 9 % a nd 33. 7 % of non

- resi d ent i al sales respectively. Space heating again make s up a majority of the savi n gs.

Table 7

- 20: Non

- Residen tial Sector Economic Potential MMBtu Savings By End Use

Non

- Residential Economic Potential Savings by End Use

48 The September 2012 “Evaluation Framework” for the District of Columbia Sustainable Efficiency Utility states on page

5

- 2 that the Societal Cost Test is the test to be used for the cost effectiveness screening of all DC SEU energy efficiency

programs.D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 82 Non

- Residential Economic Potential Savings by End Use

End Use 2017 Energy

Savings (MMBtu) % of 2017

Total 2022 Energy

Savings (MMBtu) % of 2022

Total

Space Heating 1,584,395 48% 3,168,790 48%

Build ing Envelope 668,611 20% 1,337,222 20%

Water Heating 564,458 17% 1,128,916 17%

HVAC Controls 320,099 10% 640,197 10%

Space & Water

Heating 73,985 2% 147,971 2%

Cooking 62,884 2% 125,768 2%

Total 3,274,432 100% 6,548,864 100%

Percent of Annual

Sales F orecast 17.9% 33.7%



### 7.2.3 Achievable Potential Savings in the Non

- Residential Sector



### Achievable potential is an estimate of energy savings that can feasibly be achieved given market barriers

and equipment replacement cycles. This study estimated achievable pot ential for three scenarios

corresponding to varying incentive levels provided to end

- use consumers. The Maximum Achievable

potential scenario is based on the assumption that incentives are equal to 100% of incremental costs.

The Base Achievable potential s cenario is based on the assumption that incentives are equal to the

current level of incentives offered by the DCSEU. The Constrained Achievable potential scenario is

based on the assumption that incentives are equal to half of the Base Achievable scenario . An exception

to this assumption is an assumed incentive cap of 25% of incremental cost in the Constrained

Achievable scenario.

Table 7

- 21 and Table 7

- 22 show the estimated savings for the achievable scenarios over 5 and 10 year

horizons. Under the Max A chievable sce n ario it is feasib l e to save nearly 2.8 mill i on MMBtu during the

5 year period from 2013 to 2017 across t he region, r epresenting 15.0 % of sector sales. Base Achievable

scenario can save more than 1

. 3 MMBtu at 7. 2 % of sector sales. Under the Co nstrained Achievable

scenario it is feasible to save 1 .2 milli o n MMBtu bas e d on the lower in c entive l evel. The 10

- year savings

for the three achievable potential scenario s is 28.3 %, 13. 5 % and 12. 4 % of s e ctor sales for each of the

Max, Base and Constrained Achievable scenarios

, respecti v el y

.

Ta bl e 7

- 21: N on

- Re si dential A ch i ev a b l e S avings P o tent i al i n 2017

Summary of Achievable Gas Efficiency Potential

Maximum Achievable Base Achievable Constrained Achievable

End Use Energy

Savings

(MMBtu) % of Total Ener gy Savings

(MMBtu) % of

Total Energy

Savings

(MMBtu) % of

Total

Space Heating 1,451,860 53% 734,575 56% 670,318 56%

Building Envelope 610,917 22% 93,852 7% 72,173 6%

Water Heating 515,246 19% 313,868 24% 289,269 24%

HVAC Controls 115,620 4% 114,345 9% 113,720 9%

Space & Water

Heating 11,503 0% 8,214 1% 6,611 1%

Cooking 49,474 2% 49,474 4% 49,234 4%

Total 2,754,619 100% 1,314,327 100% 1,201,325 100%

Percent of Annual

Sales Forecast 15.0% 7.2% 6.5%D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 83 Table 7

- 22: Non

- Residential Achievable Saving s Potential in 2022

Summary of Achievable Gas Efficiency Potential

Maximum Achievable Base Achievable Constrained Achievable

End Use Energy

Savings

(MMBtu) % of Total Energy

Savings

(MMBtu) % of

Total Energy

Savings

(MMBtu) % of

Total

Space Heating 2,9 03,721 53% 1,469,150 56% 1,340,635 56%

Building Envelope 1,221,833 22% 187,704 7% 144,346 6%

Water Heating 1,030,492 19% 627,735 24% 578,538 24%

HVAC Controls 231,239 4% 228,689 9% 227,440 9%

Space & Water

Heating 23,005 0% 16,428 1% 13,223 1%

Cooking 98,948 2% 98,948 4% 98,469 4%

Total 5,509,238 100% 2,628,654 100% 2,402,651 100%

Percent of Annual

Sales Forecast 28.3% 13.5% 12.4%



### Figure 7

- 5 shows t h e est

i mated 10

- year cumula t

ive e fficiency savings p otential broken out by end use

across the e n tire no n

- r e si d ential sector. The Space Heating e nd use shows the la r gest p otenti a l for

s avings by a wide margin at just u n der 15.2 million MMBtu, or 56% of total s avings , in the Base

Achievable scenario

.

Figure 7

- 5: Non

- Residential Sector 2022 Base Ca se Achievable Potential Savings for by End Use



### Figure 7

- 6 shows the bre a kdown of estimated savi ng s in 2022 by vintage for t h e Base Achievable

scenari o

. The vast m a jority of savings come from existing/tu r nover measures, meaning energy

e f ficient equipment i s installed in replacement of existing equipment that has failed, wi t h less than 5 %

of savings potenti a l coming from new c o nstru c tion.D ISTRICT O F C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 84 Figure 7

- 6 : Non

- Residential Base Case Achievable Savings in 2022 by Vintage



### Table s 7

- 23 , Table 7

- 24 and Table 7

- 25 s how cumulative energy sa vings for all achievab l e

scenarios for each year across the 10

- year hor i zon for the study, broken out b y end use.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 85 Table 7

- 23: Cumulative Annual Non

- Residential Energy Savings in Max Achievable Potential Scenario by End Use for Washington D.C.

Cumulative Annual MMBtu Savings

– Maximum Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Space Heating 290,372 580,744 871,116 1,161,488 1,451,860 1,742,233 2,032,605 2,322,977 2,613,349 2,903,721

Buildi ng Envelope 122,183 244,367 366,550 488,733 610,917 733,100 855,283 977,467 1,099,650 1,221,833

Water Heating 103,049 206,098 309,147 412,197 515,246 618,295 721,344 824,393 927,442 1,030,492

HVAC Controls 23,124 46,248 69,372 92,496 115,620 138,743 161, 867 184,991 208,115 231,239

Space & Water

Heating 2,301 4,601 6,902 9,202 11,503 13,803 16,104 18,404 20,705 23,005

Cooking 9,895 19,790 29,684 39,579 49,474 59,369 69,263 79,158 89,053 98,948

Total 550,924 1,101,848 1,652,771 2,203,695 2,754,619 3,305, 543 3,856,467 4,407,390 4,958,314 5,509,238

% of Annual Sales

Forecast 3.1% 6.2% 9.2% 12.2% 15.0% 17.8% 20.5% 23.2% 25.8% 28.3%

Table 7

- 24: Cumulative Annual Non

- Resident ial Energy Savings in Base Achievable Potential Scenario by End Use for Washington D.C.

Cumulative Annual MMBtu Savings

– Base Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Space Heating 146,915 293,830 440,745 587,660 734,575 881,490 1,028,405 1,175,320 1,322,235 1,469,150

Building Envelope 18,770 37 ,541 56,311 75,082 93,852 112,622 131,393 150,163 168,933 187,704

Water Heating 62,774 125,547 188,321 251,094 313,868 376,641 439,415 502,188 564,962 627,735

HVAC Controls 22,869 45,738 68,607 91,476 114,345 137,214 160,082 182,951 205,820 228,689

Spac e & Water

Heating 1,643 3,286 4,928 6,571 8,214 9,857 11,500 13,143 14,785 16,428

Cooking 9,895 19,790 29,684 39,579 49,474 59,369 69,263 79,158 89,053 98,948

Total 262,865 525,732 788,596 1,051,462 1,314,328 1,577,193 1,840,058 2,102,923 2,365,788 2,628 ,654

% of Annual Sales

Forecast 1.5% 3.0% 4.4% 5.8% 7.2% 8.5% 9.8% 11.1% 12.3% 13.5%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 86 Table 7

- 25: Cumulative Annual Non

- Residential Energy Savings in Constrained Achievable Potential Scenario by End Use for Washington D.C.

Cumulative Annual MMBtu Sav ings

– Constrained Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Space Heating 134,064 268,127 402,191 536,254 670,318 804,381 938,445 1,072,508 1,206,572 1,340,635

Building Envelope 14,435 28,869 43,304 57,738 72,173 8 6,608 101,042 115,477 129,911 144,346

Water Heating 57,854 115,708 173,561 231,415 289,269 347,123 404,976 462,830 520,684 578,538

HVAC Controls 22,744 45,488 68,232 90,976 113,720 136,464 159,208 181,952 204,696 227,440

Space & Water

Heating 1,322 2,64 5 3,967 5,289 6,611 7,934 9,256 10,578 11,900 13,223

Cooking 9,847 19,694 29,541 39,387 49,234 59,081 68,928 78,775 88,622 98,469

Total 240,265 480,531 720,796 961,059 1,201,325 1,441,591 1,681,855 1,922,120 2,162,385 2,402,651

% of Annual Sales

Forecas t 1.4% 2.7% 4.0% 5.3% 6.5% 7.8% 9.0% 10.1% 11.2% 12.4%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 87 

### 7.2.4 Non

- Residential Savings Summary



### Table 7

- 26 below show the Natural Gas potential breakdown by measure for technical, economic and all

three achievable scenarios.

Table 7

- 26: Natural Gas Potential b y End

- Use and Measure

End Use Technical

Potential

(MMBtu) Economic

Potential

(MMBtu) Max.

Achievable

(MMBtu) Base Achievable

(MMBtu) Constrained

Achievable

(MMBtu)

Building Envelope

Improved Wall Insulation (to R12) 365,755 365,755 345,309 37,636 37,63 6

Air Sealing 346,559 346,559 327,186 62,694 38,174

Improved Roof/Ceiling Insulation (to

R32) 243,798 243,798 230,169 25,087 25,087

Triple Glazing Low Emissivity

Windows 228,682 228,682 107,949 11,766 11,766

Integrated Building Design, Envelope

Only ( 30% > code) 152,429 152,429 35,977 4,233 3,921

Double Glazing Low Emissivity

Windows 56,322 0 0 0 0

Improved Below

- Grade Insulation (to

R6) 31,343 0 0 0 0

Cooking

Energy Star Steam Cooker 56,998 56,998 44,843 44,843 44,550

Energy Star Fryer 46,225 46, 225 36,367 36,367 36,276

Energy Star Griddle 12,303 12,303 9,680 9,680 9,616

Energy Star Oven 10,242 10,242 8,058 8,058 8,027

HVAC Controls

Programmable Thermostat 244,931 244,931 231,239 228,689 227,440

Zoning 209,648 209,648 197,929 30,388 23,376

R etrocommissioning 159,631 159,631 150,707 30,753 17,570

EMS Optimization 25,988 25,988 24,535 15,535 10,191

EMS install 486,785 0 0 0 0

Commissioning 7,003 0 0 0 0

Space Heating

Demand Controlled Ventilation 411,370 411,370 388,375 49,481 45,775

Heat Recovery from Air to Air 378,920 378,920 357,738 38,991 38,991

Repair/Replace malfunctioning steam

traps 321,667 321,667 303,686 301,207 301,148

High Efficiency Furnace (<=300,000

Btu/h) (AFUE>=92%) 310,972 310,972 163,105 163,105 155,640

Boiler Reset Controls 294,040 294,040 277,603 141,408 97,611

Boiler blowdown heat exchanger

(steam) 203,388 203,388 192,019 70,563 45,395D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 88 End Use Technical

Potential

(MMBtu) Economic

Potential

(MMBtu) Max.

Achievable

(MMBtu) Base Achievable

(MMBtu) Constrained

Achievable

(MMBtu)

Stack Heat Exchanger (Condensing

Economizer) 182,135 182,135 171,954 169,388 168,446

High Efficiency Steam Boiler

(<=300,000 B tu/h) (AFUE >=82%) 155,222 155,222 58,618 19,874 12,501

Boiler O2 Trim Controls 114,288 114,288 107,899 11,760 11,760

Boiler Heating Pipe Insulation 112,770 112,770 106,466 96,598 91,699

Destratification Fans (HVLS) 98,044 98,044 92,563 10,089 10,089

E xhaust Hood Makeup Air 98,214 98,214 92,724 79,476 73,325

Boiler Tune

- Up 94,768 94,768 89,470 88,692 88,616

Stack Heat Exchanger (Standard

Economizer) 73,636 73,636 69,520 66,982 65,688

Infrared Heater (low intensity

- two

stage) 72,770 72,770 40,413 38 ,534 37,564

High Efficiency Steam Boiler (>300,000

Btu/h) (Th.Eff.>=80%) 72,061 72,061 27,213 12,643 8,851

High Efficiency Hot Water Boiler

(<=300,000 Btu/h) (AFUE =85%

- 90%) 46,244 46,244 21,830 6,418 3,926

Boiler Parallel Positioning 38,170 38,170 36 ,036 3,928 3,928

Insulate steam lines/condensate tank 33,524 33,524 31,650 30,962 30,647

Condensing Boiler (<=300,000 Btu/h)

(AFUE>90%) 30,776 30,776 16,142 4,759 2,912

Condensing Boiler (>300,000 Btu/h)

(Th.eff.=>90%) 9,864 9,864 5,174 4,614 4,341

G as Unit Heater

- Condensing (AFUE

=93%) 9,656 9,656 4,240 702 502

High Efficiency Hot Water Boiler

(>300,000 Btu/h) (Th.eff.=85%

- 90%) 6,291 6,291 2,376 2,217 2,136

Exhaust Hood

- Demand Ventilation 33,121 0 0 0 0

Insulate and Seal Ducts (New Aerosl

Duct Sealing) 60,212 0 0 0 0

Water Heating

Solar pool heater 146,715 146,715 138,514 58,701 30,096

Ozone Commercial Laundry System

(Gas HW) 143,208 143,208 135,203 132,832 131,035

Low flow shower head (1.5 GPM) 121,783 121,783 114,976 113,215 111,997

Wast ewater, Filtration/Reclamation 114,747 114,747 108,333 11,808 11,808

Graywater Heat Exchanger/GFX 95,930 95,930 90,568 16,566 10,567

Pool Cover 95,190 95,190 89,869 89,266 89,214

Circulation Pump Time Clocks 81,079 81,079 76,546 73,033 69,802

Condensin g Stand Alone Commercial

Water Heater (.96 TE/.8 TE) (Baseline

>75000 btu) 65,920 65,920 47,873 5,586 5,218

Heat Recovery Water Heater 62,131 62,131 58,658 57,077 55,683

High Efficiency Clothes Washer 57,528 57,528 49,375 5,381 5,381D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 89 End Use Technical

Potential

(MMBtu) Economic

Potential

(MMBtu) Max.

Achievable

(MMBtu) Base Achievable

(MMBtu) Constrained

Achievable

(MMBtu)

High Efficiency (9 5%) Gas Pool Water

Heater 47,711 47,711 45,044 5,586 4,909

Indirect Water Heater

- Combined

appliance efficiency rating

(CAE)>=85% (EF=.82/.59 EF

Baseline) 33,680 33,680 21,198 19,245 14,820

Faucet aerator 31,809 31,809 30,031 29,835 29,827

Pipe wrap 1 2,564 12,564 11,862 2,865 1,445

Low Flow Pre

- Rinse Spray Nozzle (1.25

gpm) 6,414 6,414 6,056 6,043 6,040

On

- Demand, Tankless Water Heater

(>=.95 EF) (<=200,000 Btu/h) 5,141 5,141 2,427 264 264

On

- Demand, Tankless Water Heater

(.82 EF/.59 EF Baseline) ( <=200,000

BTU/h) 3,768 3,768 1,778 194 194

High Efficiency Stand Alone

Commercial Water Heater (0.67 EF/.59

EF) (Baseline <=75000 Btu) 1,901 1,901 1,381 151 151

On

- Demand, Tankless Water Heater

(.85 TE/.8 TE Baseline) (>200,000

BTU) 1,696 1,696 801 87 87

Solar Water Heating w/gas auxiliary

tank (SEF=1.5) 64,384 0 0 0 0

Space & Water Heating

Combination Water Heater/Boiler

(Condensing)(0.9 EF, 0.9 AFUE) 126,648 126,648 59,784 32,189 19,246

Combination Water Heater/Furnace

(.86 EF, .90 AFUE) 13,569 1 3,569 8,540 8,405 8,309

Combination Water Heater/Boiler

(Non

- Condensing) (0.86 EF, 85 AFUE) 7,754 7,754 3,660 2,206 1,435

Combination Water Heater/Boiler

(Non

- Condensing) (0.86 EF, 85 AFUE)

Retrofit 0 0 0 0 0

Total 7,288,034 6,548,864 5,509,238 2,628,65 4 2,402,651

% of Annual Sales Forecast 37.5% 33.7% 28.3% 13.5% 12.4%

Note: Measures in the above Table with “0” achievable potential are ones that did not pass the SCT Test.



### 7.3 A CHIEVABLE 

### P OTENTIAL 

### B ENEFITS 

### & C OSTS



### The societal cost test (SCT) measures th e net ben e fits of the en e rgy efficie n cy program for a region o r

service area as a whole. C o sts included in t h e SCT a r e costs to purcha s e and in s tall t h e e nergy e f ficiency

measure and overhead co s ts of running the energy efficiency program. The b e nefits inc luded are the

avoided costs of energy and capacity, as well as a 30% benefits adder to account for externalities such as

improved health and reduced environmental degradation

. Tables 7

- 27 and 7

- 28 below provide the

present value of benefits and c osts of t h e Societal Cost Test for the 5

- year a nd 1 0

- year perio d s for

all three achievable potential s cenarios.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 90 Table 7

- 27: 5

- Year SCT Ratios for Achievable Potential Scenarios

– Non

- Residential Sector Only

5

- year SCT Benefits SCT Costs SCT Ratio

Maximum Achiev able $4,957,853,585 $1,048,067,967 4.73

Base Achievable $2,939,805,946 $404,323,886 7.27

Constrained Achievable $2,586,039,443 $325,273,962 7.95

Table 7

- 28: 10

- Year SCT Ratios for Achievable Potential Scenarios

– Non

- Residential Sector Only

10

- year SCT Benefits SCT Costs SCT Ratio

Maximum Achievable $9,330,507,338 $1,821,566,529 5.12

Base Achievable $5,672,286,113 $726,248,449 7.81

Constrained Achievable $4,973,192,834 $580,031,118 8.57D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 91 

# 8 D E M A

N D 

# R E S P O N S E 

# P O T E N T I A L 

# E S T I M A T E S

This section provides ele ctric demand response potential estimates for the residential and commercial

sectors in Washington D.C. Estimates of technical, economic and achievable potential are provided. As

shown in Section 4, summer peak demand is projected to reach 2,739 MW by 202 2, growing at an

average rate of 1% per year. Demand response programs have the potential to target reductions in the

summer peak demand, as described more fully in this section

.



### 8.1 I NTRODUCTION TO 

### D EMAND 

### R ESPONSE



### In an August 2006 report by staff to the Fed eral Energy Regulatory Commission (“FERC”), a definition

of “demand response” was adopted by the Commission. This definition was used by the U.S.

Department of Energy (“DOE”) in its February 2006 report to Congress:

Changes in electric usage by end

- use cus tomers from their normal consumption patterns in response to

changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use

at times of high wholesale market prices or when system reliability is jeopardized

. 49



### In the same August 2006 report, it was noted that demand response is an active response to prices or

incentive payments. The changes in electricity use are designed to be short

- term in nature, centered on

critical hours when demand or market prices are high, or when reserve margins are low. This is

contrasted to energy efficiency programs that are focused on longer

- term responses or reduction in

consumption through the investment in energy efficient equipment or change in behavior.

There are generally two major types of demand response programs: incentive

- based programs and time

based programs. Incentive

- based programs generally involve the utility paying an incentive to a retail

customer to reduce peak demand or allow for direct control of end use app liances. Such programs

include direct load control, interruptible programs, demand buy

- back, and emergency demand response.

Time

- based programs include a suite of rate alternatives known as dynamic pricing. These programs

have rates that incentivize custo mers to reduce loads during certain times of the day and year (critical

peaking hours). Time

- based programs include time

- of

- use, critical peak pricing, and real time pricing

rates.



### 8.2 G ENERAL 

### B ENEFITS OF 

### D EMAND 

### R ESPONSE



### Customer responses under demand respon se programs can either reduce or shift consumption during

high cost periods. While all of the programs evaluated within this project result in reducing the load

requirements of the system during certain peak periods, there are two distinct load impacts tha t can

result.

“Load Shifting”

– Projects that move energy consumption from one time to another (usually during

a single day).

“Peak Clipping”

– Projects that reduce energy demand at certain critical times, with no recovery of

the energy at a later time

.

D emand response can provide the benefit of serving as a substitute for peaking generation resources . In

addition, it can reduce the need for expansion in distribution investment. D emand response also has the

potential to reduce energy supply costs and, in general, electricity price volatility. Finally, demand

response can also serve as supplemental (non

- spinning) operating reserves.

49 U.S. Department of Energy, Benefits of Demand Response in Electricity Markets and Recommendations for Achieving

Them: A Report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005, Febru ary 2006

(February 2006 DOE EPAct Report).D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 92 Figure 8

- 1: Load Shifting and Peak Clipping Programs



### 8.3 D EMAND 

### R ESPONSE 

### M EASURES 

### E XAMINED



### Ten residential and six com mercial demand response measures were evaluated in the potential study.

These represent several of the more typical demand response programs administered by utilities in the

United States and include a mix of incentive

- based and time

- based programs. The l ist below gives a brief

description of each measure examined in the potential study.

 

### Residential Measures

 Air Conditioning Control

– 50% Cycling

– a control switch is placed on the AC unit, giving

the utility the ability to control the AC. The compressor is cycled off for 50% of the

hour.

 Air Conditioning Control

– 75% Cycling

– similar to the 50% cycling case, but the

compressor is turned off for 45 minutes out of each hour of a control event.

 Standard Water Heater Control

– a control switch on an electr ic water heater allows the

utility to turn off the heating element during control periods. This measure assumes a

standard 40

- 50 gallon tank water heater.

 Large Capacity Water Heater Control

– similar to the standard water heater control, this is a

direct control program. This measure is for larger tank sizes, in excess of 60 gallons.

 Pool Pump Control

– the utility installs a direct control switch of swimming pool pumps.

Typically, pool pumps are associated with in

- ground pools. The pump can be shut of f

during critical event hours and allowed to run during off

- peak hours to assure proper

circulation of chemicals.

 Smart Thermostat

– This is a direct control program in which a programmable thermostat

can also be controlled by the utility, allowing the uti lity to remotely adjust the

temperature set point of the thermostat.

 TOU without enabling technology

– this is a simple time

- of

- use rate with two parts, an on

peak and off

- peak rate.

 TOU with enabling technology

– the same TOU rate is considered as above, however, the

customer is also provided with technology that better enables them to respond to price

signals. A display unit is installed in the home that provides price and usage information

to the customer.

 CPP without enabling technology

– a critical pe ak pricing rate is a three part rate. There are

on

- peak and off

- peak energy charges much like a TOU rate. However, during a select

few critical peaking days and hours, the price is much higher to encourage reduction of

loads during peaking conditions. T he price can be as high as $1.00 per kWh for such

critical hours.

 CPP with enabling technology

– The same CPP rate as described above, but with enabling

technology provided to the customer to better enable load reductionsD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 93  

### Commercial Measures

 Control of AC

– much like the residential program, this program represents utility control

over commercial air conditioning units.

 Control of lights

– small

– This program involves the utility having direct control of some

proportion of the lightings in commercial build ings. The small classification is for

smaller applications such as small offices, smaller retail stores, or restaurants.

 Control of lights

– large

– this is the same program as the small light control measure, but is

targeted at larger buildings, such as hospitals, warehouses, or large office or retail spaces.

 CPP rate

– critical peak pricing for commercial buildings

 RTP rate

– a real time pricing rate provides a different price for power in every hour of

the day. Typically, prices are provided to the cus tomer every day for the next

- days’

prices.

 Interruptible

– this is a rate

- based program in which a price incentive is offered to

customers who are able to reduce their loads when control events are called.

Given that all avoided cost benefits are accrued for reductions in the summer peak demand, programs

which target winter demands were excluded from the study. Examples of winter programs include dual

fuel heat pumps and electric thermal storage heating. Furthermore, some programs can be considered

energy efficiency and demand response programs, such as commercial Energy Management Systems

(EMS). In such cases, the program is modeled as part of the energy efficiency potential.



### 8.4 D EMAND 

### R ESPONSE 

### S AVINGS 

### S UMMARY



### This section presents esti m ates for electric t echnical, econom i c, and a chievable potential for demand

response

. Each of the ta b les in the technical, economic and achievable sections pr e sent the respective

poten ti al for demand savin g s expressed as cumulative summer peak demand s a vings (MW), percentage

o f savings by end use, and savings as a percentage of forecast summer peak demand. Data is provided

on a 5

- year and 10

- year time hori z on f or Washington D.C . As with the energy efficiency potential

estimates, the demand response estimates are subject to unc ertainty due to several factors.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 94 F i gu r e 8

- 2: S umma r

y of Demand Response P o tent i al as a % of 2017 and 2022 Summer Peak Demand F o r ec as ts



### The potential estimates are expressed as cumulati v e 5

- year and 10

- year savings, as percentages of the

respective 2017 and 2022 summer peak demand. The technical pot e ntial is 4 3

. 4 % in 2017 and 4 2

. 2 % in

2022. The 5

- year and 10

- year e c onomic potential is 4 3

. 3 % and 4 2

. 2 %

. The slight drop from technical

potential to economic potential indicates that most measu res are cost

- effective. The 5

- year and 10

- year

ach i evable potential savings are: 6.4 % and 12.5 % for the Maximum Achievable s cenario; 3.3 % and

6.5 % for the Base Achievable scenario ; and 1.6 % and 3.0 % for the Constrained Achievable s cenario

. As described ear lier, the achievable scenarios are varied based on the incentive level for each

measure.



### T E C H N I C AL 

### P O T E N TI AL



### Technic a l poten t

ial repre s ents the quant

i ficati o n of savings that can be real i zed if all technologically

available demand response measures are i mmediately adopted in all feasible inst a nces, re g ardless of cost.

Table 8

- 1 shows that i t is tec h ni c ally feasible to save more than 1,100 M W in th e residential

and commercial sectors between 2013 to 2017

, and more than 1,150 MW during the 10 year period

fr om 2013 to 2022 across Washington D.C., represent i ng 43 % of the 5

- year summer peak demand of

2,609 MW, and 4 2 % of 10

- year peak of 2,739 MW. A much greater potential exists in the commercial

sector relative to the residential sector.

Tab le 8

- 1 : Tech n i c a l P o tent i al MW S avi n gs by Sector

Technical Potential Savings by End Use

2017 % of 2017 2022 % of 2022

Sector Demand (MW) Savings Demand (MW) Savings

Residential 171.0 15% 188.8 16%

Commercial &

Industrial 960.6 85% 967.2 84%

Total 1, 131.6 100% 1,155.9 100%

% of Annual Summer

Demand Forecast 43.4% 42.2%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 95 

### In the residential sector, the greatest potential lies with AC control. Other measures that provide

significant technical potential include water heater control, CPP rates, and contr ol of pool pumps. In the

commercial sector, direct control of lighting has the greatest technical potential with dynamic pricing

options following close behind.

Table 8

- 2: Residential Technical Potential MW Savings by Measure

Residential Technical Potenti al Savings by End Use

2017 % of 2017 2022 % of 2022

Sector Demand (MW) Savings Demand (MW) Savings

AC Control 79.6 47% 90.3 48%

WH Control 35.0 20% 36.6 19%

Pool Pump Control 20.1 12% 20.7 11%

Smart Thermostat 8.6 5% 9.8 5%

TOU Rate 1.3 1% 1.4 1%

CPP Rate 26.4 15% 30.0 16%

Total 171.0 100% 188.8 100%

% of Annual Summer

Demand Forecast 6.6% 6.9%

Table 8

- 3: Commercial Technical Potential MW Savings by Measure

Commercial Technical Potential Savings by End Use

2017 % of 2017 2022 % of 2022

Sec tor Demand (MW) Savings Demand (MW) Savings

AC Control 90.6 9% 90.6 9%

Lighting Control 359.8 37% 362.9 37%

CPP Rate 159.4 17% 160.6 17%

RTP Rate 53.1 6% 53.5 6%

Interruptible Rate 297.6 31% 299.7 31%

Total 960.6 100% 967.2 100%

% of Annual Summer

D emand Forecast 36.8% 35.3%



### E CONO MI C 

### P O T E N TI AL



### Economic potential is a s u bset of technical potential, which only accounts for measures that are cos t

effective, based on a screening using the Societal Cost Test (SCT), when calculati n g the savings p o tenti a l.

The SCT was used for this study because it is mandated by the District to be the cost

- effectiveness test

used when considering energy efficiency programs in Washington D

. C. The test includes a 30% adder to

electric and natural gas benefits. The only dem and response program to not pass the SCT was the

residential TOU rate. Therefore, the economic potential is not very different from the technical

potential.

Table 8

- 4 : Economic P o tent i al MW S avi n gs by Sector

Economic Potential Savings by End Use

2017 % of 2017 2022 % of 2022

Sector Demand (MW) Savings Demand (MW) Savings

Residential 169.7 15% 187.3 16%

Nonresidential 960.6 85% 967.2 84%

Total 1,130.3 100% 1,154.5 100%

% of Annual Summer

Demand Forecast 43.3% 42.2%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 96 Table 8

- 5 : Residential Econom ic P o tent i al MW S avi n gs by Measure

Residential Economic Potential Savings by End Use

2017 % of 2017 2022 % of 2022

Sector Demand (MW) Savings Demand (MW) Savings

AC Control 79.6 47% 90.3 48%

WH Control 35.0 20% 36.6 20%

Pool Pump Control 20.1 12% 20 .7 11%

Smart Thermostat 8.6 5% 9.8 5%

CPP Rate 26.4 16% 30.0 16%

Total 169.7 100% 187.3 100%

% of Annual Summer

Demand Forecast 6.5% 6.8%

Table 8

- 6 : Commercial Economic P o tent i al MW S avi n gs by Measure

Commercial Economic Potential Savings by End Use

2017 % of 2017 2022 % of 2022

Sector Demand (MW) Savings Demand (MW) Savings

AC Control 90.6 9% 90.6 9%

Lighting Control 359.8 37% 362.9 37%

CPP Rate 159.4 17% 160.6 17%

RTP Rate 53.1 6% 53.5 6%

Interruptible Rate 297.6 31% 299.7 31%

Total 960.6 100% 967.2 100%

% of Annual Summer

Demand Forecast 36.8% 35.3%



### A CHIEVABLE 

### P O T E N TI AL



### Achievable potential is an estimate of demand savings that can feasibly be achiev e d given market barriers

and equipment replacement cycles. T h is study estimated achiev able potential for three scenari o s correspond i ng to varying incent i ve levels p r ovided to end

- use c onsu m ers. Since participants have no

real costs for demand response, t he Maximum A chievable p otential scenario is based on aggressive

incentive levels, rather than 100% of incremental costs as they are in the energy efficiency analyses . The

Base Achievable p otential scenario is based on the assumption that incentives are equal to the current

level of incentives offered by PEPCO (where available) . The Constraine d Achievable p otential scenario

is based on the assumption that incentives are equal to half of the Base Achievable scenario.

Tables 8

- 7 and through 8

- 12 show the estimated savings for the achievable scenarios over 5 and 10 year

time horizons. The 5

- year and 10

- year Maximum Achievable potential savings estimates are

approximately 167.8 MW and 343.4 MW , respectively . This equates to 6.4 % and 12.5 % of summer peak

demand in 2017 and 2022. The respective 5

- year and 10

- year Base Achievable potential savings es timates

are approximately 86.5 MW and 177.3 MW . This equates to 3.3 % and 6.5 % of summer peak in 2017 and

2022. The respective 5

- year and 10

- year Constrained Achievable potential savings estimates are

approximately 40.7 MW and 83.1 MW . This equates to 1.6 % and 3.0 % of sector sales in 2017 and 2022

.

Table 8

- 7: Demand Response A ch i ev a b l e S avings P o tent i al i n 2017

– Maximum, Base and Constrained

Achievable Scenarios

Summary of Achievable Demand Response PotentialD ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 97 Summary of Achievable Demand Response Potential

5

- year Maximum

Achievable % of

Savings Base

A chievable % of

Savings Constrained

Achievable % of

Savings

Residential 57.8 34.4% 31.1 36.0% 14.5 35.5%

Commercial 110.0 65.5% 55.5 64.1% 26.2 64.5%

Total MW Savings 167.8 100.0% 86.5 100.0% 40.7 100.0%

% of Forecast

Summer Peak 6.4% 3.3% 1.6%

Table 8

- 8: Residential Achievable Potential MW Savings by Measure in 2017

– Maximum, Base and

Constrained Achievable Scenarios

Residential Achievable Potential Savings by End Use

2017

End

- Use Maximum

Achievable % of

Savings Base

Achievable % of

Savings Const rained

Achievable % of

Savings

AC Control 33.6 58.2% 18.49 59.5% 8.41 58.2%

WH Control 3.4 6.0% 1.89 6.1% 0.86 6.0%

Pool Pump Control 2.1 3.6% 1.13 3.6% 0.51 3.5%

Smart Thermostat 4.9 8.5% 2.70 8.7% 1.23 8.5%

CPP Rate 13.8 23.8% 6.89 22.2% 3.44 23.8%

Residential Sub

Total 57.8 100.0% 31.1 100.0% 14.5 100.0%

% of Annual

Summer Demand

Forecast 2.2% 1.2% 0.6%

Table 8

- 9: Commercial Achievable Potential MW Savings by Measure in 2017

– Maximum, Base and

Constrained Achievable Scenarios

Commercial Achieva ble Potential Savings by End Use

2017

End

- Use Maximum

Achievable % of

Savings Base

Achievable % of

Savings Constrained

Achievable % of

Savings

AC Control 9.1 8.2% 5.0 9.0% 2.3 8.6%

Lighting Control 9.0 8.2% 4.5 8.1% 1.8 6.8%

CPP Rate 70.7 64.3% 35.4 63.8% 17.7 67.3%

RTP Rate 2.7 2.4% 1.3 2.4% 0.8 3.0%

Interruptible Rate 18.6 16.9% 9.3 16.8% 3.7 14.2%

Commercial Sub

Total 110.0 100.0% 55.5 100.0% 26.2 100.0%

% of Annual

Summer Demand

Forecast 4.2% 2.1% 1.0%

Table 8

- 10 : Demand Response A ch i ev a b l e S avings P o tent i al i n 2022

– Maximum, Base and Constrained

Achievable Scenarios

Summary of Achievable Demand Response Potential

5

- year Maximum

Achievable % of

Savings Base

Achievable % of

Savings Constrained

Achievable % of

Savings

Residential 122.9 35.8% 66.1 37.3% 30.7 37.0%

Commercial 220.5 64.2% 111.2 62.7% 52.4 63.0%

Total MW Savings 343.4 100.0% 177.3 100.0% 83.1 100.0%

% of Forecast

Summer Peak 12.5% 6.5% 3.0%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 98 Table 8

- 11: Residential Achievable Potential MW Savings by Measure in 2022

– Ma ximum, Base and

Constrained Achievable Scenarios

Residential Achievable Potential Savings by End Use

2022

End

- Use Maximum

Achievable % of

Savings Base

Achievable % of

Savings Constrained

Achievable % of

Savings

AC Control 71.8 58.4% 39.5 59.7% 17.95 58 .4%

WH Control 7.0 5.7% 3.87 5.9% 1.76 5.7%

Pool Pump Control 4.2 3.4% 2.29 3.5% 1.04 3.4%

Smart Thermostat 10.5 8.5% 5.76 8.7% 2.62 8.5%

CPP Rate 29.4 24.0% 14.7 22.3% 7.36 24.0%

Residential Sub

Total 122.9 100.0% 66.1 100.0% 30.7 100.0%

% of Annual

Summer Demand

Forecast 4.5% 2.4% 1.1%

Table 8

- 12: Commercial Achievable Potential MW Savings by Measure in 2022

– Maximum, Base and

Constrained Achievable Scenarios

Commercial Achievable Potential Savings by End Use

2022

End

- Use Maximum

Achievable % of

Savings Base

Achievable % of

Savings Constrained

Achievable % of

Savings

AC Control 18.1 8.2% 10.0 9.0% 4.5 8.7%

Lighting Control 18.0 8.2% 9.0 8.1% 3.6 6.9%

CPP Rate 141.9 64.3% 70.9 63.8% 35.5 67.7%

RTP Rate 5.3 2.4% 2.7 2.4% 1.3 2.5%

Interruptib le Rate 37.2 16.9% 18.6 16.7% 7.4 14.2%

Commercial Sub

Total 220.5 100.0% 111.2 100.0% 52.4 100.0%

% of Annual

Summer Demand

Forecast 8.0% 4.1% 1.9%



### Figure 8

- 3 shows t h e percentage of savings by each measure for the Base Achievable p otential scenario

i n the residential sector. Direct control of air conditioners has the greatest residential potential, followed

by CPP rates. Water heater control provides a greater winter than summer benefit, so the proportion of

water heater control potential in the summe r is lower. Pool pumps provide a good per

- unit kW

reduction, but the market share of pools limits the potential of the program.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 99 Figure 8

- 3: Residential Sector 2022 Achievable Potential Savings for the Base Achievable Scenario, by Measure



### Figure 8

- 4 shows the bre a kdown of estimated savi ng s in 2022 by measure in the commercial sector

. The

dynamic pricing programs offer the greatest potential in the commercial sector. CPP and interruptible

rates provide incentives for nonresidential customer s to alter their operations or otherwise respond to

the price incentives. They can require little investment from the utility, depending on how strong the

price incentive is.

Figure 8

- 4: Commercial Sector 2022 Achievable Potential Savings for the Base Ac hievable Scenario, by

Measure



### Table 8

- 13 , Table 8

- 1 4 and Table 8

- 1 5 s hows cumulative demand sa vings for all three achievab l e potential scenarios for each year across the 10

- year time hor i zon for the study, broken out b y end use.D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 100 Table 8

- 13 : Cumu l at i ve A nn u al Demand Response S avings i n the Maximum A c h i ev a b l e P o ten t i al S ce n a r i o, by

Measure f

o r Washington D.C.

Cumulative Annual MW Savings

- Maximum Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Res AC 6.38 12.93 19.65 26. 54 33.61 40.87 48.31 55.94 63.77 71.80

Res WH 0.68 1.36 2.05 2.74 3.44 4.15 4.86 5.58 6.30 7.03

Res Pool

Pumps 0.41 0.82 1.23 1.64 2.06 2.47 2.89 3.31 3.74 4.16

Res TSTAT 0.93 1.89 2.87 3.87 4.90 5.96 7.05 8.16 9.30 10.47

Res CPP 2.62 5.30 8.06 10.88 1 3.78 16.76 19.81 22.94 26.15 29.44

Com AC 1.81 3.62 5.43 7.24 9.06 10.87 12.68 14.49 16.30 18.11

Com Lights 1.79 3.58 5.38 7.17 8.97 10.77 12.58 14.39 16.19 18.01

Com CPP 14.10 28.22 42.35 56.52 70.69 84.88 99.10 113.33 127.58 141.85

Com RTP 0.53 1.06 1.59 2.13 2.66 3.19 3.72 4.25 4.78 5.31

Com

Interruptible 3.72 7.44 11.16 14.88 18.60 22.32 26.04 29.76 33.48 37.20

Total 32.97 66.21 99.76 133.62 167.77 202.24 237.03 272.14 307.59 343.39

% of Annual

Peak Forecast 1.3% 2.6% 3.9% 5.2% 6.4% 7.7% 8.9% 10. 1% 11.3% 12.5%

Table 8

- 1 4 : Cumu l at i ve A nn u al Demand Response S avings i n the Base A c h i ev a b l e P o ten t i al S ce n a r i o, by

Measure f

o r Washington D.C.

Cumulative Annual MW Savings

- Base Achievable by End Use

End Use 2013 2014 2015 2016 2017 2018 2019 2020 202 1 2022

Res AC 3.51 7.11 10.81 14.60 18.49 22.48 26.57 30.77 35.07 39.49

Res WH 0.37 0.75 1.13 1.51 1.89 2.28 2.67 3.07 3.47 3.87

Res Pool

Pumps 0.22 0.45 0.68 0.90 1.13 1.36 1.59 1.82 2.06 2.29

Res TSTAT 0.51 1.04 1.58 2.13 2.70 3.28 3.88 4.49 5.12 5.7 6

Res CPP 1.31 2.65 4.03 5.44 6.89 8.38 9.91 11.47 13.08 14.72

Com AC 1.00 1.99 2.99 3.98 4.98 5.98 6.97 7.97 8.97 9.96

Com Lights 0.89 1.79 2.69 3.59 4.49 5.39 6.29 7.19 8.10 9.00

Com CPP 7.05 14.11 21.17 28.26 35.35 42.44 49.55 56.66 63.79 70.93

Com RTP 0.27 0.53 0.80 1.06 1.33 1.59 1.86 2.13 2.39 2.66

Com

Interruptible 1.86 3.72 5.58 7.44 9.30 11.16 13.02 14.88 16.74 18.60

Total 17.00 34.14 51.44 68.92 86.54 104.34 122.31 140.45 158.77 177.28

% of Annual

Peak Forecast 0.7% 1.3% 2.0% 2.7% 3.3% 4.0 % 4.6% 5.2% 5.9% 6.5%

Table 8

- 1 5 : Cumulative Annual Demand Response Savings in the Constrained Achievable Potential Scenario,

by Measure for Washington D.C.

Cumulative Annual MW Savings

- Constrained Achievable by End Use

End Use 2013 2014 2015 2016 20 17 2018 2019 2020 2021 2022

Res AC 1.60 3.23 4.91 6.64 8.41 10.22 12.08 13.99 15.94 17.95

Res WH 0.17 0.34 0.51 0.69 0.86 1.04 1.22 1.39 1.58 1.76

Res Pool

Pumps 0.10 0.20 0.31 0.41 0.51 0.62 0.72 0.83 0.93 1.04

Res TSTAT 0.23 0.47 0.72 0.97 1.23 1.49 1.76 2.04 2.33 2.62

Res CPP 0.65 1.32 2.01 2.72 3.44 4.19 4.95 5.73 6.54 7.36

Com AC 0.45 0.91 1.36 1.81 2.26 2.72 3.17 3.62 4.08 4.53

Com Lights 0.36 0.72 1.08 1.43 1.79 2.15 2.52 2.88 3.24 3.60

Com CPP 3.53 7.05 10.59 14.13 17.67 21.22 24.77 28.33 31 .89 35.46D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 101 Com RTP 0.27 0.27 0.53 0.53 0.80 0.80 1.06 1.06 1.33 1.33

Com

Interruptible 0.74 1.49 2.23 2.98 3.72 4.46 5.21 5.95 6.70 7.44

Total 8.10 16.00 24.25 32.30 40.70 48.91 57.46 65.83 74.55 83.09

% of Annual

Peak Forecast 0.3% 0.6% 0.9% 1.3% 1.6% 1.9% 2.2% 2.5% 2.7% 3.0%



### 8.5 A CHIEVABLE 

### P OTENTIAL 

### B ENEFITS 

### & C OSTS



### The societal cost test (SCT) measures the net ben e fits of the en e rgy efficie n cy program for a region o r

service area as a whole. C o sts included in t h e SCT a r e costs to purcha s e and in s tall t h e demand response

measure and overhead co s ts of running the demand response program. The b e nefits included are the

avoided costs of energy and capacity, as well as a 30% benefits adder to account for externalities such as

improved health and reduced envir onmental degradation

. Tables 8

- 16 and 8

- 17 below provide the

present value of benefits and c osts of t he Societal Cost Test for the 5

- year a nd 1 0

- year perio d s for

all three achievable potential s cenarios.

Table 8

- 16 : 5

- Year SCT Ratios for Achievable Poten tial Scenarios

– Demand Response Only

5

- year SCT Benefits SCT Costs SCT Ratio

Maximum Achievable $441,960,053 $83,258,607 5.31

Base Achievable $227,021,163 $32,032,093 7.09

Constrained Achievable $106,801,523 $11,383,424 9.38

Table 8

- 17 : 10

- Year SCT R atios for Achievable Potential Scenarios

– Demand Response Only

10

- year SCT Benefits SCT Costs SCT Ratio

Maximum Achievable $894,333,581 $160,456,732 5.57

Base Achievable $459,663,725 $61,758,970 7.44

Constrained Achievable $215,542,890 $22,205,957 9.71D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 102 

# 9 S U M M A R

Y O F 

# R E S U L T S

This final section of the report provides a brief recap of the savings estimates of technical, economic and

achievable potential, and also provides some recommendations for policy makers and planners to

consider when utilizing the resu lts of this study for the development of future program plans and policy

measures.



### 9.1 T ECHNICAL



### , E CONOMIC AND 

### A CHIEVABLE 

### S AVINGS 

### P OTENTIAL



### Tables 9

- 1 through 9

- 4 provide a summary of the technical, economic, and achievable energy efficiency

potential over th e 5 and 10 year planning horizons. These energy efficiency savings potential results

show that significant electric energy and demand and natural gas savings potential remains in the District.

The tables also show the savings as a percentage of the respect ive sales forecasts for 2017 and 2022. The

Base Achievable estimates include 13% electric savings and 7% natural gas savings by 2017. The Base

Achievable estimates include 21% electric savings and 13% natural gas savings by 2022. Tables 9

- 5 and

9

- 6 provide a summary of the technical, economic, and achievable demand response potential over the 5

and 10 year planning horizons.

Table 9

- 1: Summary of Technical, Economic and Achievable Electric Energy Savings for 2017

Summary of Technical, Economic and Achievab le Electric Energy Efficiency Savings for 2017

Energy Demand

Energy

(MWh) % of 2017

Sales Winter

MW % of 2017

Winter Peak Summer

MW % of 2017

Summer

Peak

ALL SECTORS COMBINED

Technical Potential 3,544,474 28.8% 789 41.7% 668 25.6%

Economic Potential 3,413,829 27.7% 771 40.7% 643 24.7%

Max Achievable Potential 2,212,680 18.0% 486 25.7% 403 15.4%

Base Achievable Potential 1,560,081 12.7% 313 16.5% 289 11.1%

Constrained Achievable

Potential 1,342,525 10.9% 244 12.9% 215 8.2%

Table 9

- 2: Summary of T echnical, Economic and Achievable Electric Energy Savings for 2022

Summary of Technical, Economic and Achievable Electric Energy Efficiency Savings for 2022

Energy Demand

Energy

(MWh) % of 2022

Sales Winter

MW % of 2022

Winter Peak Summer

MW % of 2022

Summer

Peak

ALL SECTORS COMBINED

Technical Potential 5,759,943 44.7% 1,216 61.3% 1,051 38.4%

Economic Potential 5,537,521 43.0% 1,181 59.5% 1,011 36.9%

Max Achievable Potential 3,781,942 29.4% 836 42.1% 703 25.7%

Base Achievable Potential 2,715,397 21 .1% 548 27.6% 511 18.6%

Constrained Achievable

Potential 2,340,833 18.2% 495 25.0% 438 16.0%D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 103 Table 9

- 3: Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2017

Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2017

Energy

Energy (MMBtu) % of 2017 Sales

ALL SECTORS COMBINED

Technical Potential 7,182,714 23.4%

Economic Potential 6,400,319 20.8%

Max Achievable Potential 3,845,186 12.5%

Base Achievable Potential 1,974,923 6 .4%

Constrained Achievable Potential 1,645,886 5.4%

Table 9

- 4: Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2022

Summary of Technical, Economic and Achievable Natural Gas Energy Efficiency Savings for 2022

En ergy

Energy (MMBtu) % of 2022 Sales

ALL SECTORS COMBINED

Technical Potential 10,991,828 34.5%

Economic Potential 9,817,767 30.8%

Max Achievable Potential 7,681,736 24.1%

Base Achievable Potential 3,998,724 12.5%

Constrained Achievable Potential 3,3 08,069 10.4%

Table 9

- 5: Summary of Technical, Economic and Achievable Demand Response Savings for 2017

Summary of Technical, Economic and Achievable Natural Gas Demand Response Savings for 2017

Demand (MW) % of 2017 Sales

ALL SECTORS COMBINED

Technic al Potential 1,131.6 43.4%

Economic Potential 1,130.3 43.3%

Max Achievable Potential 167.8 6.4%

Base Achievable Potential 86.5 3.3%

Constrained Achievable Potential 40.7 1.6%

Table 9

- 6: Summary of Technical, Economic and Achievable Demand Response Sa vings for 2022

Summary of Technical, Economic and Achievable Demand Response Savings for 2022

Demand (MW) % of 2022 Sales

ALL SECTORS COMBINED

Technical Potential 1,155.9 42.2%

Economic Potential 1,154.5 42.2%

Max Achievable Potential 343.4 12.5%

Ba se Achievable Potential 177.3 6.5%

Constrained Achievable Potential 83.1 3.0%



### 9.2 R ECOMMENDATIONS



### Finally, the consultants offer a few recommendations for how to best utilize the results of this report for

planning purposes. While the sector level and overa ll savings provide a useful vantage point in terms of

the potential impact of energy efficiency in the District , it is also useful to point out some of the

measures which may yield the most significant energy efficiency gains over the next 5 and 10 years.

Tables 9

- 7 through 9

- 10 list the Top 10 energy efficiency measures for the following categories:

residential electric measures, residential gas measures, non

- residential electric measures, and non

-D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 104 

### residential gas measures. In the residential sector, the an alysis indicates significant potential remains in

the lighting sector, with LED Screw

- In Bulbs and Specialty CFL Bulbs taking 2 of the top 3 spots, and

Controlled Power Strips rounding out the Top 3. The increase in plug load electric use across the U.S.

m eans efficient electronics products are becoming increasingly viable options for capturing energy

efficiency gains. Wall insulation and Gas Water Heaters make up 2 of the Top 3 among residential gas

measures. The cold winters of the District combined with the aging infrastructure of District homes

means weatherization measures can still yield significant gains in the District. Among non

- residential

electric measures, LED Screw

- In bulbs again make the top 3, as do two separate dual enthalpy

economizer measur es. Among non

- residential gas measures, Demand Controlled Ventilation, Heat

Recovery from Air to Air, and Improved Wall Insulation make the top 3, with several other

weatherization measures rounding out the Top 10.

Table 9

- 7: Top 10 Residential Electric S avings Measures

10

- Year Max. Achievable

Potential (MWh)

Specialty CFL Bulbs 95,390

Controlled Power Strips 51,040

LED Screw

- In Bulbs 44,951

Efficient Televisions 44,769

ENERGY STAR Air Source Heat Pumps 32,856

Standard Screw

- In CFL Bulbs 32,589

Low Income Weatherization Package 29,845

Wall Insulation 26,619

Exterior Lighting 25,610

Heat Pump Water Heater 25,302

Table 9

- 8: Top 10 Residential Gas Savings Measures

10

- Year Max. Achievable

Potential (MMBtu)

Wall Insulation 410,645

Gas Water Heater 358,466

Low Income Weatherization Package 280,164

Air Sealing 258,298

Ceiling/Attic Insulation 189,364

Low Flow Showerheads 123,418

ENERGY STAR Windows 121,621

Efficient Furnaces 112,102

Floor Insulation 80,032

Duct Sealing 76,660

Table 9

- 9: Top 10 Non

- Residential Electric Savings Measures

10

- Year Max. Achievable

Potential (MWh)

Dual Enthalpy Economizer

- from Fixed

Damper 228,386

LED Screw In 185,003

Dual Enthalpy Economizer

- from Dry 166,099D ISTRICT OF C OLUMBIA E NERGY E FFICIENCY P OTENTIAL

Page 105 10

- Year Max. Achievable

Potential (MWh)

Bulb

EMS install 165,167

LED Wallpack 101,002

CFL Screw

- in 100,590

Programmable Thermostats 99,496

Ductless (mini split) 80,428

Variable Speed Drive Control, 40 HP 79,993

Variable Speed Drive Control, 5 HP 79,993

Table 9

- 10: Top 10 Non

- Residential Gas Savings Measures

10

- Year Max. Achievable

Pot ential (MMBtu)

Demand Controlled Ventilation 388,375

Heat Recovery from Air to Air 357,738

Improved Wall Insulation (to R12) 345,309

Air Sealing 327,186

Repair/Replace malfunctioning steam

traps 303,686

Boiler Reset Controls 277,603

Programmable Th ermostat 231,239

Improved Roof/Ceiling Insulation (to

R32) 230,169

Zoning 197,929

Boiler blowdown heat exchanger (steam) 192,019



### the consultants recommend that the reader of this report use the overall results in order to understand

the energy effici ency potential that remains to be captured Washington D

. C

. and to understand the

measures that have the most savings potential and are the most cost effective. Utilizing the report in this

way will best inform policy makers and planners in order to equip t hem with the best information

possible to help the District to continue capturing the available energy efficiency gains as efficiently and

cost effectively as possible.