PUBLIC VERSION (11.18.2013)



# Second Annual

Energy Efficiency Benchmarking Report

(Based on EIA 2011 data)

Energy Efficiency Working Group

Benchmarking Subcommittee: Data Analysis Team

Benchmarking Subcommittee Chair:

Norman	Muraya



### Report Authors (Data Analysis Team within the Benchmarking Subcommittee):

Annika	 Brink,	 Paul	 Davis,	 Tom	 Gross,	 Michael	 Little,	 Nicole	 Mor eland,	 Norman	 Muraya,

Larry	Philbin,	Jeff	S tafford,	Don	Wucker,	and	Steve	Zach

October 11, 2013

### LPPC EEWG Benchmarking Subcommittee

Page i

### LPPC EEWG Benchmarking Subcommittee

Page ii 

## Table of Contents

Executive	Summary	.............................................

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

Introduction

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

Outline of the Report.........................................................................................................................

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

 Analysis	of LPPC	Data	.........................................

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

 General	and	Metric‐Spe cific	Data	Issues	.......................

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

 Improved	Data	Collection,	Q uality,	and	Usefulness	.............

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

 Conclusions	and	Recommendatio ns	for	Future	Research	........... ......................................................	2

 Charts	........................................................

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

Introduction	..................................................

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

The Large Public Power Council and the Energy Efficiency Working Group

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

Benchmarking Subcommittee: Purpose and Activities

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

Analysis	of LPPC	Data	.........................................

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

Description of LPPC Utility Population

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

Table	1‐A:	LPPC	“Retail	Equivalen t”*	Utilities	Included	in	this Report	(2011	Data)	........................	7

Table	 1‐B:	 Remaining	 LPPC	 Utilities	 –	 Primarily	Wholesale	 Utili ties	 not	 Otherwise	 Found	 in

this	Report,	and	Summary	S tatistics	(2 011	Data)	...............

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

Energy Efficiency Program Performance Metrics and Measures

........................................................................... 9

Cost	Measures	.................................................

............................................................... .................................................	9

Savings	Measures	and	Deman d	Response	Indicators	...............

............................................................... ....	10

Cost‐to‐Savi ngs	Rates	.........................................

............................................................... ........................................	10

Trends	........................................................

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

Short‐Term	and	Long‐Term	Goals	................................

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

Metrics	Not	Included in	This	Report	...........................

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

General	Data Issues	...........................................

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

Metric‐Specific Data	Issues	...................................

............................................................... ..............................................	13

Cost

............................................................................................................................... ..................................................................... 13

### LPPC EEWG Benchmarking Subcommittee

Page iii Savings

............................................................................................................................... ............................................................. 13

Cost

‐ to

‐ Savings Rates

............................................................................................................................... ................................ 13

Improving	Data	Collection,	Q uality,	and	Usefulness	............

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

Conclusions	and	Recommendatio ns	for	Future	Research	...........

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

Charts.........................................................

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

Cost Measures

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

Chart	1:	Total	EE	&	DR	Spendin g,	2011	(in	millions	of	$)	......

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

Chart	2:		Total	EE	Spending	Relative	to	Retail	Sales,	2011	(in $/MWh)	..............................................	17

Chart	3:		Total	DR	Spending	Rela tive	to	Peak	Demand,	2011	(in	$ /MW)	...........................................	18

Chart	4:		Total	EE	&	DR	Spending	Relative	to	Retail	Revenue,	20 11	(in	%)	.......................................	18

Chart	5:	Total	EE,	DR,	&	Renewable	FTE	Employees	by	Type	(Exter nal	vs.	Internal),	2011	.......	19

Chart	 6:	 Total	 EE,	 DR,	 &	 Renewable	 FTE	 Employees	 Relative	 to	 MW h	 Retail	 Sales,	 2011	 (in

FTEs	per	mi llion	MWh)	.........................................

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

Savings Measures

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

Chart	7:		Incremental	Energy	Sav ings	from	EE,	by	Sector,	2011	( in	MWh)	........................................	21

Chart	8:	Incremental	Energy	Savi ngs	from	EE	Relative	to	Retail Sales,	2011 (in	%)	.....................	21

Chart	9:	Incremental	Energy	Savi ngs	from	Sector‐Specific	EE	Rel ative	to	Retail	Sales	from	that

Sector,	2011	(in	%)	...........................................

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

Chart	10:	Peak	Demand	Reduction from	EE	&	DR, 2011	(in	MW)	.... ......................................................	22

Chart	11:	Peak	Demand	Reduction	fr om	EE	&	DR,	by	Sector,	2011	( in	MW)	....................................	23

Chart	 12:	 	 Peak	Demand	Reduction	 from	 EE	&	DR	Relative	 to	Annua l	System	 Peak	Demand,

2011	(in	%)	...................................................

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

Chart	13:		Peak	Demand	Reduction	from	EE	&	DR	Relative	to	Annua l	System	Peak	Demand,	by

Sector,	2011	(in	%)	...........................................

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

Cost

‐ to

‐ Savings Rate Measures

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

Chart	14:		EE	Spending	Relative	to	Incremental	Energy	Savings, 2011	(in	$/MWh)	.....................	25

Chart	15:		EE	Spending	Rel.	to	Incremental	Energy	Savings,	by	S ector,	2011	(in	$/MWh)	.........	25

Chart	16:	EE	&	DR	Spend ing	Relative	to	Peak Demand	Saved	(in	$/ kW)	...........................................	26

### LPPC EEWG Benchmarking Subcommittee

Page iv Chart	17:	Incremental	Energy	Savings	from	EE	Relative	to	#	of	( Internal	&	External)	EE	FTE’s

&	from	DR	Relative	to	#	of	(Internal	&	External)	DR	FTE’s,	2011 (in	MWh/FTE)	..........................	26

Trends: 2009

‐ 2011

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

Chart	18:	2009‐2011	Total	R etail	Sales	(in	MWh)	...............

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

Chart	19:	2009‐2011 Retail	Revenue	(i n	billions	of	$)	.........

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

Chart	20:	2009‐2011	Total	EE	& DR	Spending	(in	millions	of	$)	. ...........................................................	28

Chart	21:	2009‐2011	Total	EE Spending	(in	millions	of	$)	......

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

Chart	22:	2009‐2011	Total	DR	Sp ending	(in	millions	of	$)	......

............................................................... ..	29

Chart	23:	2009‐2011	Total	EE	&	DR	Spending	Relative	to	Retail	R evenue	(in %)	..........................	29

Chart	24:	2009‐2011	Total	Increme ntal	Energy	Savings	from	EE	(i n	MWh)	....................................	30

Chart	25:	2009‐2011	Total	EE	&	DR	FTE’s	(Internal	and	External/ Contract ed)	.............................	30

Chart	26:	2009‐2011	Total	Incremental	Savings	from	EE	Rel.	to	M Wh	Retail	Sales	(in	%)	........	31

Chart	27:	2009‐2011	Total	 Incremental	EE	Spending	Relative	 to	 I ncremental	EE	MWh	Saved

(in	millions	o f	$/MWh)	........................................

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

Chart	 28:	 2009‐2011	 Total	 Increme ntal	 EE	Spending	Relative	 to	 I ncremental	 Peak	 kW	 Load

Reduction	from EE	(in	$/kW)	...................................

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

Chart	29:	2009‐2011	Load	Factor (MWh	per	Peak	kW	x	8,760)	..... ........................................................	32

Short

‐ Term and Long

‐ Term Goals

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

Chart	30:	Short‐Term	Goals	for	Energy	Savings	(MWh	as	%	of	Tota l	MWh	Retail	Sales)	............	33

Chart	31:	Long‐Term	Goals	for	Energy	Savings	(MWh	as	%	of	Total MWh	Retail	Sales)	.............	33

Chart	32:	Short‐Term	Demand	Goals	for	Energy	Efficiency	and	Dem and	Response	(MW	as	%	of

Peak	Demand)	..................................................

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

Chart	33:	Long‐Term	Demand	Goals	for	Energy	Efficiency	(MW	as	% of	Peak	Demand)	............	34

Chart	34:	Long‐Term	Demand	Goals	for	Demand	Response	(MW	as	%	o f	Peak	Demand)	..........	35

Chart	35:	Long‐Term	Demand	Goals for	Demand‐Side	Renewables	(MW Installed	Capacity	as

%	of	Peak Demand)	.............................................

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

Chart	36:	Long‐Term	Goals	for	De mand‐Side	Renewables	(MWh	Annua lly	as	%	of	Total	MWh

Retail	Sales)	.................................................

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

### LPPC EEWG Benchmarking Subcommittee

Page v Chart	37:	Long‐Term	Demand	Goals	for	Supply‐Side	Renewables	(MW Installed	Capacity	as	%

of	Peak	Demand)	...............................................

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

Chart	 38:	 Long‐Term	Goals	 for	Su pply‐Side	Renewables	 (MWh	Annua lly	as	%	 of	 Total	MWh

Retail	Sales)	.................................................

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

National Comparison

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

Data	Table	for	Five	Key	EE Performance	Measures	...............

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

Chart	40:	Percentiles	f or	Total	EE	Spending	Relative	to	Retail Revenue	(i n	%)	..............................	41

Chart	41:	Percentiles	f or	Total	EE	Spending	Relative	to	Retail Sales	(in	$/MWh)	..........................	42

Chart	42:	Percentiles for	EE	Spending	(in thousands	of	$)	.....

............................................................... ....	43

Chart	43:	Percentiles	for	Increme ntal	Energy	Savings	from	EE	Re lative	to	Retail	Sales	(in	%)	44

Data	Table	for	Four	Key	DR Performance	Measures	...............

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

Chart	44:	Percentiles	 for	Actual Annual	Demand	Reduction	 from	D R	as	a	Percent	of	Summer

System	Peak	De mand	(%)	........................................

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

Chart	 45:	 Percentiles	 for	 Actual	 Annual	 Demand	 Reduction	 from	 D R	 as	 a	 Percent	 of	Winter

System	Peak	De mand	(%)	........................................

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

Chart	46:	Percentiles	for	Direct &	Incentive	Costs	Rel.	to	Actu al	Peak	Reduction	(in	$/MW)	...	47

Appendix	A:	Benchmarking	Data	by Utility	(Main	Source:	EIA	Form 861,	2011)	......................................	49

Appendix	B:	Overview	of DEED	Grant	Activities	.................

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

Appendix	C:	EEWG	Benchmarking	Subcommittee’s	Public	Comments	to the	U.S.	Energy	Information

Administration	regarding	EIA	Form 861	(Submitted	May	6,	2013)	.

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

### LPPC EEWG Benchmarking Subcommittee

Page 1 

## Executive Summary

Introduction

This	report	is	a	project	of	the	Large	Public	Power	Council	(LPP C)	Energy	Efficiency	Working	Group

(EEWG),	 a	 collaboration	 among	 ene rgy	 efficiency	 professionals	 d rawn	 from	 the	 nation’s	 largest

public	power	utilities.	The	EEWG’s	Benchmarking	Subcommittee	id entified	 the	limited	availability

of	 dependable	 energy	 efficiency	 program	 data	 from	 peer	 utilitie s	 as	 a	 barrier	 to	 LPPC	 utilities’

ability	to	judge	and	improve	energy	efficiency	program	performa nce.

This	 second	 annual	 benchmarking	 report	 documents	 the	 continuati on	 of	 the	 EEWG	 data	 analysis

benchmarking	 initiative	 and	 provides	 a	 foundation	 for	 developin g	 useful	 energy	 efficiency

performance	 data	 and	 information.	 This	 report	 uses	 data	 from	 th e	 Energy	 Information

Administration’s	 (EIA)	 Form	 861	 to	 provide	 a	 snapshot	 of	 LPPC	 u tilities’	 energy	 efficiency

performance	from	2009	through	2 011.	In	some	cases,	this	data	wa s	supplemented	with	additional

information	 provided	 by	 LPPC	 utilities.	 The	 Benchmarking	 Subcom mittee	 will	 produce	 annual

reports	and	use	findings	from	ea ch	year’s	report	to	support	bes t	practices	conversations	within	the

EEWG,	 to	improve	subsequent	annual	reports,	 to	continually	infl uence	EIA	 to	improve	Form	861,

and	 to	 standardize	 LPPC	 data	 reporting.	 Wherever	 possible,	 the Subcommittee	 will	 draw	 on

existing	initiatives	in	this	arena.



### Outline of the Report

 Analysis of LPPC Data

The	report	begins	by	listing	the	data	sources	used	and	explaini ng	which	twenty‐one	utilities	are

included	in	this	report.	It	further	outlines	concerns	about	the small	sample	of	utilities	and	areas

of	variation	among	utilities	that	affect	data	comparability.	Fo r	example,	the	size	of	the	included

LPPC	 utilities	 ranges	 from	 46,000	 to	 1.48	 million	 customers.	 Th e	 report	 goes	 on	 to	 explain

which	 energy	 efficiency	 and	 demand	 response	 metrics	 and	 measure s	 were	 included	 in	 the

analysis.	These	metrics	and	meas ures	were	chosen	based	on	usefu lness	and	perceived	lack	of

bias,	but	also	based	on	the	data	available	through	EIA	Form	861 .They	are,	briefly:

Cost Measures ‐	describes	the	annual	expenditures	and/or	resources	consumed	b y	EE	and

DR	programs. 1 These	include	relative	cost	measu res	that	adjust	for	utility	si ze.

Savings Measures

‐ describes	MWh	and	MW	reductions	a chieved;	also	adjusted	for	siz e.

Cost

‐ to

‐ Savings Rates ‐	describes	the	reductions	achie ved	relative	to	their	costs.

Demand Response Indicators ‐	describes	demand	response	capabilities.

1 In this report, indirect costs were allocated to EE or DR according to the relative weight of direct spending in

these categories.

### LPPC EEWG Benchmarking Subcommittee

Page 2  General and Metric

‐ Specific Data Issues

Next,	the	report	explores	general	as	well	as	metric‐specific	da ta	issues	that	affect	the	ability	to

draw	 comparisons	 among	 utilities.	 Data	 reporting	 content	 and	 co nsistency	 have	 surfaced	 as

issues	 primarily	 due	 to	 different	 ways	 each	 utility	 may	 classif y	 its	 data	 and	 due	 to	 lack	 of

definitional	 precision	in	 the	 Form	 861	itself.	 Areas	 of	 uncerta inty	include	 utility	methods	 for

measuring	 and	 reporting	 savings and	 for	 defining	 cost	 categorie s.	 Additional	 comparability

issues	 occur	 because	 LPPC	 utilities	 vary	 in	 the	 percent	 of	 whol esale	 power	 sold	 (although

primarily‐wholesale	LPPC	utilities	have	largely	been	excluded	f rom	this	report)	and	in	whether

or	not	they	provide	energy	efficiency	services	to	both	wholesal e	and	retail	customers.

Measures	in	the	Cost	metric	are affected	primarily	by	imprecise definitions	of	the	data	elements

comprising	 them	and	a	lack	 of	direction	 on	how	 to	apportion	cos ts.	Additionally,	it	is	 unclear

how	 utilities	 count	 employees	 working	 part‐time	 on	 DSM	 activiti es	 and	 whether	 utilities	 are

including	 fully‐burdened	rates	when	reporting	labor	costs.	Meas ures	in	the	Savings	metric	are

affected	by	the	type	of	savings reported	(gross,	net,	etc.).	Me asures	in	the	Cost‐to‐Savings	Rate

metric	 are	 affected	 by	 the	 fact	 that	 Form	 861	 does	 not	 collect information	 on	 the	 lifetime	 of

energy	 efficiency	 measures.	 Without	 this	 information,	 cost‐effe ctiveness	 cannot	 truly	 be

measured.



###  Improved Data Collection, Quality, and Usefulness

Since	issuing	the	inaugural	benchmarking	report	in	June	2012,	t he	LPPC	EEWG	Benchmarking

Subcommittee	 has	 made	 a	 significant	 effort	 to	 improve	 the	 quali ty	 of	 energy	 efficiency	 data

generated	via	the	U.S.	Energy	In formation	Administration’s	(EIA )	data	collection	efforts.

Further	 discussion	 on	improving	 utility	 data	 reporting	 on	EIA	 F orm	 861	appears	later	in	 this

report,	 including	 Appendix	 B	 –	 Overview	 of	 DEED	 Grant	 Activitie s.	 Major	 recommendations

include:	 provide	 clear	 definitions of	 specific	 terms	 and	 data	 i nputs,	 provide	 examples	 of

calculation	 methodologies,	 provide	 more	 opportunities	 for	 trans parency	 of	 calculation

methodologies,	 ask	 for	 information	 about	 the	 longevity	 of	 savin gs,	 standardize	 reporting	 of

labor	 costs,	 and	 break	 out	 additional	 cost	 categories.	 Ceres	 an d	 the	 Consortium	 for	 Energy

Efficiency	 have	 each	 also	 produc ed	 useful	 recommendations	 for	 h ow	 EIA	 can	 improve	 data

collection	and	reporting.



###  Conclusions and Recommendations for Future Research

The	 written	 analysis	 concludes	 with	 a	 summary	 of	 challenges	 enc ountered	 in	 producing	 the

report	 and	 a	 list	 of	 recommendations	 for	 future	 research	 and	 re ports.	 	 In	 the	 process	 of

soliciting	and	reviewing	participant	data,	 the	Benchmarking	Sub committee	discovered	several

issues	related	 to	data	accuracy	and	precision;	however,	it	also generated	many	questions	and

ideas	 that	 could	 pave	 the	 road	 to	 ongoing	 and	 dynamic	 performan ce	management	 tools.	 The

challenge	going	forward	will	be	to	categorize	and	prioritize	wh ich	areas	and	activities	have	the

best	cost‐benefit	potential	give n	limited	resources	to	pursue	t hem.

Areas	of	note	include	(but	are	certainly	not	limited	to):	devel oping	or	adopting	data	definitions

and	 reporting	 protocols,	 creating	 performance	 analyses	 database s	 to	 track	 trends	 over	 time,

bringing	in	data	from	utility‐ge nerated	benchmarking	reports,	c reating	a	cross‐tabbed	database

### LPPC EEWG Benchmarking Subcommittee

Page 3 of	 energy	 efficiency	 program	 cha racteristics	 in	 order	 to	 statis tically	 correlate	 these

characteristics	to	performance	results,	and	capturing	informati on	on	measure	longevity.	In	the

future,	 the	 Benchmarking	 Subcommittee	 may	 want	 to	 create	 its	 ow n	 data	 definitions	 and

reporting	protocols	or	it	may	ad opt	guidelines	and	protocols	cr eated	by	others.



###  Charts

Finally,	 the	 report	 presents	 a	 series	 of	 charts	 showing	 the	 res ults	 of	 the	 Benchmarking

Subcommittee’s	data	analysis:	the se	charts	are	presented	largel y	without	commentary.	The	first

set	 of	 charts	 uses	 2011	 data	 to	 explore	 the	 primary	measures	 ch osen	 for	 analysis.	 These	 are

followed	by	charts	showing	a	2009	to	2011	comparison	for	severa l	of	these	measures.	The	next

set	of	charts	shows	short‐term	and	long‐term	LPPC	utility	energ y	savings	goals.	The	last	section

of	charts	brings	in	additional	EIA	data	to	present	a	national	c omparison	among	LPPC	and	other,

similarly‐sized	utilities.

### LPPC EEWG Benchmarking Subcommittee

Page 4 

## Introduction

The Large Public Power Council and the Energy Efficiency Working Group

The	Energy	Efficiency	Working	Group	(EEWG)	is	made	up	of	energy efficiency	professionals	 from

members	of	the	Large	Public	Powe r	Council	(LPPC),	an	organizati on	comprised	of	twenty‐six	of	the

nation's	 largest	 locally	 owned	 and	 controlled,	 not‐for‐profit	 p ower	 systems.	 The	 LPPC	 EEWG	 is

working	 to	 move	 the	 public	 power	 sector	 toward	 providing	 more	 r obust	 energy‐efficiency

programs	and	services.	Members	of	the	EEWG	have	focused	on	brea king	down	many	of	the	barriers

to	collaboration	among	utilities	in	order	to	foster	ongoing	com munication	and	to	create	a	forum	in

which	members	can	share	informat ion	and	resources.	In	2012,	the EEWG	has	focused	its	efforts	in

three	areas:	benchmarking,	retai ler	partnerships,	and	emerging issues	and	programs.

Since	2011,	the	EEWG	has	been	assi sted	in	its	efforts	by	the	Cl ean	and	Efficient	Energy	Program	for

Public	Power	(CEEP),	a	project	staffed	by	the	Alliance	to	Save Energy	in	cooperation	with	the	Large

Public	Power	Council	and	 the	American	Public	Power	Association. CEEP	 facilitates	peer	exchange

and	collaboration	among	LPPC	energy	efficiency	program	managers .	In	addition,	CEEP	maintains	a

website	 of	 energy	 efficiency	 res ources,	 CleanEfficientEnergy.or g,	 and	 has	 worked	 with	 the

American	Public	Power	Associati on	(APPA)	to	develop	resources	a nd	trainings.



### Benchmarking Subcommittee: Purpose and Activities

The	Benchmarking	Subcommittee	identified	the	limited	availabili ty	of	dependable	energy	efficiency

program	 data	 from	 peer	 utilities	 as	 a	 barrier	 to	 LPPC	 utilities judging	 and	 improving	 energy

efficiency	program	performance.	The	subcommittee	decided	to	ana lyze	LPPC	energy	efficiency	data

to	 identify	 high‐performing	 utilities,	 areas	 for	 specific	 utili ties	 to	 target	 for	 improvement,

shortcomings	of	the	existing	dat a,	and	future	research	needs.

First,	the	subcommittee	aggregated	LPPC	energy	efficiency	data as	reported	to	the	U.S.	Department

of	Energy’s	Energy	Information	Administration	(EIA)	through	For m	861.	It	then	chose	several	data

points	 from	Schedule	6,	“Demand‐Side	Management	 Information,”	i ntended	 to	provide	a	snapshot

of	 LPPC	 utilities’	 performance	 for	 2009	 through	 2011.	 The	 subco mmittee	 also	 issued	 a

supplemental	data	survey	to	colle ct	information	from	LPPC	utili ties	on	a	few	additional	data	points.

The	subcommittee’s	goal	is	to	produce	annual	benchmarking	repor ts	that	provide	insights	to	LPPC

utilities.	LPPC	utilities	will	use	 these	insights	 to	initiate	c onversations	with	management,	 to	share

best	 practices	with	 other	 LPPC	 utilities,	and	 to	modify	 their	e nergy	efficiency	 programs	 to	 better

match	LPPC	best	practices	and	be nchmarks.	The	subcommittee	will also	use	the	findings	from	each

year’s	 report,	 including	 emerging	 data	 challenges,	 to	 improve	 s ubsequent	 reports.	 The

subcommittee	has	worked	 (and	will	continue	 to	work)	with	EIA	 to improve	its	data	collection	by

improving	 the	 instructions	 and	 format	 for	 Form	 861. 2 It	 also	 works	 across	 LPPC	 utilities	 to

standardize	 the	way	 that	LPPC	utilities	(and	other	public	power utilities)	report	energy	efficiency

data	on	Form	861:	this	occurs	naturally	as	a	result	of	Subcommi ttee	member	conversations	and	has

2 The EIA’s Form 861 is subject to periodic review and public comments, per the Paperwork Reduction Act of 1995.

Other groups, including the Consortium for Energy Efficiency, have also commented on Form 861.

### LPPC EEWG Benchmarking Subcommittee

Page 5 been	supplemented	in	2012	by	one ‐on‐one	technical	assistance	to public	power	utilities	that	CEEP

data	analysis	identified	as	havi ng	potentially	erroneous	EIA‐86 1	data.

As	a	follow‐up	to	its	2012	Inaug ural	Benchmarking	Report,	the	S ubcommittee	has	dug	deeper	into

the	annual	EIA‐861	data	to	produce	a	2013	report	with	a	finer	l evel	of	detail.	This	includes	breaking

down	 data	 to	 the	 sector	 level	 (residential	 vs.	 commercial/resid ential),	 collecting	 more	 detailed

information	on	types	of	energy	e fficiency	and	renewable	energy employees,	and,	for	the	first	time,

requesting	that	utilities	provide	the	Subcommittee	with	informa tion	on	spending	and	savings at the

program or measure level .	 To	 some	 extent,	 this	 year’s	 da ta	 collection	 efforts	 have	 been

experimental,	as	the	Subcommittee	makes	an	effort	to	understand which	types	of	data	are	easy	to

produce,	 seeking	 a	 balance	 betwee n	 collecting	 useful	informatio n	 and	minimizing	 data	 reporting

requests	to	LPPC	peer	utilities.	For	example,	because	the	Subco mmittee	is	just	beginning	to	explore

peers’	 reporting	 systems,	 this	 year’s	 request	 for	 program/measu re‐level	 information	 did	 not

request	specific	data	points	and	asked	utilities	to	provide	thi s	information	in	whichever	format	was

most	convenient,	including	by	simply	providing	a	link	to	existi ng	reports.

In	 future	years,	the	Subcommittee	would	like	to	start	conversat ions	with	high‐performing	utilities

identified	via	its	Benchmarking	Report	analysis.	These	conversa tions	will	help	LPPC	utilities	access

peer	 knowledge,	 identify	 best	 practices,	 and	 improve	 their	 own programs	 going	 forward.	 The

Subcommittee	will	also	draw	on	existing	initiatives	in	this	are na,	such	as	those	being	conducted	by

DOE	through	the	State	and	Local	Energy	Efficiency	Action	Networ k	(SEE	Action),	by	the	Northwest

Regional	 Technical	 Forum,	 and	 by	 Northeast	 Energy	 Efficiency	 Pa rtnerships.	 As	 this	 initiative

continues,	the	Subcommittee	will also	place	more	emphasis	on	tr acking	trends	over	time.

Start: Unify LPPC EIA

‐ 861 Data in a 2013 report (2011 data)

Oct 2012 Nov

‐ Dec 2012 Jan

‐ Sep 2013 Oct

‐ Nov 2013 Nov

‐ Dec 2013

Identify

barriers Collect

data Analyze

data Produce	report Identify	findings:

 High	performers

 Areas	to	improve

 Data	challenges

 Future	research	needs Apply	findings:

 Bring	results	to

management

 Share	best	practices

 Modify	programs

Continue: Re

‐ initiate process to produce improved

2014 report with finer level of detail

### LPPC EEWG Benchmarking Subcommittee

Page 6 

## Analysis of LPPC Data

Description of LPPC Utility Population

The	 subcommittee	 began	 its	 data	 analysis	 with	 EIA‐861	 data	 from the	 population	 of	 twenty‐six

LPPC	 utilities.	 The	 subcommittee	 determined	 that	 seven	 utilitie s	 (ElectriCities	 of	 North	 Carolina,

Inc.;	Grand	River	Dam	Authority;	Lower	Colorado	River	Authority ;	MEAG	Power;	Nebraska	Public

Power	 District;	 New	 York	 Power	 Authority;	 and	 Platte	 River	 Powe r	 Authority)	 were	 wholesale

power	 providers,	 and	 should	 be	 excluded	 from	 this	 analysis.	 How ever,	 Nebraska	 Public	 Power

District	 and	 Platte	River	 Power	Authority	 subsequently	 adjusted their	 data	 so	 that	 they	 could	 be

meaningfully	compared	with	the	data	of	the	largely	retail	utili ties. 3

Of	 the	 remaining	 twenty‐one	 utilities,	 several	 have	 substantial wholesale	 power	 sales,	 but	 were

retained	because	 they	seem	 to	have	more	in	common	(e.g.	number of	customers)	with	retail	 than

with	wholesale	utilities.	These	utilities	were	invited	 to	parti cipate	in	a	supplemental	data	survey,

which	 several	 did.	 Robust	 benchmarking	 requires	 enough	 similari ty	 to	 be	 able	 to	 compare

performance	 attributes	 on	 an	 “apples	 to	 apples”	 basis:	 purely	 w holesale	 utilities	 could	 create	 a

subset	 for	 future	analysis.	Of	 these	 twenty‐one	members,	only	n ineteen 4 provided	energy	savings

data.	This	number	is	too	small	to	justify	high	confidence	in	st atistical	comparisons	and	analyses,	but

still	useful	for	providing	a	sna pshot	of	the	utilities	in	quest ion.

There	 is	 a	 wide	 range	 of	 variation	 in	 participant	 utility	 makeu p	 including	 size,	 MWh	 sales,

geographic	 location,	 customer	 class	 distribution,	 savings	 goals and	 expenditures,	 peaking

characteristics,	maturity	 of	 EE programs,	 and	 EE	 program	 portfo lio	 content	 and	 design,	 etc.	 This

exacerbates	 the	 problem	 of	meaningful	and	 representative	 compar isons.	 For	example,	 the	 size	 of

the	included	LPPC	utilities	ranges	from	46,000	to	1.47	million customers.	Where	the	EIA‐861	data

allowed,	this	report	includes	me asures	that	attempt	to	compensa te	for	these	varied	attributes—for

example,	by	relating	spending	to	a	utility’s	size.	However,	the data	are	not	sufficient	to	compensate

for	every	variation.

The	 table	 that	 follows	 outlines	 specific	 utility	 characteristic s	 that	 make	 it	 difficult	 to	 draw

meaningful	comparisons	among	LPPC	utilities.

3 For the purposes of this report, NPPD data include NPPD’s seventy

‐ seven wholesale customers’ retail customers,

as NPPD’s energy efficiency program serves all end

‐ use customers. For the purposes of this report, Platte

River’s customer base characterization (e.g., peak load, annual load, number of customers) is based on the

customer base of its four member municipal utilities. For DSM programs, only those programs managed and

funded primarily by Platte River are included. Its member utilities also offer efficiency and load management

programs, but they are not included in this report.

4 Puerto Rico Electric Power Authority did not report information on MWh savings from energy efficiency

programs, although it did report MWh savings from its demand response programs.

### LPPC EEWG Benchmarking Subcommittee

Page 7 Table 1

‐ A: LPPC “Retail Equivalent”* Utilities Included in this Report (2011 Data)

CLIMATE SIZE

(by MW) SIZE

(by # customers) SIZE

(by MWh Sold)

% Customer Mix

by MWh (R/C/I) HDD / CDD Peaking System

Peak

(MW) Rank Number of

Customers Rank Annual MWh Sold

(Retail +

Wholesale) Rank %

Whole

‐ sale **Avg

price,

$/kWh

Austin

Energy 36 / 45 / 19 2,039 / 3,791 Summer 2,714 10 417,191 9	 13,101,834	 12 0%	 0.09

Clark	PUD 53 / 29 / 17 4,884 / 477 Winter 956 17 185,035 16	 4,871,980	 19 8%	 0.08

Colorado

Springs 33 / 24 / 44 6,226 / 1,005 Summer 878 19 211,188 15	 4,748,463	 20 4%	 0.09

Imperial

Irrig	Dist 47	 / 53 /	 0 1,574 / 4,409 Summer 1,000 16 148,196 19	 3,313,144	 22 1%	 0.12

JEA 43 /	 33	 /	 24 1,599 / 2,791 Winter 3,062 8 419,992 8	 14,784,868	 11 18%	 0.11

Long	Island

Pwr	Auth 50 / 50 / 0 4,618 / 1,214 Summer 5,771 4 1,118,202 4	 20,248,464	 6 0%	 0.18

LA	Dept.

Water&Pwr 32	 / 59 /	 9 1,753 / 415 Summer 5,907 3 1,463,076 3	 24,178,842	 5 4%	 0.13

NE	Pub.

Pwr	Dist 32	 / 41 /	 27 6,942 / 1,194 Summer 2,646 11 371,907 11	 19,869,177	 7 N/A	 0.08

Omaha

Pub.	Pwr

Dist 34 / 32 / 34 6,207 / 1,452 Summer 2,468 12 352,182 12	 15,328,409	 10 30%	 0.07

Orlando

Util	Comm 39 / 55 / 7 624 / 3,461 Winter 1,276 15 223,618 14	 7,350,359	 18 18%	 0.11

Platte	River

Power	Auth 36 /	 33	 /	 31 6,846 / 1,022 Summer 640 21 146,198 20	 4,118,996	 21 N/A	 0.07

PUD	No.	1

of	Chelan 49 / 30 / 20 7,039 / 777 Winter 634 22 47,636 21	 11,825,032	 15 87%	 0.03

PUD	No.	2

of	Grant 19	 /	 18	 / 63 6,488 / 890 Summer 664 20 46,351 22	 11,844,013	 14 66%	 0.03

Puerto	Rico	 36 / 48 / 16 0 / 5,308 Summer 3,303 7 1,475,196 2	 18,251,359	 8 0%	 0.27

SMUD 44 / 6 / 49 3,443 / 1,327 Summer 2,840 9 598,681 7	 12,870,474	 13 19%	 0.12

Salt	River

Project 47 /	 41	 /	 12 1,301 / 5,068 Summer 6,493 2 965,644 5	 32,885,786	 2 19%	 0.09

San

Antonio 45 / 50 / 4 1,623 / 3,882 Summer 4,911 6 723,541 6	 28,448,864	 3 24%	 0.08

Santee

Cooper 16 / 18 / 66 2,795 / 2,200 Winter 5,676 5 164,677 18	 27,551,663	 4 59%	 0.07

Seattle	City

of 33	 / 55 /	 12 5,488 / 251 Winter 1,731 13 400,351 10	 17,058,087	 9 44%	 0.07

Snohomish

PUD	No.	1 52 / 35 / 13 5,750 / 130 Winter 1,375 14 323,460 13	 9,034,481	 16 24%	 0.08

Tacoma

City	of 41 / 7 / 52 5,637 / 187 Winter 931	 18 168,286 17	 7,515,807	 17 36%	 0.06

TVA 36 / 24 / 40 3,674 / 2,003 Summer 31,157 1 4,615,606 1	 165,449,755	 1 N/A	 0.07

TOTAL 87,032 14,586,214 474,649,857

Legend HDD	–	Heating	Degree	Da y CDD	– Cooling	Degree	Da y R	– Residential 							 	 	 	 C	– Commercial I	– Industrial

**	Calculated	by	dividing	Retail Revenue	by	Electricity	Retail	Sales

*	For	the	purposes	of	this	repor t	the	group	of	“Retail	Equivale nt”	utilities	also	includes	prim arily	wholesale	utilities	that provided	data	adjustments	to

the	Benchmarking	Subcommittee.	F or	these	utilities,	we	list	as “retail	customers”,	“retail	MWh sold”,	and	“retail	revenues”	da ta	from	all	customer

groups	to	which	the	utility	prov ides	energy	efficiency	services .	Thus,	the	data	shown	here—and elsewhere	in	this	report—differ s	from	EIA‐861	data

for	the	following	utilities:	Nebr aska	Public	Power	District,	Pl atte	River	Power	Authority,	and	Tennessee	Valley	Authority.

### LPPC EEWG Benchmarking Subcommittee

Page 8 Table 1

‐ B: Remaining LPPC Utilities

– Primarily Wholesale Utilities not Otherwise Found

in this Report, and Summary Statistics (2011 Data)

CLIMATE SIZE

(by MW) SIZE

(by # customers) SIZE

(by MWh Sold)

% Customer Mix

by MWh (R/C/I) HDD /

CDD Peaking System Peak

(MW) Number of

Customers Annual MWh

Sold (Retail +

Wholesale) %

Whole

‐ sale **Avg

price,

$/kWh

Grand	Riv.	Dam	Auth. Summer 996 81	 7,893,613

Lower	CO	Riv.	Auth. Winter 3,945 Not	Avail.	 17,412,038

Mun.	Elec.	Auth.	GA Summer 2,093 Not	Avail.	 12,840,991

ElectriCities*** Summer 2,745 Not	Avail.	 14,316,360

NY	Power	Auth. Summer 3,730 163	 39,919,170

Subtotal LPPC Primarily

Wholesale 244 92,382,172

Total, Tables 1

‐ A & 1

‐ B 14,586,458 567,032,029

U.S. Total  151,707,966 3,716,376,665

Share from LPPC + TVA 9.65%** *** 9.61% 15.3%

**	Calculated	by	dividing	Retail	Revenue	by	Electricity	Retail Sales

***	The	ElectriCities	numbers	were	arrived	at	by	adding	the	ent ries	for	N	Carolina	Mun	Pwr	Agency	#1	and	North	Carolina	Easter n	MPA.

 	In	order	to	avoid	double‐counting,	Tables	1‐A	and	1‐B	list the	combined	Retail	and	Wholesale	MWh	Sold	for	the	LPPC	utilit ies	and	for	TVA;

however,	Table	1‐B	lists	only	Retail	MWh	Sold	for	the	U.S.	Tota l.

** ***	Percentage of	combined	Summer	Peak	Demands	reported	to	EIA

### LPPC EEWG Benchmarking Subcommittee

Page 9 

### Energy Efficiency Program Performance Metrics and Measures

The	 EEWG	Benchmarking	Subcommittee	 selected	 three	metric	 catego ries	 for	immediate	analysis:

cost,	savings,	and	cost‐to‐savings	ratios.	Because	there	is	no perfect	measure	to	assess	performance

within	 any	 of	 these	 metric	 categories,	 this	 report	 includes	 sev eral	 measures	 to	 give	 a	 global

perspective	 of	 utility	 performan ce.	 Below	is	 the	list	 of	 these Energy	 Efficiency	 (EE)	 and	 Demand

Response	 (DR)	measures.		The	biase s	of	 these	measures	as	well	a s	inherent	data	weaknesses	are

assessed	as	they	arise	th roughout	the	report.

With	the	exception	of	data	relating	to	EE	and	DR	Full	Time	Empl oyees	(FTEs)	and	short‐term	and

long‐term	 EE	 and	 renewable	 energy	 goals,	 EIA‐861	 reporting	 is	 t he	 source	 of	 the	 data	 used	 to

generate	the	measures	listed	below.	We	also	gave	utilities	the opportunity	to	correct	or	update	the

data	 from	 their	 EIA	 submissions.	 In	 cases	 where	 the	 values	 repo rted	 to	 the	 Benchmarking

Subcommittee	 differ	 from	 those	 reported	 to	 EIA,	 this	 report	 use s	 the	 values	 provided	 directly	 by

the	utility.	These	data,	as	well	as	additional	utility‐reported information,	are	detailed	in	Appendix	A

and	are	available	in	spreadsheet	format	upon	request.

Metric	categories	and	associated	measures	are:



### Cost Measures ‐	describes	the	annual	expenditures	and/or	resources	consumed	b y	EE	and

DR	programs. 5

1. Energy	 efficiency	 and	 demand	 response	 spending	 (Total	 EE	 and	 DR Actual

Expenditure).	Unit	in	$. 6

2. Energy	 efficiency	 spending	 relative	 to	 retail	 sales	 (Total	 EE	 A ctual	 Expenditure	in

$/Electricity	Retail	Sales	in	MWh).	Unit	in	$/MWh.

3. Demand	response	spending	relative	to	peak	demand	(Total	DR	Actu al	Expenditures

in	$/Annual	System	Peak	Demand	in	MW).	Unit	in	$/MW.

4. Energy	efficiency	and	demand	resp onse	spending	relative	to	elec tric	retail	revenues

(Total	 EE	 Actual	 Expenditure	 in	 $/Retail	 Revenue	 in	 $	 and	 Total DR	 Actual

Expenditure	in	$/Retail	Re venue	in	$).	Unit	in	%.

5. FTE’s	 allocated	 to	 energy	 effici ency,	 demand	 response,	 and	 rene wables,	 by	 type

(both	internal	and	external/outsourced).	Unit	in	#.

6. FTE’s	 allocated	 to	 ene rgy	 efficiency,	 demand	 response,	 and	 rene wables	 relative	 to

retail	sales	(FTE’s/Electricity Retail	Sales	in	MWh).	Unit	in	# /MWh.

5 In this report, indirect costs were allocated to EE or DR according to the relative weight of direct spending in

these categories.

6 The descriptions in parentheses generally refer back to EIA data category names. One change has been made

consistently throughout this report: whereas EIA uses “Load Management” and “LM,” this report uses

“Demand Response” and “DR.” For the purposes of this report, these terms are interchangeable. Additionally,

the original EIA cost data have been altered to include indirect costs.

### LPPC EEWG Benchmarking Subcommittee

Page 10 Savings Measures and Demand Response Indicators

‐ describes	 MWh	 and	 MW

reductions	achieved.

7. Incremental 7 energy	 savings	 from	 energy	 effi ciency,	 by	 sector	 (Sector‐Speci fic

Incremental	Energy	Effects	fr om	EE	in	MWh).	Unit	in	MWh.

8. Incremental 8 energy	savings	from	energy	effi ciency	as	a	percent	of	retail	s ales	(Total

Incremental	Energy	Effects	from	EE	in	MWh/	Electricity	Retail	S ales	in	MWh).	Unit

in	%.

9. Incremental 9 energy	 savings	 from	 sector‐specific	 energy	 efficiency	 as	 a	 per cent	 of

retail	sales	 from	that	sector	(Sector‐Specific	Incremental	Ener gy	Effects	 from	EE	in

MWh/Sector‐Specific	Electricity	Retail	Sales	in	MWh).	Unit	in	%

.

10. Peak	demand	reduction	from	energ y	efficiency	and	demand	respons e	(Total	EE	and

DR	Incremental	Peak	Demand	Saved).	Unit	in	MW.

11. Peak	 demand	 reduction	 from	 energ y	 efficiency	 and	 demand	 respons e,	 by	 sector

(Sector‐Specific	Incremental	EE	an d	DR	Peak	Demand	Saved).	Unit in	MW.

12. Peak	demand	reduction	as	a	percent	of	annual	system	peak	demand (Total	EE	and

DR	Peak	Demand	Saved	in	MW/	Annual	System	Peak	Demand	in	MW).	U nit	in	%.

13. Peak	demand	reduction	from	sector‐specific	activities	as	a	perc ent	of	annual	system

peak	 demand	 (Sector‐specific	 EE	 and	 DR	 Peak	 Demand	 Saved	 in	 MW/ Annual

System	Peak	Demand	in	MW).	Unit	in	%.



### Cost

‐ to

‐ Savings Rates ‐	describes	the	reductions	achie ved	relative	to	their	costs.

14. Current	year	energy	efficiency	spending	per	incremental 10 savings	(Total	EE	Actual

Expenditure	 in	 $/Total	 Incremental	 Energy	 Effects	 from	 EE	 in	 MW h).	 Unit	 in

$/MWh. 11

15. Current	 year	 energy	 efficiency	 spending,	 by	 sector,	 per	 increme ntal 12 savings,	 by

sector	 (Sector‐Specific	 EE	 Actual	 Expenditure	 in	 $/Sector‐Speci fic	 Incremental

Energy	Effects	from	EE	in	MWh).	Unit	in	$/MWh. 13

16. Energy	efficiency	and	demand	response	spending	per	peak	demand reduction	from

energy	 efficiency	 and	 per	 peak	 de mand	 reduction	 from	 demand	 res ponse,

7 The instructions to EIA Form 861 define incremental effects as: “those changes in energy use (measured in

megawatt hours) and peak load (measured in megawatts) caused in the current reporting year by new

participants in DSM programs that already existed in the previous reporting year, and all participants in your

new DSM programs that existed for the first time in the current reporting year.”

8 See earlier footnote for definition of “incremental effects.”

9 See earlier footnote for definition of “incremental effects.”

10 See earlier footnote for definition of “incremental effects.”

11 Please note that this measure does not accurately reflect cost

‐ effectiveness, because EIA does not track data

such as measure life, lifetime savings, or expected useful life.

12 See earlier footnote for definition of “incremental effects.”

13 Please note that this measure does not accurately reflect cost

‐ effectiveness, because EIA does not track data

such as measure life, lifetime savings, or expected useful life.

### LPPC EEWG Benchmarking Subcommittee

Page 11 respectively	(Total	EE	Actual	Exp enditures	in	$/EE	Peak	Demand Saved	in	MW	and

Total	DR	Actual	Expenditures	in	$/DR	Peak	Demand	Saved	in	MW). Unit	in	$/kW.

17. Incremental	 energy	 savings	 from	 e nergy	 efficiency	 per	 FTE	 alloc ated	 to	 energy

efficiency	and	incremental	energy	savings	from	demand	response per	FTE	allocated

to	 demand	 response 14 (Total	 Incremental	Energy	Effects	 from	 EE	in	MWh/EE	 FTE

and	Total	Incremental	E nergy	Effects	from	D R	in	MWh/DR	FTE).	Un it	in	FTE/MWh.



### Trends

Charts	18‐29	depict	changes	over	time	for	the	above,	and	relate d,	measures:	2009‐2011.



### Short

‐ Term and Long

‐ Term Goals

Information	on	goals	was	collected	independently	by	the	Benchma rking	Subcommittee	and

addresses	short‐term	and	long‐term	goals	for	energy	efficiency, demand	response,	demand‐

side	 renewables,	 and	 supply‐side	 renewables.	 Some	 utilities	 did not	 have	 goals	 in	 all	 of

these	areas,	and	some	utilities	did	not	have	both	MWh	and	MW	go als.	Charts	30‐38	cover

this	information.



### Metrics Not Included in This Report

The	 Benchmarking	 Subcommittee	 also	 recognizes	 the	 following	met rics	 as	important,	 but

does	not	have	the	data	to	include	them	in	the	current	analysis. These	metrics	are	potential

targets	for	future	research.

 Quality ‐shows	how	good	the	EE	process 15 is	and	how	well	it	m eets	customer	needs.

 Speed ‐shows	how	long	it	takes	the	EE	process	to	produce	output	resul ts.

 Financial Value ‐shows	the	return	in	dollars	to	stakeholders	of	the	EE	process.

 Milestone ‐shows	the	accomplishment	of	an	activity	or	goal	of	the	EE	proc ess.

 Innovation ‐shows	 the	 impact	 of	 new	 ideas	 or	 ways	 of	 doing	 things	 for	 the EE

process.

14 See earlier footnote for definition of “incremental effects.”

15 Process refers globally to the development and deployment of energy efficiency portfolios, programs, and

measures.

### LPPC EEWG Benchmarking Subcommittee

Page 12 

## General Data Issues

The	Benchmarking	Subcommittee	chose	the	metrics	and	measures	li sted	above	based	on	usefulness

and	perceived	lack	of	bias,	but	also	based	on	 the	data	availabl e	 through	EIA	Form	861.	As	shown

above,	the	initial	focus	was	on	cost	and	efficiency	of	the	EE	p rocess	and	this	is	to	be	expected	in	the

early	 stages	 of	 the	 subcommittee’s	 work	 as	 these	 are	 the	 areas that	 management	 typically	 is

interested	 in	 on	 a	 short‐term	 basis.	 There	 is	 ample	 room	 to	 exp and	 this	 effort	 into	 balanced

performance	management	assessment	tools.

Data	 reporting	 content	 and	 consistency	 have	 surfaced	 as	 issues primarily	 due	 to	 different	 ways

each	utility	may	classify	its	data	and	due	to	lack	of	definitio nal	precision	in	the	Form	861	itself.	As

an	example,	we	are	not	sure	if	reported	EE	savings	are	based	on engineering	calculations,	deemed,

verified,	M&V	 gross,	M&V	 net,	 or	 produced	 by	 a	 combination	 of	 t hese	 methods.	 Uncertainty	 also

exists	regarding	which	costs	are	reported	by	each	utility,	and how	cost	categories	are	defined.	The

Benchmarking	Subcommittee	has	worked	with	EIA	 over	 the	course	 o f	 the	past	 year	 to	clarify	 the

inputs	 to	 EIA	 cost	 categories,	 b oth	 for	 current	 and	 future	 repo rting	 formats.	 In	 the	 future,	 the

Subcommittee	may	nevertheless	wish to	issue	guidelines	to	help public	power	utilities	report	their

costs	to	EIA.	One	option	is	the	adoption	of	guidelines	and	prot ocols	created	by	others,	such	as	DOE’s

SEE	 Action	 Work	 Group,	 the	 Northwest	 Regional	 Technical	 Forum, or	 the	 Northeast	 Energy

Efficiency	Partnerships.	In	2012‐13,	LPPC	utilities	worked	dili gently	with	EIA	staff	and	consultants

to	 improve	 the	 quality	 of	 data	 used	 in	 this	 and	 upcoming	 Benchm arking	 Reports:	 for	 additional

details	see	Appendix	B	–	Overv iew	of	DEED	Grant	Activities.

As	 mentioned	 in	 “Description	 of	 LPPC	 Utility	 Population,”	 compa ring	 retail	 to	 wholesale	 utilities

also	 produces	 uncertainty,	 since	 utilities	 do	 not	 report	 whethe r	 they	 provide	 energy	 efficiency

services	to	both	wholesale	and	retail	customers.	This	report	ge nerally	assumes	that	utilities	direct

energy	 efficiency	 spending	 toward	 retail	 customers	 only,	 and	 th us	 uses	 retail	 sales	 (MWh)	 and

retail	 revenues	 ($)	 wherever	 sales	 and	 revenue	 numbers	 are	 call ed	 for.	 In	 cases	 where	 utilities

direct	 energy	 efficiency	 spending	 toward	 retail and wholesale	 customers,	 the	 report	 bases	 its

analysis	 on	 retail plus wholesale	 sales	 and	 on	 retail plus wholesale	 revenues.	 In	 this	 report,

however,	 this	 accommodation	 has	 only	 been	 made	 for	 NPPD	 and	 Pla tte	 River,	 which	 drew	 the

report	authors’	attention	to	thi s	situation	(see	earlier	footno te	for	additional	clarification).

Small	sample	size	is	also	an	issue,	as	discussed	elsewhere	in	 t his	report.	The	charts	in	 this	report

will	 help	 LPPC	 utilities	 compare	 themselves	 to	 their	 peers,	 but the	 small	 sample	 size	 limits	 the

conclusions	 that	 LPPC	 utilities	 can	 draw	 from	 these	 comparisons .	 The	 “National	 Comparison”

section	brings	in	data	 from	 IOU’s	and	cooperatives	 to	provide	a more	statistically	valid	picture	of

utility	performance	relative	to a	broader	popula tion	of	similar ly	sized	utilities.

### LPPC EEWG Benchmarking Subcommittee

Page 13 

## Metric

‐ Specific Data Issues

Cost

Measures	in	 the	 Cost	metric	 are	 affected	 primarily	 by	imprecise definitions	 of	 the	 data	 elements

comprising	 them	 and	 a	 lack	 of	 direction	 on	 how	 to	 apportion	 cos ts.	 For	 example,	 utilities	 may

report	 marketing	 costs	 as	 direct	 costs	 or	 as	 indirect	 costs,	 de pending	 on	 how	 internal	 cost

categories	 are	 structured	 and	 a llocated.	 Or,	 marketing	 activiti es	 may	 be	 handled	 by	 another

department	 and	 entirely	 excluded	 from	 EIA	 reporting.	 Similar	 si tuations	 may	 occur	 with	 EM&V

costs.	Additionally,	it	is	unclear	how	utilities	count	employee s	working	part‐time	on	DSM	activities

and	whether	utilities	are	includi ng	fully‐burdened	rates	when	r eporting	labor	costs.	Some	utilities

do	 not	 separately	 report	 indirect	 costs,	 and	 for	 2011	 data,	 EIA did	 not	 ask	 utilities	 to	 allocate

indirect	costs	between	EE	and	DR	programs.	 In	 this	report,	indi rect	costs	were	allocated	 to	EE	or

DR	according	 to	 the	relative	weight	of	direct	spending	in	 these categories.	LPPC	utilities	reported

between	 0‐25%	 of	 total	 expenses	 as	 indirect	 costs,	 with	 eleven utilities	 reporting	 0‐2%	 of	 total

expenses	as	indirect	costs.

Additionally,	some	utilities	report	expenses	only	 for	EE	or	DR, but	not	both.	 It	is	unclear	whether

this	reflects	a	lack	of	programmatic	activity	in	one	of	these	a reas,	or	whether	the	utility	is	reporting

combined	expenses	under	one	category.

As	a	result	of	LPPC	EEWG	efforts	with	the	EIA,	the	current	form planned	for	2014	will	eliminate	the

five	cost	categories	of	“Direct	Costs	EE”,	“Direct	Costs	LM”	(D R),	“Incentive	Payments	EE”,	Incentive

Payments	 LM”	 (DR),	 and	 “Indirect	 Costs”.	 For	 2013	 data,	 the	 cat egories	 of	 “customer	incentives”

and	 “all	 other	 costs”	 will	 be	 lis ted	 separately	 for	 energy	 effi ciency	 programs	 and	 for	 demand

response	programs,	 for	a	 total	of	 four	cost	categories.	This	wi ll	aid	consistency	and	ensure	better

accuracy	 in	 future	 reports	 by	 el iminating	 the	 need	 to	 allocate indirect	 costs	 based	 on	 relative

weighting.



### Savings

As	 noted	 previously,	measures	in	 the	Savings	metric	are	affecte d	 by	 the	 type	 of	 savings	 reported

(gross,	net,	etc.).	In	this	report,	we	have	made	an	effort	to	n ormalize	savings	achieved	by	utility	size,

either	 on	 a	 “per	MWh	 sales”	 or	a	 “per	 revenues”	 basis.	Normaliz ation	 by	 revenues	 can	introduce

bias	based	on	how	retail	electric	rates	differ	among	utilities. Additionally,	certain	savings	categories

had	 few	 reported	 data	 points:	 many	 utilities	 reported	 neither	 M W	 peak	 demand	 reductions	 nor

incidental	MWh	savings	from	load	management	(DR)	programs.



### Cost

‐ to

‐ Savings Rates

The	biggest	barrier	to	using	Form	861	data	to	determine	cost‐to savings	rates	is	the	fact	that	it	does

not	 collect	 information	 on	 lifetime	 savings	 of	 energy	 efficienc y	 measures.	 The	 form	 collects

information	 on	 incremental	 effec ts—that	 is,	 current‐year	 saving s	 from	 all	 participants	 in	 new

programs	and	new	participants	in	old	programs—without	solicitin g	the	longevity	in formation	that

would	 enable	 a	 true	 measure	 of	 cost‐effectiveness.	 The	 Benchmar king	 Subcommittee	 and	 other

stakeholders	 have	 discussed	 this	 issue	 with	 EIA,	 which	 has	 resp onded	 by	 publishing	 proposed

### LPPC EEWG Benchmarking Subcommittee

Page 14 changes	 to	 Form	 EIA‐861	 that	 would	 solicit	 information	 on	 longe vity	 via	 a	 request	 for	 the

“weighted	average	life”	of	savings.

Measures	in	the	Cost‐to‐Savings	Rate	metric	are	also	affected	b y	the	same	issues	existing	in	the	Cost

and	 Savings	 metrics,	 along	 with	 the	 fact	 that	 actual	 reporting of	 demand	 data	 in	 the	 survey	 is

sparse.	As	noted	above,	customer	contribution	is	not	collected by	Form	861,	which	means	that	the

full	 cost	 of	 incremental	 energy	 saved	 is	 not	 reflected.	 Similar ly,	 the	 Cost‐to‐Savings	 Rate	 metric

focuses	on	 the	cost	of	saved	energy	and	does	not	address	 the	mo netary	value	of	savings	benefits,

such	 as	 bill	 savings,	 increased	 customer	 comfort,	 reduced	 emiss ions,	 etc.	 These	 benefits	 can	 be

estimated,	but	this	is	beyond the	scope	of	this	report.



## Improving Data Collection, Quality, and Usefulness

Since	 issuing	 the	 inaugural	 benchmarking	 report	 in	 June	 2012,	 t he	 LPPC	 EEWG	 Benchmarking

Subcommittee	 has	 made	 a	 significant	 effort	 to	 improve	 the	 quali ty	 of	 energy	 efficiency	 data

generated	 via	 the	 U.S.	 Energy	 Information	 Administration’s	 (EIA )	 data	 collectio n	 efforts.	 The

Subcommittee	has	partnered closely	with	the	EIA	to:

 Submit	feedback	on	the	EIA‐produc ed	User	Guide	for	EIA	Form	861 ,	Schedule	6.

 Plan,	develop,	and	conduct	two	we binars	on	EIA	energy	efficienc y	data,	which	were

attended	by	167	utility	staff,	i nclude	86	public	power	utility staff.

 Provide	70	public	power	utilities with	technical	assistance	on EIA	Form	861, Schedule	6.

 Submit	feedback	on	EIA’s	proposed changes	to	their	data	collect ion	for	EIA	Form	861,

Schedule	6	for	the	2014	data	co llection	cycle	(2013	data	year).

While	impacts	 of	 this	effort	will	 not	 be	 seen	immediately,	 thes e	investments	in	generating	 better

data	 will	 yield	 better	 intelligence	 in	 years	 to	 come.	 Further	 d iscussion	 on	 improving	 utility	 data

reporting	on	EIA	Form	861	appears	later	in	this	report,	includi ng	Appendix	B	–	Overview	of	DEED

Grant	 Activities.	 The	 Benchmarking	 Subcommittee	 has	 submitted	 r ecommendations	 to	 EIA	 that

would	resolve	some	of	these	issues	of	concern:	visit www.eia.gov/survey/changes/electricity/ for

EIA’s	 proposed	 revisions	 to	 Form	 EIA‐861,	 Schedule	 6	 2014	 form (for	 2013	 data).	 	 The

subcommittee’s	 main	 categories	 of	 recommendation,	 many	 of	 which would	 be	 addressed	 by	 the

changes,	include:

 Definitions	of	specific	terms	for consistent	understanding	and application 16

 Clarification	on	 the	data	inputs	and	what	 they	do	or	do	not	inc lude	–	some	improvements

are	currently	planned	for	i nclusion	in	the	2014	form.

 Providing	examples	of	how	some	calculations	should	be	done	–	EI A	has	proposed	to	provide

a	calculation	worksheet	for	certain	data	requested	by	the	2014 form.

 Providing	more	opportunities	for transparency	of	utility	calcul ation	methodology.

16 EIA provides a glossary, available here: http://www.eia.gov/tools/glossary/index.cfm

, and NEEP has created a

glossary, available here: http://neep.org/emv

‐ forum/project

‐ committees/protocol

‐ development

‐ projects

.

### LPPC EEWG Benchmarking Subcommittee

Page 15  Asking	 for	information	 about	 the	longevity	 of	 EE	 savings	 (e.g. weighted	 average	measure

life,	expected	useful	life,	etc. )	–	currently	planned	for	inclu sion	in	the	proposed	2014	form.

 Standardization	of	reporting	“bu rdened”	costs	for	all	labor	cos ts	–	not	fully	addressed	by	the

proposed	2014	form.

 Reporting	 of	 Administrative	 and Marketing	 costs	 separately	 –	 no t	 addressed	 by	 the

proposed	2014	form.

 Appropriate	 allocation	 of	 “indire ct	 costs”	 to	 either	 EE	 program s	 or	 DR	 programs. 17

Currently,	 indirect	 costs	 (someti mes	 substantial)	 are	 combined into	 only	 one	 category.	 –

Currently	planned	for	inclusion	in the	2014	form,	via	a	simplif ication	of	the	cost	categories.

The	EEWG	Benchmarking	Subcommittee	is	by	no	means	the	first	gro up	to	suggest	improvements	to

EIA	data	collection	and	usefulness.	Others	have	developed	simil ar	recommendations	in	the	past	and

the	Subcommittee	 assumes	 that,	in	 addition	 to	 the	Subcommittee, several	 other	 groups	 provided

feedback	 to	EIA	 via	 the	public	comment	period	on	its	proposed	2 014	 form	 (comments	submitted

March	6	to	May	6,	2013).	The	Subcommittee’s	public	comments	are available	in	Appendix	C	–	EEWG

Benchmarking	 Subcommittee’s	 Public	 Comments	 to	 the	 U.S.	 Energy Information	 Administration

regarding	EIA	Form	861	(Submitted	May	6,	2013).

17 Currently, indirect costs (sometimes substantial) are combined into only one category.

### LPPC EEWG Benchmarking Subcommittee

Page 16 

## Conclusions and Recommendations for Future Research

This	 report	 builds	 on	 the	 Subco mmittee’s	 inaugural	 report,	 incl uding	 a	 modest	 expansion	 of	 the

type	of	data	collected	and	analyzed.	This	report	is	intended	to provide	a	foundation	for	developing

useful	energy	efficiency	perform ance	data	and	indicators.	Measu res	contained	herein	are	based	on

a	very	small	participant	sample	size	and	have	some	issues	as	no ted	and	 for	 this	reason	should	be

viewed	as	a	very	high	level	snap shot	of	what	the	actual	populat ion	of	energy	efficiency	performance

actually	is.		Data	accuracy	exists	only	within	the	participant reported	data	range	and	should	not	be

extrapolated	beyond	this.	Data	pr ecision	is	low	due	to	the	smal l	sample	size.

In	the	process	of	soliciting	and	reviewing	participant	data,	mo re	questions	and	ideas	have	surfaced

that	 could	 pave	 the	 road	 to	 ongoing	 and	 dynamic	 performance	man agement	 tools.	This	 potential

will	 be	 constrained,	 however,	 by	 limited	 resources	 and	 potentia lly	 by	 demands	 for	 narrow	 and

quick‐response	cost	and	savings measurements	that	could	be	used too	literally.

Many	 ideas	 for	 future	 research	 and	 development	 have	 surfaced	 du ring	 various	 Subcommittee

discussions	 and	 this	 is	 natural	 for	 the	 early	 stages	 of	 an	 init iative	 to	 exchange	 performance

information	and	develop	knowledg e	and	intelligence	for	improvem ent	of	processes.	The	challenge

going	 forward	 will	 be	 to	 categorize	 and	 prioritize	 which	 areas and	 activities	 have	 the	 best	 cost‐

benefit	potential	given	limite d	resources	to	pursue	them.

Areas	of	note	include	(but	are	certainly	not	limited	to):

 Addressing	identified	data	issues via	increasing	participant	sa mple	size	and	developing	(or

adopting/borrowing)	 precise	 data	 definitions	 and	 reporting	 prot ocols	 along	 with	 peer

review	of	responses	(DEED	grant	a ctivities	included	review/erro r	analysis	of	2011	data).

 Using	EIA	data	for	IOU’s	and	coop eratives	to	expand	and	contras t	LPPC	performance	data.

 Creating	performance	analyses	da tabases	for	each	specific	year along	with	combined	years

and	producing	summary	data	reports.

 Obtaining	and	reviewing	extant	E E	performance	benchmarking	repo rts	and	data	(first	steps

have	been	taken	to	do	this	in	the	current	report).

 Developing	a	hierarchy	 of	measure usefulness	 to	reduce	 the	amou nt	of	data	collected	and

processed.	 For	instance,	 the	 80/20	 Pareto	 principle	 holds	 that 80%	 of	important	 outputs

are	the	result	of	20%	of	the	inputs.

 Developing	natural	subsets	of	utilities	with	similar	characteri stics,	so	 that	more	useful,	in‐

depth	 comparisons	 can	 be	 conducted	 (e.g.	 primarily	 wholesale	 ut ilities	 or	 utilities	 with

similar	peaking	characteristics).

 Creating	 a	 cross‐tabbed	 database	 o f	 energy	 efficiency	 portfolio s,	 including	 distinguishing

characteristics	and	programs,	an d	statistically	correlating	the m	to	performance	results.

 Adding	case	studies	to	the	website	to	allow	utilities	to	descri be	their	use	of	benchmark	data.

 Capturing	 information	 on	 measure longevity,	 perhaps	 in	 the	 form of	 a	 weighted	 average

measure	life	across	each	utility’s	energy	efficiency	program	po rtfolio	(will	be	facilitated	by

EIA‐861	data	starting	with	2013	data	year).

### LPPC EEWG Benchmarking Subcommittee

Page 17 

## Charts

Cost Measures

Chart 1: Total EE & DR Spending, 2011 (in millions of $)

Description:		Includes	direct,	in centive,	and	indirect	spending for	both	EE	and	DR	programs.



### Chart 2: Total EE Spending Relative to Retail Sales, 2011 (in $/MWh)

Description:	Relates	direct,	ince ntive,	and	indirect	EE	spendin g	 to	retail	sales,	normalizing	 for	utility	size.	 “Retail	Sales”

numbers	 for	 Tennessee	 Valley	 Authority,	Nebraska	 Public	 Power	D istrict,	 and	 Platte	 River	 Power	 Authority	 have	 been

adjusted	to	reflect	the	full	cust omer	base	to	which	these	utili ties	provide	EE	services.

### LPPC EEWG Benchmarking Subcommittee

Page 18 Chart 3: Total DR Spending Relative to Peak Demand, 2011 (in $/MW)

Description:	Relates	direct,	ince ntive,	and	indirect	DR	spendin g	to	peak	capacity,	normal izing	for	utility	size.



### Chart 4: Total EE & DR Spending Relative to Retail Revenue, 2011 (in %)

Description:		Relates	direct,	in centive,	and	indirect	EE	and	DR spending	to	each	utility’s	total	retail	revenues,	normalizing

for	utility	size.	This	measure	is skewed	by	a	utility’s	retail electric	rates.

### LPPC EEWG Benchmarking Subcommittee

Page 19 Chart 5: Total EE, DR, & Renewable FTE Employees by Type (External vs. Internal), 2011

Description:	 	 Shows	 the	 full‐time	 employees	 each	 utility	 has	 al located	 as	 resources	 for	 energy	 efficiency,	 demand

response,	 and	 renewable	 program activities.	 Data	 on	 FTE’s	 is	 no t	 collected	 by	 EIA‐861	 and	 was	 provided	 directly	 by

utilities	 to	 the	 LPPC	 EEWG.	 No	 FTE	 data	 was	 provided	 for	 Tennes see	 Valley	 Authority,	 Puerto	 Rico	 Electric	 Power

Authority,	and	Imperial Irrigation	District.

### LPPC EEWG Benchmarking Subcommittee

Page 20 Chart 6: Total EE, DR, & Renewable FTE Employees Relative to MWh Retail Sales, 2011

(in FTEs per million MWh)

Description:	 Relates	 the	 full‐time	 employees	 each	 utility	 has	 a llocated	 as	 resources	 for energy	 efficiency,	 demand

response,	and	renewable	program activities	 to	retail	sales,	nor malizing	 for	utility	size.	Data	on	FTEs	is	not	collected	by

EIA‐861	and	was	provided	by	utilit ies	directly	to	the	LPPC	EEWG .	“Retail	Sales”	numbers	for	Tennessee	Valley	Authority,

Nebraska	Public	Power	District,	and	Platte	River	Power	Authorit y	have	been	adjusted	to	reflect	the	full	customer	base	to

which	these	utilities	provide	EE services.	No	FTE	data	was	prov ided	for	Tennessee	Valley	Authority,	Puerto	Rico	Electric

Power	Authority,	and	Impe rial	Irrigation	District.

### LPPC EEWG Benchmarking Subcommittee

Page 21 

### Savings Measures

Chart 7: Incremental Energy Savings from EE, by Sector, 2011 (in MWh)

Description:	 Shows	 energy	 savings	 achieved	 by	 EE	 in	 current	 yea r	 (excludes	 energy	 effects	 of	 DR).	 Includes	 only	 new

participants. 18



### Chart 8: Incremental Energy Savings from EE Relative to Retail Sales, 2011 (in %)

Description:		“Shows	 the	energy	savings	achieved	by	EE	in	 the	c urrent	year	(excludes	effects	of	DR).	 Includes	only	new

participants. 19 Relates	 energy	 savings	 to	 retail	 sales,	 normalizing	 for	 utilit y	 size.	 Retail	 Sales”	 numbers	 for	 Tennessee

Valley	Authority,	Nebraska	Public	Power	District,	and	Platte	Ri ver	Power	Authority	have	been	a djusted	to	reflect	the	full

customer	base	to	which	these	uti lities	provide	EE	services.	Gre en	shading	indicates	better	performance.

18 See earlier footnote for definition of “incremental effects.”

19 See earlier footnote for definition of “incremental effects.”

### LPPC EEWG Benchmarking Subcommittee

Page 22 Chart 9: Incremental Energy Savings from Sector

‐ Specific EE Relative to Retail Sales from

that Sector, 2011 (in %)

Description:	 	Shows	 the	energy	 savings	achieved	 by	EE	in	 the	 cu rrent	 year	 (excludes	effects	 of	DR).	 Includes	 only	new

participants. 20 Relates	energy	savings	at	the	sector‐level	to	retail	sales	fro m	that	sector,	normalizing for	utility	size.	“Retail

Sales”	numbers	 for	Tennessee	Valley	Authority,	Nebraska	Public Power	District,	and	Platte	River	Power	Authority	have

been	adjusted	to	reflect	the	full	customer	base	to	which	these utilities	provide	EE	services.	Green	shading	indicates	better

performance.



### Chart 10: Peak Demand Reduction from EE & DR, 2011 (in MW)

Description:		Shows	peak	demand	saved	by	EE	and	DR	programs.	On ly	seven	utilities	reported	DR	peak	demand	savings

from	DR,	a	very	small	sample	s ize	for	comparison	purposes.

20 See earlier footnote for definition of “incremental effects.”

### LPPC EEWG Benchmarking Subcommittee

Page 23 Chart 11: Peak Demand Reduction from EE & DR, by Sector, 2011 (in MW)

Description:		Shows	peak	demand	saved	by	EE	and	DR	programs.	On ly	seven	utilities	reported	peak	demand	savings	from

DR,	a	very	small	sample	size for	comparison	purposes.



### Chart 12: Peak Demand Reduction from EE & DR Relative to Annual System Peak

Demand, 2011 (in %)

Description:		Shows	peak	demand	saved	by	EE	and	DR	programs.	Re lates	peak	demand	savings	 to	annual	system	peak

demand,	normalizing	 for	utility	size.	Depicts	 the	relative	aggr essiveness	of	DSM	programs.	Only	seven	utilities	reported

peak	demand	savings	from	DR.	Gr een	shading	indicates	better	per formance.

### LPPC EEWG Benchmarking Subcommittee

Page 24 Chart 13: Peak Demand Reduction from EE & DR Relative to Annual System Peak

Demand, by Sector, 2011 (in %)

Description:		Shows	peak	demand	saved	by	EE	and	DR	programs.	Re lates	peak	demand	savings	 to	annual	system	peak

demand,	normalizing	for	utility	size.	The	ranking	depicts	the	r elative	aggressiveness	of	DSM	p rograms.	Again,	only	seven

utilities	reported	peak	demand	s avings	from	DR.	Green	shading	i ndicates	better	performance.

### LPPC EEWG Benchmarking Subcommittee

Page 25 

### Cost

‐ to

‐ Savings Rate Measures

Chart 14: EE Spending Relative to Incremental Energy Savings, 2011 (in $/MWh)

Description:		Relates	EE	spending to	incremental	MWh	saved.		Me asures	cost‐effectiveness	achieved on a first year basis ;

does	 not	 account	 for	 measure	 life	 or	 levelized	 costs.	 Includes only	 new	 participants. 21 Green	 shading	 indicates	 better

performance.



### Chart 15: EE Spending Rel. to Incremental Energy Savings, by Sector, 2011 (in $/MWh)

Description:		Relates	EE	spending to	incremental	MWh	saved.		Me asures	cost‐effectiveness	achieved on a first year basis ;

does	 not	 account	 for	 measure	 life	 or	 levelized	 costs.	 Includes direct	 spending	 and	 incentives.	 Includes	 only	 new

participants. 22 Green	shading	indicates	better	performance.

21 See earlier footnote for definition of “incremental effects.”

22 See earlier footnote for definition of “incremental effects.”

### LPPC EEWG Benchmarking Subcommittee

Page 26 Chart 16: EE & DR Spending Relative to Peak Demand Saved (in $/kW)

Description:	Relates	EE	spending to	peak	demand	reductions	from EE	programs	(blue)	and	relates	DR	spending	to	peak

demand	reductions	from	DR	programs	(red).	This	is	useful	for	ut ilities	that	measure	demand	acquisition	against	the	cost

of	installed	generation.	Utilities	with	high	 $/kW	numbers	gener ally	have	excess	capacity	and/or	little	emphasis	 on	DR.

Green	shading	indicates	better	performance.



### Chart 17: Incremental Energy Savings from EE Relative to # of (Internal & External) EE

FTE’s & from DR Relative to # of (Internal & External) DR FTE’s, 2011 (in MWh/FTE)

Description:		Relates	energy	savings	to	the	number	of	EE	and	DR FTEs.	Data	on	FTEs	is	not	collected	by	EIA‐861	and	was

provided	by	utilities	directly	 to	 the	LPPC	EEWG.	 Includes	only new	participants	in	old	programs	and	all	participants	in

new	programs. 23 No	FTE	data	was	 provided	 for	Te nnessee	Valley	Authority,	Puert o	Rico	Electric	Power	Authority,	and

Imperial	Irrigation	District.

23 See earlier footnote for definition of “incremental effects.”

### LPPC EEWG Benchmarking Subcommittee

Page 27 

### Trends: 2009

‐ 2011

Chart 18: 2009

‐ 2011 Total Retail Sales (in MWh)

Description:	 “Retail	 Sales”	 numbe rs	 for	 Tennessee	 Valley	 Author ity,	 Nebraska	 Public	 Power	 District,	 and	 Platte	 River

Power	Authority	have	been	adjus ted	to	reflect	the	full	customer base	to	which	these	utili ties	provide	EE	services.



### Chart 19: 2009

‐ 2011 Retail Revenue (in billions of $)

Description:	“Retail	Revenue”	nu mbers	for	Tennessee	Valley	Auth ority,	Nebraska	Public	Power	District,	and	Platte	River

Power	Authority	have	been	adjus ted	to	reflect	the	full	customer base	to	which	these	utili ties	provide	EE	services.

### LPPC EEWG Benchmarking Subcommittee

Page 28 Chart 20: 2009

‐ 2011 Total EE & DR Spending (in millions of $)

Chart 21: 2009

‐ 2011 Total EE Spending (in millions of $)

### LPPC EEWG Benchmarking Subcommittee

Page 29 Chart 22: 2009

‐ 2011 Total DR Spending (in millions of $)

Chart 23: 2009

‐ 2011 Total EE & DR Spending Relative to Retail Revenue (in %)

Description:	:	“Retail	Revenue” numbers	for	Tennessee	Valley	Au thority,	Nebraska	Public	Powe r	District,	and	Platte	River

Power	Authority	have	been	adjus ted	to	reflect	the	full	customer base	to	which	these	utilities provide	EE	services.	Green

shading	indicates	better	performance.

### LPPC EEWG Benchmarking Subcommittee

Page 30 Chart 24: 2009

‐ 2011 Total Incremental Energy Savings from EE (in MWh)

Chart 25: 2009

‐ 2011 Total EE & DR FTE’s (Internal and External/Contracted)

Description:	 No	 FTE	 data	 was	 provided	 for	 Tennessee	 Valley	 Auth ority,	 Puerto	 Rico	 Elect ric	 Power	 Authority,	 and

Imperial	Irrigation	District.

### LPPC EEWG Benchmarking Subcommittee

Page 31 Chart 26: 2009

‐ 2011 Total Incremental Savings from EE Rel. to MWh Retail Sales (in %)

Description:	 “Retail	 Sales”	 numbe rs	 for	 Tennessee	 Valley	 Author ity,	 Nebraska	 Public	 Power	 District,	 and	 Platte	 River

Power	Authority	have	been	adjusted	to	reflect	the	full	customer base	to	which	these	utilities	provide	EE	services.	Green

shading	indicates	better	performance.



### Chart 27: 2009

‐ 2011 Total Incremental EE Spending Relative to Incremental EE MWh

Saved (in $/MWh)

Description:	Green	shading	ind icates	better	performance.

### LPPC EEWG Benchmarking Subcommittee

Page 32 Chart 28: 2009

‐ 2011 Total Incremental EE Spending Relative to Incremental Peak kW

Load Reduction from EE (in $/kW)

Description:	 Green	 shading	 indicates	 better	 performance.	 Utilit ies	 with	 high	 $/kW	 numbers	 generally	 have	 excess

capacity	and/or	little	emphasis	on	DR.



### Chart 29: 2009

‐ 2011 Load Factor (MWh per Peak kW x 8,760)

### LPPC EEWG Benchmarking Subcommittee

Page 33 

### Short

‐ Term and Long

‐ Term Goals

The	Benchmarking	Subcommittee’s	supplemental	data	survey	asked utilities	to	report	their	short‐

term	and	long‐term	energy	 savings	goals.	These	goals	are	depict ed	below	 on	a	percent	 of	 system

basis.



### Chart 30: Short

‐ Term Goals for Energy Savings (MWh as % of Total MWh Retail Sales)

Chart 31: Long

‐ Term Goals for Energy Savings (MWh as % of Total MWh Retail Sales)

Note:	All	energy	savings	are	from	energy	efficiency,	except	for Austin	Energy,	which	includes	a	small	amount

from	demand	response.

### LPPC EEWG Benchmarking Subcommittee

Page 34 Chart 32: Short

‐ Term Demand Goals for Energy Efficiency and Demand Response (MW as

% of Peak Demand)

Note:	Goals	over	multiple	years were	averaged	and	are	represent ed	here	on	a	one‐year	basis.



### Chart 33: Long

‐ Term Demand Goals for Energy Efficiency (MW as % of Peak Demand)

### LPPC EEWG Benchmarking Subcommittee

Page 35 Chart 34: Long

‐ Term Demand Goals for Demand Response (MW as % of Peak Demand)

Chart 35: Long

‐ Term Demand Goals for Demand

‐ Side Renewables (MW Installed

Capacity as % of Peak Demand)

### LPPC EEWG Benchmarking Subcommittee

Page 36 Chart 36: Long

‐ Term Goals for Demand

‐ Side Renewables (MWh Annually as % of Total

MWh Retail Sales)

Chart 37: Long

‐ Term Demand Goals for Supply

‐ Side Renewables (MW Installed Capacity

as % of Peak Demand)

### LPPC EEWG Benchmarking Subcommittee

Page 37 Chart 38: Long

‐ Term Goals for Supply

‐ Side Renewables (MWh Annually as % of Total

MWh Retail Sales)

### LPPC EEWG Benchmarking Subcommittee

Page 38 

### National Comparison 24

The	national	comparison	percentil e	table	and	charts	that	follow are	based	on	2011	EIA	data	from	all

utilities	 that	 filled	 out	 EIA	 Fo rm‐861,	 Schedule	 6,	 including	 L PPC	 members.	 Charted	 data	 may

exclude	extreme	values	 for	visual	clarity.	A	percentile	is	a	va lue	on	a	scale	of	0‐100	 that	indicates

the	percent	of	a	distribution	above	or	below	it.

As	 an	 example,	 Austin	 Energy	 experienced	 a	 cost‐effectiveness	 r ate	 of	 $125/MWh	 saved	 by	 EE,

which	 resulted	 in	 a	 percentile	 rank	 of	 28%.	 This	 means	 that	 abo ut	 72%	 of	 the	 EIA	 respondents

were	 as	 high	 or	 higher	 in	 terms	 of	 $/MWh	 saved	 by	 EE.	 Conversel y,	 about	 28%	 of	 the	 EIA

respondents	were	as	low	or	lower. Depending	on	the	measure,	a	l ow	percentile	can	indicate	good	or

bad	relative	standing.

The national comparison data (in	contrast	to	the	data	in	the rest	of	the	report)	are	taken directly

from	EIA	and	do	not	reflect	acco mmodations	or	corrections	made by	LPPC	utilities	that	are

included	elsewhere	in	this	report .	Platte	River	Power	Authority ’s	four	member	utilities	(City	of	Fort

Collins,	City	of	Longmont,	City	o f	Loveland,	and	Town	of	Estes Park)	are	included	here	in	lieu	of

Platte	River	Power	Authority,	which	does	not	report	on	Schedule 6.	Each	point	on	a	chart

represents	one	of	these	LPPC or	LPPC‐related	utilities.

The	data	for	TVA,	NPPD,	and	Plat te	River	in	the	national	compar ison	may	be	misleading,	especially

when	compared	to	data	earlier	in	the	report,	because	these	data have	not	been	adjusted	to	account

for	its	wholesale	customers’	sales	and	revenues.

24 Data in the National Comparison section is drawn directly from EIA’s 2011 data and does not include any self

‐

corrected data from LPPC utilities. Also, in contrast to the rest of the charts in this report, spending numbers

do not include weighted indirect costs for EE and DR.LPPCEEWGBenchmarkingSubcommitteePage39DataTableforFiveKeyEEPerformanceMeasuresLPPCUtilityNameCostEffectivenessEESpending$/MWhSavedPercentileEESpending$asa%ofRetailSales$PercentileEESpending$/RetailSalesMWhPercentileEESpending$(,000)PercentileEESavingsMWhasa%ofRetailSalesMWhPercentileAustin Energy125$28% 1.30% 70% 1.13$67% 14,768$88% 0.91% 76%City of Colorado Springs - (CO)80$12% 0.40% 35% 0.34$31% 1,544$66% 0.42% 56%City of Fort Collins - (CO)188$44% 2.88% 90% 1.98$83% 2,870$73% 1.06% 81%City of Longmont185$43% 1.19% 65% 0.80$55% 637$59% 0.43% 56%City of Loveland - (CO)123$27% 0.76% 53% 0.50$41% 351$55% 0.41% 55%City of San Antonio - (TX)337$69% 1.30% 70% 1.09$65% 23,468$91% 0.32% 49%City of Seattle - (WA)304$65% 4.99% 97% 3.41$92% 32,707$93% 1.12% 83%City of Tacoma - (WA)203$48% 4.54% 96% 2.62$88% 12,647$87% 1.29% 88%Imperial Irrigation District629$87% 1.65% 77% 1.92$82% 6,307$80% 0.31% 48%JEA141$32% 0.71% 50% 0.80$56% 9,760$85% 0.57% 64%Long Island Power Authority242$55% 1.33% 71% 2.51$87% 47,725$95% 1.04% 80%Los Angeles Department of Water & Power143$33% 1.69% 78% 2.14$84% 49,530$96% 1.49% 92%Nebraska Public Power District173$39% 1.72% 78% 1.39$73% 4,533$78% 0.80% 71%Omaha Public Power District120$26% 0.36% 32% 0.26$27% 2,823$73% 0.22% 40%Orlando Utilities Comm319$67% 0.67% 49% 0.71$53% 4,316$77% 0.22% 41%PUD No 1 of Chelan County145$33% 3.34% 92% 1.10$65% 1,728$67% 0.76% 69%PUD No 1 of Clark County - (WA)172$38% 3.30% 92% 2.59$88% 11,583$86% 1.51% 92%PUD No 2 of Grant County81$12% 2.98% 91% 1.00$63% 4,019$76% 1.24% 88%Sacramento Municipal Util Dist186$43% 2.56% 87% 3.05$90% 31,707$93% 1.64% 93%Salt River Project77$11% 1.20% 66% 1.12$67% 29,961$92% 1.46% 92%Snohomish County PUD No 1250$58% 3.90% 95% 2.95$89% 20,298$90% 1.18% 86%South Carolina Pub Serv Auth590$86% 1.31% 70% 0.89$59% 9,997$85% 0.15% 32%Town of Estes Park286$62% 1.41% 72% 1.35$72% 172$43% 0.47% 59%Note: all EE spending is incrementalNote:	The	following	cities	are	included	here	because	they	are	served	by	Platte	River	Power	Authority:	Fort	Collins,	Longmont,Loveland,	and	Estes	Park.LPPCEEWGBenchmarkingSubcommitteePage40Chart39:Percentilesfor“Cost‐Effectiveness,”orEESpendingRelativetoIncrementalEnergySavings(in$/MWh)LPPCEEWGBenchmarkingSubcommitteePage41Chart40:PercentilesforTotalEESpendingRelativetoRetailRevenue(in%)LPPCEEWGBenchmarkingSubcommitteePage42Chart41:PercentilesforTotalEESpendingRelativetoRetailSales(in$/MWh)LPPCEEWGBenchmarkingSubcommitteePage43Chart42:PercentilesforEESpending(inthousandsof$)LPPCEEWGBenchmarkingSubcommitteePage44Chart43:PercentilesforIncrementalEnergySavingsfromEERelativetoRetailSales(in%)LPPCEEWGBenchmarkingSubcommitteePage45DataTableforFourKeyDRPerformanceMeasuresUtilityName% Summer Peak (MW)of Actual Annual DRPercentile% Winter Peak (MW)of Actual Annual DRPercentileRedundancy (Ratio ofPotential to Actual)PercentileDirect and IncentiveCosts per ActualMW($/MW)PercentileAustin Energy 0.54% 36% 3.42% 45% 0.01 2% 34,173$ 52.40%City of Colorado Springs - (CO) 1.03% 20% 32,169$ 51.20%City of Fort Collins - (CO) 2.71% 37% 24,848$ 42.60%City of LongmontCity of Loveland - (CO) 7.48% 100% 7.03% 68% 119,589$ 81.70%City of San Antonio - (TX) 0.01% 2% 2.28% 34% 146,021$ 86.90%City of Seattle - (WA) 2.90% 72%City of Tacoma - (WA) 0.17% 20%Imperial Irrigation DistrictJEA 0.15% 16%Long Island Power AuthorityLos Angeles Department of Water & PowerNebraska Public Power District 0.41% 31% 26.36% 97% 0.02 9% 4,540$ 12.60%Omaha Public Power District 3.06% 42% 29,012$ 47.50%Orlando Utilities CommPUD No 1 of Chelan CountyPUD No 1 of Clark County - (WA)PUD No 2 of Grant CountySacramento Municipal Util DistSalt River Project7.77% 71% 10,065$ 26.80%Snohomish County PUD No 1South Carolina Pub Serv Auth 0.11% 13% 0% 60,000$ 67.80%Town of Estes Park29.63% 1,250$ 4.00%Note:	The	following	cities	are	included	here	because	they	are	served	by	Platte	River	Power	Authority:	Fort	Collins,	Longmont,Loveland,	and	Estes	Park.LPPCEEWGBenchmarkingSubcommitteePage46Chart44:PercentilesforActualAnnualDemandReductionfromDRasaPercentofSummerSystemPeakDemand(%)Chart45:PercentilesforActualAnnualDemandReductionfromDRasaPercentofWinterSystemPeakDemand(%)LPPCEEWGBenchmarkingSubcommitteePage47Chart46:PercentilesforDirectandIncentiveCostsRelativetoActualPeakReduction(in$/MW)LPPCEEWGBenchmarkingSubcommitteePage48LPPCEEWGBenchmarkingSubcommitteePage49AppendixA:BenchmarkingDatabyUtility(MainSource:EIAForm861,2011)25Page	1	of	425LPPCutilitiesweregiventheopportunitytocorrecttheirdata.TheseExcelsnapshotsreflectedthecorrecteddata.LPPCEEWGBenchmarkingSubcommitteePage50Page	2	of	4LPPCEEWGBenchmarkingSubcommitteePage51Page	3	of	4Page	4	of	4LPPCEEWGBenchmarkingSubcommitteePage52

### LPPC EEWG Benchmarking Subcommittee

Page 53 

## Appendix B: Overview of DEED Grant Activities

In	the	Fall	of	2012	Santee	Cooper	worked	with	five	other	DEED	u tilities	(Austin	Energy,	Nebraska

Public	 Power	 District,	 Orlando	 Utilities	 Commission,	 Omaha	 Publ ic	 Power	 District,	 and	 Tacoma

Public	Utilities)	and	CEEP	staff	to	apply	for	a	Demonstration	o f	Energy	and	Efficiency	Developments

(DEED)	 grant	 from	 the	 American	 Public	 Power	 Association.	 The	 gr oup	 was	 awarded	 a	 grant	 of

$75,000	for	work	beginning	in	January	2013	and	running	through April	2014,	to	be	performed	by

CEEP	staff	with	in‐kind	staff	ti me	contributed	by	the	participa ting	utilities.

The	DEED	activities	are	designed to	enable	public	power	utiliti es	to	make	better‐informed	decisions

about	how	to	spend	limited	energy	efficiency	resources	by	impro ving	quality,	access	to,	and	ease	of

interpretation	 of	 peer	 data.	Officials	 constantly	 demand	 data	 f rom	 public	 power	 utilities	 to	 show

how	their	energy	efficiency	(EE)	program	performance	stacks	up to	peer	performance.	Yet,	the	best

source	of	national	EE	data,	EIA’s	861	survey,	is	confusing	and filled	out	inconsistently	from	utility	to

utility.	Resource‐constrained	utilities	find	it	difficult	to	ac cess	reliable	data,	make	apples‐to‐apples

comparisons,	 confidently	 rank	 the ir	 EE	 performance,	 and	 decide how	 to	 allocate	 resources.	 The

project	 works	 to	 reduce	 utilities’	 time	 burden	 to	 report	 EIA‐86 1	 Schedule	 6	 data	 and	 generate

benchmark	comparisons.

To	date,	 the	LPPC	EEWG	Benchmarking	Subcommittee	has	partnered closely	with	 the	U.S.	Energy

Information	Administration	to:

 Submit	feedback	on	the	EIA‐produc ed	User	Guide	for	EIA	Form	861 ,	Schedule	6.

 Plan,	develop,	and	conduct	two	we binars	on	EIA	energy	efficienc y	data,	which	were

attended	by	167	utility	staff,	i nclude	86	public	power	utility staff	(Spring	2013).

 Provide	70	public	power	utilities with	technical	assistance	on EIA	Form	861, Schedule	6.

 Submit	feedback	on	EIA’s	proposed changes	to	their	data	collect ion	for	EIA	Form	861,

Schedule	6	for	the	2014	data	co llection	cycle	(2013	data	year).

### LPPC EEWG Benchmarking Subcommittee

Page 54 In	Winter/Spring	2013,	CEEP	staff	analyzed	the	2011	EIA‐861,	Sc hedule	6	data	to	identify	potential

data	measurement	and	reporting	errors	made	by	public	power	util ities.	CEEP	staff	then	contacted

staff	at	 75+	 utilities	in	 order	 to	 discuss	 these	 potential	erro rs	and	 help	 utility	 staff	improve	 their

reporting	practices	fo r	subsequent	years.



### Table B

‐ 1: Summary of DEED Activities and Timeline

Activity Description Status

1) Create	Interactive

Web	Benchmarking

Tool We	will	create	a	user‐friend ly	online	tool	that	generates

customizable	peer	comparison charts	for	indicators	such

as	energy	savings,	potenti al	demand	reduction,	and

spending	relative	to	size.	User s	may	filter	by	utility	size,

region,	etc.	The	tool	will	incl ude	data	from	500+	utilities

that	submit	EIA‐861,	including	154+	public	power

utilities.	Future	year	uploads will	require	marginal	effort. Anticipated	Completion	in

Autumn	2013

2) Develop	and	Conduct

Webinars To	improve	national	data quality,	we	will	conduct

webinars	on	how	to	generate	reliable,	comparable	data

for	EIA‐861,	Sched.	6. Two	webinars	held	Spring

2013;	Two	more	webinars

planned	for	Spring	2014

3) Write	Practical	Guide

to	EIA‐861 This	guide	will	give	examples	and	outline	consensus

reporting	practices	clarified	via	project	outreach. Activity	scheduled	for

Winter	2013/2014

4) Conduct	Technical

Assistance	Outreach Through	outreach,	we	will	identify	and	correct	mistakes

in	EIA‐861,	Sched.	6	data,	spur webinar	participation	and

resource	use,	and	publicize	the	benchmarking	tool.	We

expect	one	year	of	quality	co ntrol	outreach,	together	with

new	resources,	to	result	in	sustained	improvement	in

reporting	practices. 2013	outreach	conducted

Spring	2013;	minimal

additional	outreach

planned	for	Spring	2014

5) Provide

Benchmarking

Access	for	Small

Utilities Small	DEED	utilities	not	re quired	to	report	EIA‐861,

Sched.	6	may	voluntarily	submi t	data	to	the	online	tool	to

generate	comparisons.	They will	have	full	access	to

technical	assistance	and	webinars. Benchmarking

opportunity	to	be

announced	to	small

utilities	in	Autumn	2013

### LPPC EEWG Benchmarking Subcommittee

Page 55 

## Appendix C: EEWG Benchmarking Subcommittee’s Public

Comments to the U.S. Energy Information Administration regarding

EIA Form 861 (Submitted May 6, 2013)

To: Rebecca	Peterson, ERS2014@eia.gov

Re: Public	Comments	on	Form	EIA–861, ‘‘Annual	Electric	Power	Indus try	Report’’

From:

Volunteer	 members	 of	 the	 Large	 Pu blic	 Power	 Council	 Energy	 Effi ciency	 Working	 Group	 (LPPC

EEWG)	Benchmarking	Subcommittee,	led	by:

 Subcommittee	Chair	Norman	Muraya	(Austin	Energy) norman.muraya@austinenergy.com

,

 Member	Tom	Gross	(Orlando Utilities	Commission) tgross@ouc.com ,	and

 Facilitated	by	Annika	Brink	(Alli ance	to	Save	Energy/Clean	and Efficient	Energy	Program

for	Public	Power) abrink@ase.org

.

Over	the	course	of	the	past	year,	the	LPPC	EEWG’s	Benchmarking Subcommittee	has leveraged	data

from	Form	EIA‐861,	Schedule	6	 to	benchmark	 the	energy	efficienc y	activities	and	performance	of

LPPC	member	utilities.	This	work	has	included	ongoing	discussio ns	among	Subcommittee	members

and	 with	 the	 Energy	 Information	 Administration	 regarding	 the	 qu ality	 and	 consistency	 of	 data

collected	via	Form	EIA‐861.	Questions	and	comments	on	the	publi c	comments	submitted	below	can

be	directed	toward	the	three	working	group	participants	listed above.

Comments on Form EIA

‐ 861: Excel Version of Form

Incorrect	terminology	in	Tab “ENERGY	EFFICIENCY	6a”

1. Tab	“ENERGY	EFFICIENCY	6a”

a. In	the	title	of	the	last	section, the	word	“Weighed”	in	“Weighe d	Average	Life	for

Portfolio	(Years)	‐	Use	Spreadsh eet	to	Calculate”	should	be	rep laced	with

“Weighted.”

b. In	line	10,	the	word	“Weighed”	i n	“Weighed	Average	Life”	should be	replaced	with

“Weighted.”

2. Tab	“Weighed	average	life	calculator”

a. In	the	name	of	the	tab,	the	word	“Weighed”	should	be	replaced	w ith	“Weighted.”

3. To	verify	that	the	term	“Weighed	average	life”	is	not	widely	us ed,	try	an	internet	for	this

term,	which	retrieves	zero	resul ts.	A	search	for	“Weighted	aver age	life”	on	the	other	hand,

returns	over	3	million	results. To	take	things	a	step	further: we	prefer	“Weighted	average

measure	life,”	which	is	widely	u sed	in	utility	energy	efficienc y	and	returns	over	7,000

results,	most	of	which	seem	to	re late	directly	back	to	energy	e fficiency.

©	used	instead	of	(c)

 In	Tabs	“ENERGY	EFFICIENCY	6a,”	“DEMAND	RESPONSE	6b,”	and	“DYNA MIC	PRICING

PROGRAMS	6c,”	Excel	autocorrect	h as	mistakenly	replaced	(c)	wit h	©	for	the	“Industrial”

columns.

Inconsistency	between	“whom”	and	“that”

### LPPC EEWG Benchmarking Subcommittee

Page 56  In	Tab	“ADVANCED	METERING	AND	CUSTOM	6d,”	Line	6	asks	for	the	“ Number	of

Customers	for	whom...”	while	Line	9	asks	for	the	“Number	of	custo mers	that	can...”

In	the	tab	labeled	“Weighed	average	life	calculator,”	the	title “Residential	Customers”	links	back	to

the	 “ENERGY	 EFFICIENCY	 6a”	 Tab,	 while	 the	 titles	 for	 “Commercia l	 Customers,”	 “Industrial

Customers,”	and	“Transportation	Customers”	do	not	link	back	to anything.	This	is	confusing.

In	the	tab	labeled	“Weighed	aver age	life	calculator,”	the	termi nology	“Average	mean	life	program”	is

unclear.	 This	 should	 read	 “Average	 measure	 life,”	 or	 “Average	 l ife	 of	 program	 or	 measure,”	 or

“Average	life	of	measu re	or	measures	in	program”	(Columns	D,	I, N,	and	S).

Comments on Form EIA

‐ 861: Pdf Version of Instructions

On	Page	2,	Point	 9,	where	 the	instructions	 state	 “See	 the	Gloss ary	 for	 terms	used	in	 this	survey,”

please	provide	a	link	to	the	Glossary.

On	Page	2,	Point	9	where	the	instructions	state	“The	financial and	accounting	terms	are	consistent

as	outlined	in	the	Uniform	System	of	Accounts	for	Public	Utilit ies	and	Licensees	(U.S.	of	A.)	(18	CFR

Part	101),”	please	provid e	a	link	to	this	source.

On	 Page	 9‐10,	 under	 “SCHEDULE	 6. DEMAND‐SIDE	 MANAGEMENT	 AND	 SMA RT	 GRID

INFORMATION,”	 additional	 guidance	 is	 needed	 on	 the	 reporting	 re sponsibilities	 of	 wholesale

utilities	and	joint	action	agencies,	etc.	that	conduct	demand‐s ide	management	activities	on	behalf	of

distribution	utilities.	The	instructions	note	that	“Power	suppl y	cooperatives,	municipal	joint	action

agencies,	 and	 Federal	 Power	 Mark eting	 Administrations	 should	 co ordinate	 the	 reporting	 of	 DSM

information	with	their	power	pu rchasing	utilities	to	avoid	doub le	counting	the	effects	and	costs	of

DSM	programs.”	In	this	section,	EIA	should	also	state	its	prefe rence	for	which	entity	should	report

this	information.

Typo	on	Page	10:	Where	the	instructions	state	“An	energy	effici ency	resource	must	achieve	a	long

term	continuous	reduction	in	dema nd	for	electricity	and	are	ava ilable...”	the	word	“are”	should	read

“be.”

On	 Page	 10	 where	 the	 instructions	 state	 “Examples	 are	 replacing light	 bulbs	 with	 more	 efficient

technology	 or	 replacing	 older	 HVA C	 systems	 with	 high	 efficiency systems,”	 we	 recommend

replacing	this	with	better	exampl es:	“Examples	are	adding	addit ional	insulation	in	older	homes	or

replacing	 an	 HVAC	 system	 with	 a	 higher	 efficiency	 system	 that	 e xceeds	 current	 codes	 and

standards.”

On	Page	11,	under	“1.	Incremental Annual	Savings—Reporting	Year ,”	the	two	bullets	are	confusing

and	could	be	eliminated	 to	simply	read:	“Participants	in	DSM	pr ograms.”	 If	EIA	insists	on	keeping

both	bullets,	then	we	recommend	r eplacing	“DSM	programs	that	op erated	in	the	previous	reporting

year”	with	“Existing	DSM	programs.”

### LPPC EEWG Benchmarking Subcommittee

Page 57 On	Page	11,	under	“Incremental	Sav ings—Life	Cycle,	we	recommend striking	“DSM	programs	have

a	useful	life,	and	 the	net	effec ts	of	 these	programs	will	dimin ish	over	 time.	To	 the	extent	possible

consider	the	useful	life	of	effi ciency	by	accounting	for	buildi ng	demolition,	equipment	degradation,

and	program	attrition.”	This	gui dance	is	directly	in	conflict	w ith	EIA	guidance	on	Page	10	to	report

Gross	Savings.	As	a	reminder:	EIA	has	decided	to	switch	from	Ne t	Savings	to	Gross	Savings	in	order

to	achieve	better	consistency	of	reporting	across	different	uti lities.	This	guidance	would	introduce	a

new	 opportunity	 for	 inconsistenc y	 by	 asking	 utilities	 to	 self‐d efine	 a	 type	 of	 Net	 Savings.	 	 We

recommend	replacing	the	phrase	q uoted	above	with,	“Gross	saving s	do	not	consider	free	ridership,

spillover	effects,	building	demo lition,	equipment	degradation, and	program	attrition.”

Page	 11:	 It	 might	 be	 better	 if	 the	 terminology	 did	 not	 vary	 sli ghtly	 between	 the	 form	 and	 the

instructions:

 “Reporting	Year	Incremental	Annual Savings”	vs.	“Incremental	An nual	Savings—Reporting

Year”

 “Incremental	Life	Cycle	Savings” vs.	“Incremental	Savings—Life Cycle”

Page	 11:	 In	 general,	 the	 proposed	 instructions	 use	 the	 word	 “pr ogram”	 where	 “measure”	 or

“project”	would	be	more	appropriate.

 Here,	and	throughout	the	instruc tions,	it	would	be	more	accurat e	to	refer	to	“DSM	program

measures”	rather	than	“DSM	progr ams”	when	discussing	the	useful life	of	savings.

 The	instructions	also	state	that a	“Life	cycle”	mean	the	number of	years	the	program	is

planned	to	exist...”	First,	there	is	a	typo:	it	should	read	“mean s”	rather	than	“mean.”	Second,

this	is	inaccurate:	a	program	ma y	exist	for	2	years,	but	instal l	measures	that	last	30	years.

Clearly,	EIA	wants	to	collect	inf ormation	on	savings	from	the	i nstalled	measures	over	the

course	of	30	years	rather	than	f rom	the	two	years	the	program	i s	in	existence,	actively

implementing	new	measures.

 Building	off	the	example	outlined	above,	we	recommend	replacing “the	number	of	years	the

program	is	planned	to	exist”	with “the	number	of	years	the	effe cts	of	the	program	measures

are	planned	to	exist.”

 For	“Incremental	Savings—Life	Cy cle,”	instead	of	“the	life	cycl e	of	the	incremental	programs

and	participants,”	it	would	be	b etter	to	say,	“the	life	cycle	o f	the	program	measures

implemented	in	the	reporting	year.”

Page	12:	Point	3,	Costs

 We	recommend	that	this	section	of fer	guidance	on	what	“all	othe r	costs”	should	include,	e.g.

utility	DSM	staff	time,	administ ration,	marketing,	contractual obligations,	EM&V	costs,	etc.

 We	recommend	that	this	section	of fer	guidance	on	whether	or	not costs	should	be

“loaded”/“fully	burdened”	i.e. include	fringe,	overhead,	etc.

 We	think	EIA	should	consider	pu lling	out	marketing	costs	into	t heir	own,	third,	separate

category.	Marketing	of ten	composes	a	large	percentage	of	DSM	bu dgets,	making	this	data

useful	for	benchmarking	purposes .	(If	EIA	makes	this	change,	it should	provide	guidance	on

whether	or	not	to	include	marketi ng	staff	labor	costs	as	part	o f	marketing	DSM	costs.)

### LPPC EEWG Benchmarking Subcommittee

Page 58  The	instructions	designate	“in‐k ind	services	(e.g.	design	work) ”	as	part	of	customer

incentives.	However,	the	inclusi on	here	of	“in‐kind	services”	c ould	be	misconstrued	to

include	many	types	of	activities traditionally	undertaken	by	ut ility	energy	efficiency	staff

and	not	generally	counted	as	“c ustomer	incentives.”	Additional clarification	is	required.

 We	recommend	not	switching	back and	forth	between	“reporting	ye ar”	and	“incremental

year”	if	these	terms	are	meant	to	be	used	interchangeably.	It	w ould	be	clearer	to	choose	one

term	and	use	it	consistently: we	prefer	“reporting	year.”

 The	proposed	instructions	state	that,	“Reporting	Year	Increment al	costs	should	include	all

costs	for	the	programs	for	years prior	to	the	in cremental	year if	these	costs	were	incurred	at

part	of	the	start	up	of	the	program.”

o “costs”	should	be	capita lized	to	read	“Costs.”

o “at”	should	read	“as”

o As	the	proposed	instructions	currently	read,	it	is	not	clear	wh ether	or	not	start	up

costs	are	meant	to	be	re‐reported	each	year	that	the	program	is in	existence.	Should

the	utility	report	the	entire	start	up	cost	again	each	year?	Sh ould	it	only	re‐report	a

certain	portion	that	it	consider s	attributable	to	program	activ ities	that	occurred	in

the	reporting	year?

o Please	include	an	example	that	shows	how	to	count	start	up	cost s	incurred	in

previous	years,	while	avoiding	d ouble‐counting	across	years.

Page	12:	SCHEDULE	6.	PART	B.	DEMAND	RESPONSE	PROGRAMS

 For	“Demand	Response	Programs”	we recommend	that	EIA	replace	“d imming	of	lights”	with

“cycling	HVAC”	(because	it’s	a	more	common	DR	program).

 Instead	of	“shutting	down	indust rial	processes”	we	recommend	“s hifting	industrial

processes.”

 For	“Potential	peak	demand	savin gs”	we	are	not	in	agreement	as to	whether	or	not	EIA

should	be	collecting	information on	energy	savings	in	MWh	from demand	response

programs.	It	is	not	clear	that	there	are	significant	energy	sav ings	from	demand	response,

because	energy	use	is	generally shifted	to	non‐peak	hours.	(Ind ustrial/production

processes	are	shifted,	generator s	are	less	efficient,	HVAC	is	d eferred	momentarily,	etc.)

 For	“Potential	peak	demand	savings”	EIA	requests	information	on grid	intera ctive	water

heaters.	Please	add	a	link	to	th e	DOE	definition	or	provide	a	d efinition.	Why	just	Water

Heaters	and	not	HVAC,	pool	pumps,	or	thermostats?

Page	12:	Point	4,	Weighted	Avera ge	Life	for	Portfolio	(Years)

 Here,	the	instructions	correctly use	the	word	“weighted”	rather than	“weighed.”	However,

we	still	recommend	use	of	the	term “Weighted	Average	Measure	Li fe”	rather	than

“Weighted	Average	Life.”	This	sh ould	be	standardized	across	the instructions	and	the	form

itself.