ORNL/
OAK RIDGE NATIONAL LABORATORY IWARTIN IWARIETTA
Electric Utility Demand Side Programs and Integrated Resource Planning: Visits to Ten Utilities
Eric Hirst
OPERATED BY MARTIN MARiffiA ENERGY SYSTEMS, INC. FOR THE UNITED STATES DEPARTMENT DF ENERGY
CONTENTS
SUMMARY •••••
v
• v; ;
LIST OF ACRONYMS 1.
INTRODUCTION BACKGROUND • • • CONTENT OF REPORT
1 1 6
2.
KEY OBSERVATIONS
9
3.
R&D OPPORTUNITIES
21
ACKNOWLEDGMENTS
29
REFERENCES
31
• •
APPENDICES A. NOTES ON INDIVIDUAL UTILITIES ••• B. NOTES ON INTEGRATED PLANNING MODELS
;;;
33 47
SUMMARY During Fall 1985, I visited ten investor-owned electric utilities in California, Nevada, Washington, Wisconsin, New Jersey, New York, Connecticut, Massachusetts, and Maine. The purpose of these visits was to discuss electric utility demand-side planning and programs, and to learn more about utility efforts to establish integrated resource planning processes. I also attended a course on the Load Management Strategy Testing Model, developed for the Electric Power Research Institute. Finally, I reviewed three other integrated resource planning models. This report presents my impressions of current electric utility activities in conservation and load management program planning, analysis, and evaluation; and in integrated demand/supply planning. The observations and suggested research topics presented here are based on my impressions and observations. Other researchers, visits with different people in the same utilities, or visits with other utilities might yield different findings and conclusions. In brief, these utilities are vigorously and intelligently pursuing demand-side options. They have a variety of conservation and load management programs underway, which range from traditional information-only programs to provision of substantial financial incentives for installation of energy-efficient equipment. The data collection and analytical activities surrounding these programs are also quite impressive. Many interesting load research, customer survey, resource assessment, and program evaluation activities are underway within these utilities. Finally, several utilities have begun to develop data, models, and associated processes to help compare demand and supply resources on a common basis.
v
LIST OF ACRONYMS ~~
conservation and load management
CMP
Central Maine Power Company
CPAM
Conservation Policy Analysis Model
DSM
demand-side management
EPRI
Electric Power Research Institute
GPU
General Public Utilities
IRP
integrated resource planning
LMSTM
Load Management Strategy Testing Model
NEES
New England Electric System
NiMo
Niagara Mohawk Power Corporation
NU
Northeast Utilities
PGandE
Pacific Gas and Electric Company
PUC
Public Utilities Commission
Puget
Puget Sound Power & Light Company
SP
Sierra Pacific Power Company
sa
Southern California Edison Company
T&D
transmission and distribution
USAM
Utility System Analysis Model
WP&L
Wisconsin Power & Light Company
vii
1.
INTRODUCTION
BACKGROUND During the past 15 years, especially in recent years, many electric utilities began a variety of energy conservation, load management, and innovative rate design programs.
These demand side management (DSM)
programs were implemented in response to a variety of forces: Legislation, regulation, and persuasion from federal and state governments; Customer anger over r1s1ng electricity prices and utility requests for rate increases; Increasing costs (economic, financial, and temporal) of new central-station power plants; Changes in the utilities' operating environment, particularly the relationship between marginal and average costs of power production; Changes in the utilities' financial condition, which led many to reduce and defer capital projects (even if these supply expenditures were economically attractive). In addition, some utilities began to perceive a broader role for their companies -a role in which they provide energy services rather than just electricity.
This more expansive view of the utilities' market
necessarily involved much closer consideration of their customers, how and when they use electricity, for what purposes, and their alternatives to additional electricity consumption.
Thus, utilities began to manage
- rather than just meet - future electricity load growth.
This increasing
attention to customers and their energy-service needs represents a major philosophical change in utility perspective, management, and operation. Historically, utilities viewed their role in terms of building power supply facilities (generating stations, transmission lines, distribution
2
systems) to meet projected electricity demands.
This worked extremely
well for several decades during which demand grew steadily and smoothly, and economies of scale permitted the real price of electricity to decline as new, large, and more efficient power plants were brought on line. During the past decade, all this changed.
High inflation rates,
dramatic increases in construction and fuel costs, long delays in constructio n of new plants, changes in regulation, and few technical advances in power plant design led to rapid increases in electricity prices.
These changes, in turn, led to much slower growth in electri-
city demand.
Between 1950 and 1973, electricity demand grew at 8% per
year, while the real price of electricity to residential customers dropped at 3.5% per year.
During the following 11 years, demand grew at
only 2.6% per year and real electricity prices increased by 2.6% per year.
The turmoil of the 1970s led many utilities to re-examine their
roles, the result of which was often a new emphasis on DSM programs. Inclusion of DSM programs in a utility's resource portfolio offers many potential benefits, both to ratepayers and stockholder s.
In many
instances, conservation and 1oad management "resources" are 1ess ex pensive to purchase than are traditional electricity supplies.
That is,
the cost per kWh and per kW are less for some DSM programs than for supply-side programs.
Other possible benefits of demand-side programs
include: •
Small size of the resource. Conservation and load management resources can be ''purchased" from customers in small increments. In fact, such resources can only be obtained in small amounts because most customers (except for a very few large com~ merci al and industria 1 firms) consume only very sma 11 fractions of the utility's total load. The small size of conservation
3
resources (relative to a 1000 MW power plant) increases utility flexibility in planning for uncertain load growth in the future. For example, DSM programs can be increased or decreased to meet changing conditions in a particular service area. •
Short lead time. The time required to obtain resources is much less than the time required regulatory approval, to secure financing, and large baseload power plant. DSM programs can implemented within a few years, compared with more required to build a new power plant.
demand-side to obtain to construct a be designed and the decade or
e Reduced environmental hazards. In general, demand-side resources pose none of the environmental hazards associated with the production of electricity. Existing indoor air quality problems might be exacerbated by measures that reduce infiltration of outside air into a building, but such problems are rarely caused by demand-side programs. •
Positive public relations. While there is often strong opposition to construction of transmission lines -and large power plants, customers are generally supportive of utility efforts to cut customer electricity bills with conservation and load management programs. Such DSM programs may give customers greater control over their energy bills; the contact between utility staff and customers may promote good will between the utility and its customers. Although there are some complaints about one customer class subsidizing the efficiency improvements of another and complaints about utility ''handouts" these are usually much fewer than those associated with a new power plant.
•
Improved relations with regulators. Many state public utility commissions (PUCs) favor demand-side options over supply-side options. In these states, regulators are likely to strongly support utility demand-side programs. Also, the shorter leadtimes and smaller size of DSM programs reduce problems associated with regulatory lag and disallowance of past capital expenses.
•
Decreased dependence on oil and gas. Although concerns about limited oil and gas availability and rising prices have abated in recent years, these are still nonrenewable resources. When gas and oil supplies eventually tighten and prices increase, DSM programs that reduce the need to generate with these fuels will be particularly attractive.
t
Reduced uncertainty about future load growth. Recent experience shows the tremendous difficulty in accurately forecasting future electricity load growth. This argues for substantial flexibility in planning to meet and manage future growth. It also argues for utility DSM programs that reduce this uncertainty. For example, a program to upgrade efficiency of new residential
4
and commercial buildings reduces the electric demand uncertain ty associate d with economic growth. The energy and peak load reductions due to such a program vary directly with new building construct ion activity (and therefore with economic growth). Although there are substanti al benefits associate d with implementation of C/LM programs, there are also several risks.
Some of the
major uncertain ties associate d with such programs include: e Availabi lity and performance of efficient technolog ies. Although some energy-e fficient systems are well-known and reliable, many are new and relatively untested. Insuffici ent field performance data are available to document actual kWh and kW reductions for rnany such systems. Also, availabil ity of trained personnel to install and service new systems may be a problem, especiall y during the early phases of a utility DSM program. •
Effective ness and cost of utility programs. Because utility involvement on the customer side of the meter is a recent phenomenon, much remains to be learned about how to design and implement DSM programs. For example, the relative costs and importance of different marketing strategie s, different levels and types of financial incentive s (e.g., rebates vs loans), and quality control features are generally unknown. The extent to which customers respond primarily to fi nanci a1 incentive s rather than the convenience of a program offering is also not well understood. The cost of administering utility DSM programs may be high enough to affect the economics of some programs.
•
Cost-effe ctiveness of utility programs. The role of the nolosers test (or equivalen t cost-bene fit calculatio ns that assess the effects of programs from various perspecti ves) is not yet well-defi ned. In particula r, more effort is needed to ensure that the economics and regulation of demand and supply programs are handled in a consisten t fashion. Also, attention should be paid to the intangibl e benefits of C/LM programs (e.g., improved comfort and greater house value after installation of retrofit measures).
•
Customer behavior. Closely related to the preceding points is the concern over customer purchase and operation s behavior, both in the absence of the utility program and with the program. To what extent are consumer decisions affected by the utility program? How enduring are these changes? Will customers disable equipment and controls they find inconvenient? Will they modify behavior in ways that offset the efficienc y gains due to the utility program (e.g., raise indoor temperatures during winter after utility-fi nanced retrofit)? How
5
will customers react to load management efforts that affect living patterns? Gaining the benefits of DSM programs, while avoiding the pitfalls, poses difficult tasks for utilities.
Playing a role on both sides of
the customer's electric meter offers many new opportunities to electric utilities (Fig. 1).
Dn the other hand, implementation of DSM programs
requires utilities to develop new- perhaps, unfamiliar- skills and to undertake programs different from what they have done in the past. Finally, integrating DSM programs into a utility's overall planning process may require new (or improved) analytical tools and procedures, and require utility personnel with different backgrounds to work more closely together.
CONSERVE ENERGY
REDUCE CAPITAL REQUIREMENTS
REDUCE COST MAINTAIN LIFESTYLE
SATISFY DESIRES INCREASE CONFIDENCE IN COMPANY
Fig. 1.
IMPROVE FINANCIAL PERFORMANCE
CUSTOMER NEEDS
UTILITY
INCREASE SYSTEM UTILIZATION
NEEDS
REDUCE CRITICAL FUEL USAGE ENHANCE IMAGE OF
UTILITY COMPANYdNDUSTAY
Schematic showing potentia 1 benefits, to both uti 1 it i es and their customers, of demand-side management programs.! Such programs offer new and important opportunities on the customer side of the meter for many electric utilities.
6
CONTENT OF REPORT In September and October 1985, I visited four investor-owned electric utilities on the West Coast, five in the Northeast, and one in the Midwest (Table 1).
This report summarizes the major demand-side and
integrated resource planning activities underway within these utilities. The observation s and suggestions offered here are personal, rather than scientific and representat ive.
These utilities are not a statistical
sample of investor-owned electric utilities; the group was self-selecte d on the basis of their interest in demand-side issues and active conservation and load management programs.
Also, I met with only a few people
in each utility, almost always from departments concerned primarily with demand-side activities.
Finally, this report is based primarily on per-
sonal impressions, which may be subject to alternative interpretat ion.
Table 1.
Key statistics on investor-owned electric utilities visited.
Utility
State
Number of customers employees (thousand)
Peak demand a (MW)
PGandE Southern CA Ed Sierra Pacific Puget Power
CA CA NV WA
3,600 3,300 200 600
27,300 16,300 1,500 2,400
13,200 13,500 700 3,900
WI P&L
WI
300
2,300
1,400
Ctrl Maine New England El Northeast Ut Niagara Mohawk GPU
ME MA CT NY
400 1' 100 1,100 1,400 1, 700
2,100 5,100 9,600 10,200 13.200
1,300 3,200 4,400 5,600 6. 700
NJ
s s w w s w s s w s
Electric revenues (mill ion-$) 3,900 4,500 300 600 400 500 1,200 1,800 2,000 2,700
aThe letters indicate whether the peak demand occurs in Summer or Winter.
7 The next two sections of this report present observations on current utility DSM activities and suggestions for future R&D activities.
The
two Appendices deal briefly with each of the ten utilities visited and the integrated resource planning models examined.
9
2. Utilities are currently
KEY OBSERVATIONS planning~
major new generating facilities.
Some utilities go further and state that they will not begin new capital-intensive coal or nuclear plants until and unless all alternatives have been exhausted.
Practically, this means that many utilities
are interested in exploiting various energy alternatives to delay as long as possible decisions on construction of new central-station power plants (perhaps until the late 1990s or early 2000s).
The facility
siting process in many states supports (or mandates) such an approach that views large power plants as the option of last resort. Many supply and demand options are being pursued by these utilities. These include purchase of power from others (small power producers with low-head hydro, cogeneration, trash burning, as well as other utilities with excess capacity).
In addition, utilities are involved in a broad
array of conservation and load management (C/LM) programs.
These alter-
natives are beginning to represent important sources of new "supply" for some utilities.
Even among these utilities, however, C/LM programs are
likely to account for only a minority (usually less than V4) of future capacity additions (Fig. 2 and Table 2).
Thus, existing C/LM programs
cannot do the job alone; expanded programs and/or other resources are essential. Increasingly, utilities recognize the important contributions that C/LM programs can make to achievement of corporate objectives.
That is,
C/LM programs are no longer viewed solely as regulatory requirements and/or public relations functions.
Utilities are learning that these
programs can help them manage (rather than just meet) future load
10 growth, balance their electric supply system, conserve capital resources (and thereby improve their financial situation), increase customer satisfaction with the utility's services, and compete with energyrelated alternative s that their customers face.
Therefore, some utili-
ties are allocating substantial resources to these programs (Tables 3 and 4).
For example, the eight private California utilities increased
their expenditures on conservation programs from $20 million in 1976 to $91 million in 1980 and $390 million in 1984. ORNL·DWG 85C-18335
GEO 6%
HYDRO 4%
IMPORTS 8%
Fig. 2.
Planned electric resource additions by Pacific Gas and Electric Company between 1985 and 2004.2 PGandE C/LM programs account for almost 3000 MW of the nearly 17,000 MW planned. State appliance efficiency and new constructio n standards, other state and federal conservation programs, and increased electricity prices will induce additional electricity and peak load reductions beyond those due to PGandE programs alone.
11
Table 2.
The effect of conservation on the long-range load forecast prepared by Central Maine Power. CMP anticipates a 25% decrease in their (winter) peak demand and a 12% decrease in overall sales because of conservation. The residential sector accounts for about two-thirds of the estimated electricity savings. These estimates include electricity savings due to CMP programs, other programs, and to customer response to rising electricity prices.
Electricity sales (GWh) Residential Commercial Industrial Other Total Peak load (MW)
Forecast
1994 Conservationa
Forecast
2004 Conservationa
2810 2000 5400 130
1110 100 170 30
3340 2420 7650 150
1580 140 270 60
10,340
1410
13,560
2050
1750
590
2300
790
aThese estimates of conservation savings are included in the CMP forecast. Conservation savings include those due to CMP programs as well as other factors. Source: Ref. 3. Important questions remain about the cost of conserved energy and the speed with which it can be purchased.
However, the existence of a
conservation resource and the legitimacy of the utility's role in \
"mining" that resource are fully recognized by these utilities. Utilities (and increasingly, their state regulators) recognize that the information base supporting C/LM programs is weak (Fig. 3).
There
is substantial need for more and better data concerning the effects of these programs on:
customer participation in the programs, customer
adoption of recommended measures, changes in end-use load shapes, and the costs and cost-effectiveness of the programs (Table 5).
12 Table 3.
Estimated 1984 electricity savings and peak load reductions due to C/LM programs operated by Southern California Edison. SCE spent more than $90 million and cut consumption by 4.4 billion kWh and 510 MW. SCE expects the demand reductions due to its program to more than double between 1984 and 1994. Program cost (M$)
Program C/l/A conservationa Residential conservation Solar C/l/A load management Residential load management Cogen/small power production Advertising, public awareness Management
Program benefits (GWh/yr) (MW)
26 37
1.4 0.2
2 3
40 80
15
Total
320 70
2 2 5
2.8
92
4.4
510
ac;r;A refers to commercial, industrial, agricultural. Source:
Table 4.
Ref. 4.
General Public Utilities' proposed Conservation and Load Management budgets for 1986, 1987, and 1988. GPU plans to spend almost $130 million during this three-year period, with about half allocated to residential sector programs.
Program
1986
Pro2ram costs (million-$) 3-year total 1988 1987
Master Plan Residential Commercial
18 7
20 9
22 10
60 26
Mandated programs
17
12
13
42
Totals
42
41
45
128
Source:
Ref. 5
13 OANL·WS 29oi92
srFiAr: --
f:Gtc P(
---
--
----
-- ---
P~=to
ANNtN
----p,
G,qAa.•VJS
I..ANs
Fig. 3.
G
---
--
--
---
Most utility DSM programs are supported by a very narrow information base.6 A complicated structure of utility models, forecasts, program plans, program implementation, and strategic plans are based on insufficient data and analysis. Small experiments and pilot programs, supported by careful evaluations, could provide much of the information needed to better plan and manage DSM programs.
Although our knowledge of residential programs is far from perfect, data are particularly needed for the commercial sector.
The commercial
sector is often the most important because it is growing more rapidly than the residential and industrial sectors, it is very electricity intensive, and commercial lighting and air conditioning often contribute substantially to utility system peaks (Figs. 4 and 5). In addition, C/LM programs aimed at commercial buildings are likely to save more electricity than programs focused on the residential sector because commercial buildings .use more electricity than residential buildings.
Also, commercial customers may be more willing to help pay
14 for energy savings.
As a consequence, commercial C/LM programs may be
more cost-effect ive than residential programs. The era of confrontatio n between utilities and their state Public Utility Commissions (PUGs) is ending.
The absence of large price
increases and the realization that lengthy contentious PUC hearings do not solve problems are leading to more cooperation between regulators and utilities.
Although PUC and utility staff often disagree about the
pace of utility C/LM programs, there is now substantial agreement over the role of these programs.
The two staffs frequently work together to
develop programs before formal hearings are conducted.
Table 5.
Conservation research projects underway at Niagara Mohawk in 1985. These projects are intended to greatly increase NiMo understanding of how customers currently use electricity and how existing patterns of use could be modified through utility C/ LM programs.
End-use load studies Eight end-use metering projects (4 residential , 2 small commercial, 1 large commercial, 1 T&D system) Estimating marginal costs and revenues Uniform cost effectivene ss methodology Enhanced version of Load Management Strategy Testing Model Hourly electric load shape model Market penetration studies 4 residential financial incentive pilot programs 3 commercial sector incentive and/or audit pilot programs 1 farm sector pilot program 1 public sector pilot program Conservation marketing data base 10 projects to collect and organize data on all customer classes Expanded information programs 3 projects on media effectivene ss, customer attitudes, and responses to customer telephone requests Source:
Ref. 7.
15 OANL·DWO
t15C·I~JH
6000
~
:=;
OTHER
0
z <
:=; w
0
INDUSTRIAL
4000
>
<
0
COMMERCIAL
"'< w
. "' a.
"'
2000
~
a:
w :=; :=;
RESIDENTIAL
::;)
"'
0
6
12
18
24
HOUR
Fig. 4.
Northeast Utilities' forecast of 1994 summer peak demand.8 Commercial buildings are estimated to account for 40% of the total peak, primarily because of air conditioning and lighting loads.
900 800 700 500
~ "' "'"
500
~
"
400 ,00 200 100 0 1984
Fig. 5.
1989
1894
1&99
200-4
2009
An analysis done for Northeast Utilities estimated the total summer peak demand reduction due to NU's current programs.9 Savings in the commercial sector (primarily in lighting) account for almost two-thirds of the peak load reduction.
16
On the other hand, utili ties have few conta cts with their state energy offic es and littl e conta ct with the U.S. Departmen t of Energy. The two feder ally mandated programs, Residential Conservat ion Service and Commercial and Apartment Conservation Serv ice, are rarel y discussed by utili ty staff .
That is, these utili ties have moved far beyond information-only activ ities in their C/LM programs. Util ities recognize the importance of matching their C/LM programs to the needs of their parti cula r elect ric power supply syste m. Programs that reduce consumption at times of high power costs (not always during peak periods) are parti cula rly attra ctive to utili ties and their custo mers. This requi res development of data on the effec ts of demand-side programs on end-use (and sytem) load shapes. Because of the need to integ rate C/LM programs with capa city dispa tchin g and supply expansion programs, utili ties are developing Integ rated Resource Plans (Fig. 6). The typic al IRP seeks to asses s various supply and demand options and to develop the mix that "optimizes'' the system over both the short - and long-term. Optimizatio n could involve minimization of elec trici ty price s, minimization of utili ty revenue requirements, or minimization of energy servi ce costs to custo mers (Fig. 7). In some utili ties, integ rated models (such as IPRI 's Load Management Strat egy Testing Model) are used to develop IRPs. In other utili ties, their individual load forec astin g, conservation planning, dispa tchin g, capa city expansion, and finan cial planning models are used. The particul ar model(s) used is less important than the planning proce ss. The process involves staff s from various utili ty departments (Table 6), who
17
IN mAL ANALYSIS
ENERGY RESOURCES NEW IDEAS
CUSTOMER ENERGY USE NEW IDEAS
"'
COSTS AND BENEFITS
• l'l, .. ,,~~ 1n<1 o...,oo,....,t • 91M- Col!_ Fouo< ~ .... 11
•
• Ntw PuMong Pl1nts 'ln!e
• E•Ptl""''"'-'- G.ol"-'"''' S
• New or lmp
•
""PROG~ IDENTIFIED FOR
FURTMER STUDY
o Gl ..... lh"Q Pt1n1 Ad
.•
• PurciiiH Gl POWI< o Retntment of P11nts
~
• Economoc Ach••ty ~IIIH:>n
•
T
DETAILED EVALUATION
ElUmNG
CUSTOMER USE PATTERNS
•
• Oem09raph1C SuNe~• • HoSIO"C Use PIOhiU o HOmU_ 8u.,nU!. lnduSiry o EMIQY UlohUI
lndlvldu•l Progr•ma
ComblnMfon of Programs 'fre~~~';:J:,}ent Slral~y
BASIC LOAD FORECAST •
• "'"
~
PREVIOUS RESOURCE PlAN
Ft>
•
"'"
•
"'" PROGRAMS
THAT MEET AU REQUIREMENTS
Ll
ENERGY INFO PROJEC1 • Type and Ell•coency ol Eouopmenl • Mono lor Customer Loads • Oelelm•neload Shapes
o Ene•gy Resource C~ts
1Ana1ysos ollOid os Tome)
• lo..:J Prololn
• Ely CuSiom~r Type
Supply Side
I "'" PlLOTPIIOOAAMS
~
/1 f
J G.otnt
Monitor lnd Evtluate Rf/,,b,lllr•nd fconom~
I
MODIFY POOOIWI
YES
NO
T
I~
J
Resource Development
Fig. 6.
~
• fly Eouopment Type
DemandS/de
-
SYSTEM PlANNING Supply and Demand Pilot
-----:zoWAR" _____ RESOURCES PlAN 2 YEAR ACTION PlAN
Prog....,.
I• f C<><>l Stat•~l
~~-
Monitor and Evaluate Cru118en~t./. l'~tlotmann
anO" Cus1om•1 AccMr.nce
•
"'"II
YES
I
_l TNO
~'PROGRAM MOOIFY
T cA"':'"cEL
I
Customer Action Programs
The electricit{ resource planning process at Sierra Pacific Power Company. 0 Projects that survive the initial screening (top center of diagram) are then subjected to more intense scrutiny. Pi 1ot programs and 1oad research experiments (right hand side of diagram) are used to provide much of the essential data about DSM programs.
r 18 ORNL·DWQ 86C·16204
.,.
~
c::'
0
:;:;
TOTAL COST
LEAST COST RANGE
SUPPLYSIDE COST ELECTRICITY PRODUCTION (thousand MW)
Fig. 7.
A 1east-cost energy plan is one poss i b1e output from a utility's integrated resource planning process,ll Such a plan would identify the lowest cost mix of generation and demand-side resources for a given level of energy services.
Table 6.
Departments within Puget Sound Power & Light Company with computer models used for electric system planning
Corporate Planning Load, energy, revenue forecasts
T&D Engineering T&D construction
Power Supply Planning Production costing
Financial Planning Financial, investment analysis
Generation Plant Engineering New supply resources
Rate Planning Rate design, cost of service Load and consumer research
19
develop alternative portfolios of supply and demand options, test combinations of these portfolios under various assumptions concerning economic growth, fuel prices, interest rates, etc., and then develop preferred strategies for utility management and the PUC.
The major
limitation with the present analytical tools and planning processes concerns demand-side data, as noted above. The state-of-the-art among these utilities in energy and load forecasting; C/LM program planning, implementation, and evaluation; load research; and integrated resource planning is excellent. overall state-of-the-practice lags far behind.
However, the
In other words, indivi-
dual utilities emphasize particular areas to pursue vigorously and place less emphasis on other areas (probably because of limited staff and contract funds, and short-term activities such as rate cases). As examples, PGandE and NU have developed impressive IRP processes; Puget Power and GPU operate very effective residential and commercial sector conservation programs; WP&L and CMP have made major efforts to work closely and cooperatively with their state regulators; NiMo, NEES and SP conduct well-designed pilot programs that will provide valuable information on customer electricity use patterns and their determinants; and SCE has carefully evaluated several of their C/LM programs.
Each of
these ten utilities, exemplar in one or more areas, lags behind in others. The methods and results of these state-of-the-art activities are rarely published in the open literature (energy and other professional journals).
Much of the material is available only in filings for PUC
hearings; some utilities prepare reports that are available upon request
..
------~----------· · - - - - - - - - -
T
20
and some present papers at conferences.
Thus, most of this valuable
information is accessible only through the "gray" literature and requires considerable persistence to identify and obtain. Finally, although public perception suggests that there are no more energy prob 1ems to so 1ve, discussions with peop 1e at these utilities show that many important issues are being examined, i;sues that are likely to change substantially the nature of the electric utility business during the next several years.
21
3.
R&D OPPORTUNITIES
The range and depth of important activities underway within these ten utilities suggest a number of fruitful areas for future research. Such research should build upon past and ongoing work in these (and other) utilities to provide more and better data, analytical tools, and planning processes that encourage thoughtful use of these resources. 1. Integrate C/LM program evaluations with forecasting models.
There
are substantial opportunities to use evaluation data and results to strengthen energy and load forecasting models (Fig. 8).
Evaluation data
generally include detailed information from surveys, utility energy audits, monthly electricity billing data, and sometimes load data on individual customers. EXOGENOUS
DETAILED ENERGY
VARIABLES AND RELATIONSHIPS
DEMAND FORECASTS
SIMULATION MODEL Addt\IOns to the Stock or
Employment Ff I Employee
f-----.
End·UH
Cap!lall• e end·use
1-
eQurpmenl)
Space Heatmg
Coormg
r'
LrghHng Other
Fuel Type EleCIIIC
f-
fx•sling Capotal Srock
Oeprec•atoon ol Ex•srmg Srock
I-> Cap,tar StO<:k Ullhzalton
Fuel P"ces. Emptoymenl
1-
Building Type Olfoce Reslaurants Retaol Food Stores
Warel'louse
l.
Eftrc•ency Characteusllcs or New & ExtSI1ng Capotal
Slack
I--
Elem/Sec Schools Colleges/Trade Schools Heallh Care Hotel-Motel
Moscellaneous
~ ......, ..... Fig. 8.
_
Schematic diagram of the disaggregated commercial energB endMuch use forecasting model developed by Northeast Utilities. of the detailed input required to operate this model were obtained from analysis and evaluation of NU's commercial energy audit program.
\
$
22 These data should be used to incorpo rate addition al behavioral charact eristics in forecast ing models.
For example, most forecast ing
models include only fuel prices and incomes as determinants of residential energy- related behavio rs.
Evaluation data might permit the expli-
cit incorpo ration of nonenergy appliance features , nonfinancial conserv ation program effects (such as credibi lity of information sources , convenience of program particip ation, and consumer protecti on feature s), and other factors that substan tially influenc e energy- efficien cy investments and operatio ns.
Another model enhancement might include specifi-
cation of the relation ship between energy- efficien cy of equipment and subsequent utilizat ion rates. Such enhanced forecast ing models would be capable of endogenously estimati ng the likely effects of ongoing and future utility C/LM programs; current ly, such estimate s are often made offline by C/LM program staff and forecas ters. Thus, merging talents and tools of the evaluato rs and forecas ters could provide two major benefits - improved forecast ing tools and better ways to use evaluati on data (by definiti on, retrospe ctive) to estimate future effects of programs. 2. Develop models to predict particip ation in utility C/LM programs. Past evaluati ons of utility C/LM programs focused prirnari ly on program processes (was the program implemented as its planners intended) and energy savings.
Additional efforts are needed to analyze customer deci-
sions to particip ate in such programs (Table 7).
These analyses should
then form the basis of forecast ing models that can be used (either independently or within energy and load forecast ing models) to estimate likely future particip ation in the utility' s programs.
Information from
I
I
23
Table 7.
Results of statistical model to predict participation in SCE's commercial hardware rebate program. Customers who asked for an energy audit, had large buildings, and had high demand charges were more likely than other customers to participate in the post-audit rebate program.
Explanatory factor
Effect on request for rebates
Customer requested energy audita Customer responded to mass mailinga Customer reported electricity savings greater than 25% Floor area of building Demand greater than 20 kW
+ + + +
aThe default is an energy audit conducted at SCE's initiative, without prior request from customer. Source:
Ref. 12.
evaluations on marketing efforts, program characteristics, customer characteristics (both participants and nonparticipants), and the external environment (fuel prices, incomes, public concern with energy issues, competition from the gas utility, etc.) can be used to estimate models of program participation. 3. Review IRP tools and processes.
A variety of integrated resource
planning models are currently being used within these utilities.
A
review of the available models would be helpful to other utilities contemplating the purchase of such a model.
This ·review should include
their data requirements, ability to handle different kinds of situations (rate designs, conservation programs, direct load control, pumped storage, purchased power), computer run time, complexity, and costs of preparing inputs and of managing model outputs.
In addition, the review
should consider the relationship between model complexity and detail on
24
one hand and data availabil ity on the other.
It may turn out that use
of complicated and expensive simulation models is often inapprop riate, given the limited information available on costs and performance of C/LM programs.
Alternati vely, the costs and time required to operate the
more complete models may be justified by the increased accuracy and credibili ty of the results they provide. This review should also include a comparison of IRP models (Fig. 9) and the tradition al set of Individual utility planning models (financia l planning, dispatchi ng, capacity expansion, load forecastin g, conservat ion planning; Fig. 10).
Under what circumstances Is a new model preferred
to continued use of the utility's existing models?
DEMAND
'
I
What simplific ations
SUPPLY
"I'
... ./
RATES
Fig. 9.
,,/ .
FINANCIAL
The Load Management Strategy Testing Model includes four major submodels that deal with electrici ty demand, supply, finances, and rates,13 In most utilities these functions and their analyses are conducted in different departments (see Fig. 10 and Table 6 for examples).
25
and approximations are required with IRP models?
How easily can data
inputs and outputs be transferred among the utility's existing models? Finally, the review should examine the planning process (Figs. 6 and 10) -as opposed to the planning model(s) -to understand how these tools can best be used to address issues of concern to utilities.
How
are demand and supply resources identified, included or excluded in subsequent analysis?
How are these individual resources combined into use-
ful ''portfolios" (Table B)?
What are the criteria used to assess the
relative attractiveness of these portfolios (financial health of the utility, cost per kWh, utility revenue requirements, environmental considerations, capital costs, etc.)?
How are results packaged and pre-
sented to utility management and to state regulators?
OFINL·DWG 85C·18336
--
DEMAND SCREENING (STEP 2a)
t-
I
SCENARIO HRANKINGr. DEVELOPMENl (STEP 3) (STEP 4)
LOAD FORECAST' (STEP 1)
...._
SUPPLY SCREENING (STEP 2b)
--
ECONOMIC & FINANCIAL EVALUATION (STEP 5)
--
UNCERTAINTY ANALYISIS (STEP 6)
-
Fig. 10. Schematic diagram of the integrated demand/supply planning process at Northeast Utilities.14 Individual demand and supply resources are screened separately; only those that survive the initial screening are included in later steps. The major themes used in NU's scenarios are shown in Table 8. Various economic factors are examined under a variety of assumptions (sensitivity analysis) for each scenario.
26
Table 8.
Major themes (scenarios) used in Northeast Utilities' 1985 Integrated Demand/Supply Plan Add only small generating units (<200 MW) Emphasize C/LM programs Repower existing oil-fired power plants Defer baseload additions to the year 2000 Extend life of existing power plants Minimize oil dependence Smooth construction expenditures over time
Source:
Ref. 14.
4. Assess alternative regulatory treatments of C/LM programs.
What
changes in state PUC regulations might be needed to ensure a "level playing field" between demand-side and supply-side resources?
Under
what circumstances might utility investments in demand-side programs be included in rate base rather than expensed (Fig. 11)? losers test bias decisions against C/LM programs?
Does the no-
What is the demand-
side analogue of allowing construction work in progress (CWIP) in current rates?
To what extent and how should PUGs encourage their
utilities to develop and implement least-cost energy plans?
How can
PUGs review the progress of their utilities in implementing C/LM programs to ensure that these programs are operated at appropriate levels and that they represent useful expenditures of ratepayer money? 5. · Review status of C/LM programs at other utilities.
The present
review focused on a few utilities in the northeast, upper midwest, and west coast that are clearly leaders in designing and implementing C/LM programs.
Visiting utilities in the southeast, southwest, and midwest
would provide a much broader view of utility C/LM activities throughout the U.S.
Inclusion of utilities from other parts of the country might
27
permit one to draw additional conclusions concerning their involvement with C/LM programs as a function of PUC regulation, reserve margins, and generating fuel mix.
It would also be useful to visit PUC staffs in
several states to obtain information on their views of utility involvement on the customer-side of the meter. 6. Identify ways to better disseminate results of utility demand-side activities.
Because utilities are not research organizations, they
generally do not emphasize preparation of research reports and papers for professional journals.
However, much of the work underway within
utilities is of very high quality and, more important, is of direct relevance to other utilities (Table 9).
Currently, accessing this gray
literature is difficult and time consuming.
The annotated bibliography
on conservation published by the National Association of Regulatory Utility Commissioners (NARUC) can help identify relevant publication.l7 The three-volume series on Demand-Side Management, prepared for EPRI and the Edison Electric Institute (EEl), is another valuable resource.l,l8,1 9 The Energy Services Exchange program operated by the American Public Power Association includes personalized interactions among staffs in public power utilities. Perhaps EPRI, NARUC, EEl, and/or the Department of Energy can offer information exchange services to ensure that in-house reports and PUC filings are cataloged and made available to others.
Cooperative pro-
jects between these organizations and individual utilities might also be a useful way to generate and disseminate important analytical methods and results.
28
1.000
800
BENEFIT OF SUBSIDY TO AVERAGE OLDER RESIDENCE ($/houH)
800
• ..
BASE CASE {SUBSIDY COSTS
t(_
400
J
SUBSIDY COSTS AFIE EXPENSED
200
0
ARE CAPITALIZED)
1.000
2.000
3.000
J'
: 4,000
5.000
200
NONPARTICIPANT 150 PENALTY FOR AN 100 INEFFICIENT OLDER 50 RESIDENCE ($/houH) 0 5.000 1.5
BENEFIT OF SUBSIDY IN REDUCED TOTAL SYSTEM COST
1.0
0.5
(billionS) 0
Fig. 11. The effect of expensing utility conservation pro~rams rather than putting them in rate base (capitaliza tion). 5 These simulations were developed for conservation programs operated by the Bonneville Power Administration in the Pacific Northwest, using the Conservation Policy Analys~s Model. The top box shows program impacts on participant s, the middle box on nonparticipants, and the bottom box on the total system (ratepayers in general). Expensing program costs is less attractive from all three perspective s. This is so because ratepayers pay for conservation investments sooner (immediately) with expensing than with rate basing. These results may not apply to investorowned utilities, for which return to stockholder s is an important considerati on.
29
Table 9. Estimated load reductions due to Southern California Edison's Commercial/Industrial Air Conditioner Cycling program. These estimates are based on a statistical analysis of 15-minute load data, collected on days when cycling occurred and on comparable noncycling days. SCE is a leader in sophisticated analysis of actual electricity use data (both monthly kWh consumption and detailed load data). These results are from an in-house report. Results shown in Table 7, also from SCE, are from a widely available energy journal. " Average
Da~ t~~e
Peak
Moderate zone Demand reduction (kW/ton) Outdoor temperature (°F)
0.33 92
0.37 106
Hot zone Demand reduction (kW/ton) Outdoor temperature (°F)
0.37 92
0.45 105
Source:
Ref. 16.
ACKNOWLEDGMENTS Many people at these ten utilities generously devoted time to talk with me about their activities. I am particularly grateful to the following people for the time and effort they made to plan and conduct my visits: Stel Andrew (PGandE), Doug Whyte and Mike Hall (SCE), Ralph Caldwell (SP), Gary Swofford and Jerry Lehenbauer (Puget), Paul Koeppe and Bob Terrell (WP&L), Lynn Goldfarb and Hari ph Smith ( CMP), Lydia Pastuszek (NEES), John Cagnetta and Dick Brown (NU), John Hughes and Chris Turner (NiMo), and Jim McConnell and George Reeves (GPU). I appreciate the helpful comments on draft portions of an early version of this report from Stel Andrew, Ralph Caldwell, ·Gary Swofford, Hariph Smith, Phil Hastings, Doug Whyte, Lydia Pastuszek, Dick Brown, John Hughes, and George Reeves. I thank Stephen Barrager, Robert Braid, Alvin Kaufman, Mark Kumm, Mark Levine, Amory Lovins, John Reed, Jack Roll, and Mark Thornsjo for their comments and suggestions on the draft report. Finally, I thank Marjie Hubbard for perparing the draft and final reports.
31 REFERENCES 1. Battelle-Columbus Division and Synergic Resources Corp., 1984, Demand-Side Management, Vol. 1: Overview of Key Issues, prepared for the Electric Power Research Institute and Edision Electric Institute, EPRI EA/EM-3597, August. 2. Pacific Gas and Electric Company, 1985, Long-Term Planning Results, 1985-2004, July. 3. Central Maine Power Company, 1985, Long-Range Load Forecast, June. 4. Southern California Edison, 1985, 1984 Conservation/Load Management Results, March. 5. General Public Utilities Corporation, 1985, Conservation and Load Management Plan, 1986-1988, July. 6. E. Hirst, 1984, "Measuring Effects of Utility Conservation Programs: Inputs to Utility Decisionmaking," proceedings of the Conference on Utility Conservation Programs: Planning, Analysis, and Implementation, edited by T. Davis, EPRI EA-3530, May. 7. Corporate Development Department, 1985, 1985 Conservation Activities Plan, Niagara Mohawk Power Corporation. 8. Northeast Utilities, 1985, 1985 Forecast of Loads and Resources for 1985-1994, March. 9. Applied Energy Services, Inc., 1985, A Least-Cost Analysis of Northeast Utilities' Energy Markets, prepared for Northeast Utilities, draft, September. 10. Resource Planning Dept., 1985, 1984-2004 Electric Resource Plan, Sierra Pacific Power Company, April. 11. E. Hirst et al., 1986, Energy Efficiency in Buildings: Progress and Promise, American Council for an Energy-Efficient Economy. 12. K. Train, P. Ignelzi, and M. Kumm, 1985, "Evaluation of a Conservation Program for Commercial and Industrial Customers," Energy _!Q( 10), October. 13. Decision Focus, Inc., 1984, User's Guide to the Load Management Strategy Testing Model, prepared for the Electric Power Research Institute, EPRI EA-3653-CCM, August. 14. Corporate Planning Department, 1985, The 1985 Report on NU's Integrated Demand/Supply Planning Process, Northeast Utilities, August.
32
15. A. Ford and R. Naill, 1985, Conservation Policy in the Pacific Northwest, prepared by Los Alamos National Laboratory and Applied Energy Services for the Office of Conservation, Bonneville Power Administration, April. 16. System Development Department, 1985, Commercial/Industrial Air Conditioner Cycling Program, Analysis of Load Data for Summer 1984, Southern California Edison, January. 17. National Association of Regulatory Utility Commissioners, 1984, 1984 Report of the Ad Hoc Committee on Energy Conservation, September--.--18. Battelle Columbus~ Division and Synergic Resources Corp., 1984, Demand-Side Management, Volume 2: Evaluation of Alternatives, prepared for the Electric Power Research Institute and Edison Electric Institute, EPRI EA/EM-3597, December. 19. Battelle Columbus Division and Synergic Resources Corp., 1984, Demand-Side Management, Volume 3: Technology Alternatives and Market Implementation Methods, prepared for the Electric Power Research Institute and Edison Electric Institute, EPRI EA/EM-3597, December.
33
APPENDIX A. NOTES ON INDIVIDUAL UTILITIES
Southern California Edison (Los Angeles, CA). SCE is one of the nation's largest private electric utilities. It serves the southern half of California (PGandE serves most of the rest of California). I visited with staff in the Electric System Planning (ESP) Department, headed by Doug Whyte. The Department has about 55 people. Doug and many of his key staff are electrical engineers, having "grown up" in the supply planning part of SCE. ESP is responsible for planning, analysis, and evaluation of almost all SCE supply and demand programs. Groups within ESP are responsible for capacity planning (using PROMOD, a detailed and widely-used model), transmission planning, evaluation of C/LM programs, demand forecasting, market research, and other energy studies. The Conservation and Load Management (C/LM) Department, which reports to a different Vice President, is responsible for detailed program planning and for implementation of demand-side programs. From what I could deduce, the two departments are still learning how best to work with each other - the usual kinds of gaps and omissions that occur between analysts and implementors. The Forecasting and Market Research Group (within ESP) has just begun a $5 million, 3-year project on demand-side planning and modeling. This ambitious project includes development of detailed end-use data (load shapes) and the effects of C/LM activities on these load shapes, development of improved forecasting models that will incorporate these additional end-use details and the effects of SCE C/LM programs. The project will then use these data and models to develop an integrated resource plan that SCE can submit to the California PUC. USAM (Utility System Analysis Model, developed by Lotus Consulting in Palo Alto, CA) will be used as a screening tool to develop a reduced set of DSM options to compare with supply options. The ultimate goal is to give SCE the ability to develop integrated resource plans that combine different demand and supply options to yield a least-cost energy plan. SCE appears to view conservation programs and load management programs differently. Conservation programs are important elements of customer service, build good will among customers, satisfy regulatory requirements, and are important marketing tools to get customers to participate in load management programs. Load management, on the other hand, is viewed as an important electricity resource, especially those options that offer direct (utility dispatchable) control. These distinctions between conservation and load management are diminishing within SCE. These programs are increasingly viewed as energy management options, drawn from a common pool, that can reduce electric system operating costs and hold down customer rates. SCE is serious about resource planning and aggressively pursues many demand-side and alternative resources (wind power, cogeneration, geothermal, biomass, etc). Because of favorable prices set by the
34
California PUC, SCE has signed contracts to purchase large amounts of electricity generated by others. SCE is concerned that these power sources may not be reliable and will often deliver power to their system at times when they don't want the power and at prices higher than avoided costs at those times. The PUC recently suspended utility purchases of power, to provide time to develop improved pricing schemes. No one I met talked about planning any new, large, central-station coal or nuclear plants. Pacific Gas and Electric (San Francisco, CA). PGandE is, in some respects, the nation's largest private utility. It serves almost 4 million customers in northern California. For a variety of reasons including pressure from the state PUC and Energy Commission, delays with their Diablo Canyon nuclar plants, and being in California (where many interesting new ideas originate) - they probably have more experience in planning and implementing demand side programs than any other utility in the country. On the other hand, their enormous size (more than 6000 people work in corporate headquarters) and complexity make it difficult for an outsider (and probably for many staff) to determine how decisions are made and who is responsible for what. My impression of PGandE's analytical staff is that they are topnotch. They are at or near the cutting edge in conduct of consumer surveys, development of energy and load forecasting models, evaluation of C/LM programs, and integrated resource planning. Because of their large size, they can afford to apply all kinds of sophisticated analytical tools. However, I sense considerable overlap among various groups, again because of their large size. For example, a group in the Economics and Forecasting Department operates EPRI's Load Management Strategy Testing Model. The Rate Department is also- independentlythinking of using this model for its strategic analysis. PGandE has three departments that implement demand-side programs: Residential Conservation Services, Energy Services (essentially commercial and industrial programs), and Energy Management. The Economics and Forecasting Department, with more than 100 staff, reports to a different VP and is responsible for forecasting, end-use data collection, and demand-side planning. The Rate Department, reporting to a third VP, is involved with load research, load management programs, rate design, and many of the issues covered in the other departments. Their customer surveys provide good examples of PGandE's sophistication. They recently tested a way to make in situ measurements of appliance efficiencies among samples of their residential customers. This sort of test is far beyond what any other utility is contemplating, and even goes beyond EIA's Residential Energy Consumption Survey. PGandE recently published results of a major survey of their commercial customers; this survey involved development of innovative ways to identify, sample, and question these customers on their energy-related attributes.
35
A major concern at PGandE is competition. They are trying to position themselves more as a market-oriented customer service organization than in the past. In particular, they worry that if they do not provide good service to their large industrial customers, these customers will choose nonPGandE fuels (self-generation, direct purchase of gas from other companies, etc.). Because of their recognition that these large i ndust ria 1 firms represent a substantia 1 portion of their revenues and because these firms have many energy choices, PGandE recently established a program to provide one-on-one contacts with these large firms. That is, PGandE staff are assigned to work closely with these companies on their energy-related problems. PGandE's July 1985 long-term plan demonstrates their commitment to demand-side resources. Of the nearly 17,000 MW of electrical resources they plan to acquire between 1985 and 2004 (of which about 2,000 MW are the Diablo Canyon nuclear plants), fully 17%- 2800 MW- are from PGandE conservation and load management programs. Sierra Pacific Power Company (Reno, NV). SP is a very small utility, less than 1/10 the size of SCE. Their Resource Planning Department, headed by Ralph Caldwell, has about 12 staff. This small group does a great deal of very interesting work. SP's involvement in integrated resource planning stems from a state law and subsequent NV PSG order in 1984. The order requires Nevada utilities to develop least-cost energy plans. SP has no major ongoing C/LM programs. However, they have an impressive array of analytical tools and a strong set of technical experiments underway. Their strategy is to start with careful, detailed planning before implementing system-wide programs. The group uses several EPRI models, including REEPS and COMMEND for residential and commercial sector forecasting, HELM to convert annual electricity use outputs from these models into load shapes, and LMSTM to assist in integrated resource planning. They have 17 pilot programs underway, to help determine the impacts on end-use (and system) load shapes of various C/LM tchnologies. The programs include end-use load meters for 350 customers, at a cost of $3 million. These meters, at both participant and nonparticipant customers, will collect baseline (preprogram) as well as postprogram data for all major electricity end uses. SP plans to leave these meters in place for five years, which should provide terrific data on the long-term effects of C/LM technologies. Five of the pilot programs are residential and 12 are commercial. SP is now initiating a second phase of its pilot programs. This phase involves small marketing tests to see how SP customers respond to different kinds of program offerings. My sense is that SP is devoting much more time and money to determination of engineering data (changes in load-shapes due to conservation measures) than to determination of customer response.
36
As with SCE, implementation of demand-side programs is handled by a different department, reporting to a different VP. There seem to be similar difficulties in communication and coordination between the planners and implementors; such difficulties are understandable given the complexity and newness of conservation programs and the different missions of the two groups. SP has some powerful analytical tools in place. At present, they do not have the necessary data to properly run these models, but the 17 pilot programs will provide much of these data. My sense is that their vigorous analytical and research efforts are due to Caldwell, a capable technical manager with a clear vision of how to develop demand-side planning. It will be interesting to see what C/LM programs SP implements, based on results of their 17 pilot programs. Pu et Sound Power & Li ht Bellevue, WA • util1ty 4000 MW, compared with less than 13,0000 MW for PGandE). Because of their is more concerned with annual electricity (i.e., their focus is on kWh more than on
Puget Power is a medium-sized 1000 MW for SP and about large hydropower base, Puget use than wi.th time of use kW).
I spent most of my time with Gary Swofford and others in his Conservation and Division Services Department, which is responsible for design and implementation of Puget's conservation programs. Puget, along with most utilities in the Pacific Northwest, has run strong and effective conservation programs for several years. Their residential retrofit and commercial/industrial programs have achieved high penetration rates; both programs include substantial rebates (72% of the initial cost) for installation of conservation measures. Puget's active role in conservation investments stems from several factors, including substantial public support for conservation in the region, Puget's interest in offering effective energy services to its customers, Puget's lack of surplus power (they are the only private utility in the region that does not have excess capacity), and the favorable treatment provided by the Washington Utilities and Transportation Commission, which allows a 2% higher rate of return on the equity portion of Puget's conservation investments than on supply investments. The 2% addition was made possible by a recent Washington state law. The vigorous and effective implementation of conservation progams, however, is not yet fully matched by their analytical efforts. Puget has only recently begun to subject their programs to careful evaluation (they still rely primarily on engineering estimates to determine program cost-effectiveness). Similarly, they are working on ways to improve their strategic planning process to integrate their supply expansion plans with their demand-side plans. Gary recently created a Planning and Development Group within his Department, in part to strengthen their conservation planning and evaluation skills.
37
Two other groups in Puget are involved with demand-side planning. The Market Research Group (with about five people, located in the Rates Department) conducts customer surveys (both appliance saturation and· attitude surveys) and evaluates conservation programs. Another,gro~p. consisting of three professionals reporting to a third Vice President, is responsible for Puget's economic and load forecasting activities. Puget currently has a variety of models they use in plann·ing and assessing existing and possible future programs. These include their economic and energy forecasting models (Corporate Planning Department), rate design and cost-of-service models (Rate Department), production costing and capacity expansion models (Power Planning Department), and finance and investment analysis models (Financial Planning Department). It is difficult to test different scenarios or to run sensitivity analyses for individual resource portfolios because these models are in different departments, run on different computers, and have inputs and outputs that must be transferred manually. Both Puget management and staff are interested in improving the process, to better use existing models and in-house analytical talents. Puget recently initiated a high-efficiency water heater rebate program. The purposes of the program are manifold: improve energy efficiency of electric water heating, provide improved customer services, and stem the loss of its customers to natural gas water heating (a consequence of aggressive marketing by the natural gas utility). My sense is that many utilities see conservation programs as important elements of their overall marketing strategy, as a way to develop and maintain good relations with their customers. Puget recently formed a nonregulated subsidiary, Puget Energy Services. Gary is president of the subsidiary, whose purpose is to sell energy services (the shared savings concept) to commercial and industrial buildings. Central Maine Power Company (Augusta, ME). CMP is one of the smallest and, in some ways, the most isolated of the utilities I visited. They have 2000 employees, are located in the extreme Northeastern corner of the u.s., and are temporarily not members of either EPRI or EEl (because the Maine PUC will not permit these costs to be included in rates). In spite of these factors, CMP operates the usual variety of conservation programs, has recently initiated several interesting conservation pilot programs, and has a robust analytical process to plan and analyze these programs. In addition to the pilot programs, CMP is about to start a major commercial sector program, including energy audits and low interest loans or rebates (equivalent to a 20% subsidy from CMP). Because of its small size, conservation program planning and analysis, program implementation, forecasting and demand-side planning, load
38
research, market research, and rate design all report to the same Vice President (Lynn Goldfarb, VP for Customer Services). This close organizational coupling among groups and the small size of this department (50 people) reduces the turf battles sometimes seen in larger organizations. By comparison, some other utilities have three different Vice-Presidents responsible for these functions. CMP is active in C/LM programs largely because of pressure from the Maine PUC, the Office of Energy Resources, and the Public Advocate {who represents the "public" in PUC hearings). In addition, CMP's past financial problems with nuclear plants {Seabrook and Millstone) make them strongly averse to starting a large new power plant. CMP and the PUC have been quite successful recently in working out agreements concerning CMP's demand-side programs outside the formal PUC hearing process. This has resulted in several "stipulations" in which the parties (e.g., CMP, Public Advocate) formally agree on a course of action, which is then presented to the PUC for approval. CMP is proud of its recent track record in avoiding contentious battles with regulators and intervenors. The Company is developing market-research driven conservation programs. That is, rather than paying full-avoided cost for conservation (as PURPA requires for cogeneration and as Pacific Northwest conservation resource acquisition programs might suggest), they are trying to determine how little they can pay to achieve reasonable program participation and energy savings. For example, they are currently conducting a small experiment to determine response rates among residential customers to different levels of rebates for retrofit. The responses to a recent single mailing were: Rebate 1eve 1 15% 25% 50%
Response rate 16% 16% 22%
These results suggest that the size of the rebate is much less important than its existence. A 15% rebate yields almost as much participation as does a 50% rebate. Because CMP has a winter peak, they are primarily interested in programs that affect space heating electricity use and other winter uses. However, oil is their marginal generating fuel throughout most of the year, so the difference between peak and off-peak generating costs is probably small {which is generally true throughout New England). Because of this situation, there is less emphasis on load management relative to conservation than in other utilities that have strong peaks and large peak/off-peak costs. The Market Research and Forecasting group uses USAM (Utility System Analysis Model, the same model used by SCE), a microcomputer-based program, to conduct their integrated resource planning process. Like LMSTM, USAM requires a great deal of input data on pre- and post-program
39
daily load shapes for all end-use technologies affected by CMP programs. As with most utilities, CMP staff rely primarily on their intuition in feeding the model. Because USAM does not include important feedback loops between demand and supply, system optimization can be achieved with USAM only by manual iteration. The Market Research group would like to find or develop a model that can endogenously seek an optimal solution; they are also interested in improving their ability to conduct useful sensitivity analyses. New England Electric System (Westborough, MA). NEES is a holding company with operating utilities in Massachusetts, Rhode Island, and New Hampshire. They created considerable interest among utilities with their 1979 NEESPLAN, which offered a variety of steps to provide for future electricity demands (with heavy emphasis on converting oil-fired power plants to coal). In May 1985, they published NEESPLAN II, with a strong emphasis on balanced, least-cost planning, which includes C/LM programs to hold demand growth to about 1%/year. I met primarily with staff in two groups - Demand Planning and Energy Conservation (program implementation), both of which report to the same VP (Gerald Browne). NEESPLAN II is a major focus of the work in both groups. The most interesting aspect of NEESPLAN II from the program implementation perspective is the establishment of two "Enterprise Zones" in central and western Massachusetts. Within these two areas, NEES will conduct a package of programs designed to generate substantial electricity savings among all customer classes. In some respects, this effort is like the Hood River Conservation Project, with its focus on welldefined geographical areas. The NEES effort also parallels HRCP in its effort to achieve large penetration rates, short-time focus (about two years), and experimental nature. It will be interesting to see whether NEES' data collection and subsequent evaluations will yield as much useful information as HRCP is. NEES views itself as analytically very lean. They pride themselves on an ability and willingness to make decisions quickly and to be actionoriented. As one NEES analyst put it, their corporate philosophy is, "Ready, Fire, Aim." Their emphasis on action and dislike of complicated paper studies is reflected in the small staff devoted to Demand Planning. The 20 people in this group are responsible for energy and demand forecasting, load research, load management, program planning and experiments, and program evaluation; by comparison, Northeast Utilities has about 50 people working in these areas. As an example of the small size of the NEES analytical staff, consider their load management experiments. NEESPLAN II includes six load management pilot programs, including combinations of direct control and peak-pricing for residential and commercial customers. Only two people are assigned to the design, data collection, and analysis of these experiments. (One additional staff person has been approved for 1986 to work on these projects.)
•
~~· ..
40
NEES staff dislike the existing integrated resource planning models (e.g., LMSTM) because of their long run-times and enormous input data requirements. NEES developed its own screening model, which operates on an IBM-PC. Two aspects of the model particularly impressed me. First, the data requirements on demand-side programs were less outrageous than those of other models. For example, instead of requiring daily load shapes for each day-type and season, the NEES model requires only estimates of annual electricity savings, winter peak reduction, and summer peak reduction. Second, the program is sufficiently friendly that their Executive VP can (and does) use the model. Of course, the small size and limited data inputs require simplifications within the model. For example, the model has limited detail on the supply side (only estimates of future operating costs are input, not the details on individual existing generating units, although future generating plants are individually detailed). Also, the model has limited feedback loops between supply and demand, and can adequately treat alternative rate structures only indirectly. Northeast Utilities (Hartford, CT). Although NU is also a holding company, with operating utilities in Connecticut and Massachusetts, NU and NEES differ in important ways and enjoy a friendly competition. Where NEES is analytically lean and action-oriented, NU has much greater depth in planning and analysis of demand side programs. For example, NU's Consumer Research Department and Rates and Load Research Department have about 50 people; NEES's Demand Planning Department has about 20 people to cover roughly the same areas. While NEES rarely publishes results of their analyses, NU's staff write many reports. My impression is that NU has been much more successful than most utilities in C/LM program planning, analysis, and evaluation activities and in integrating these activities with each other and with NU's energy and load forecasting models. NU (along with PGandE and Puget Power) is probably the most active and successful in understanding its commercial customers, in developing a useful engineering/economic model of commercial energy use (EPRI's COMMEND model), and in running commercial sector conservation programs. They have been successful in integrating their commercial audit program and its data collection with additional surveys and billing data to provide useful inputs to their commercial forecasting model. Like many other large utilities, NU relies heavily on contractors to do much of their research. Development of their commercial data base involved Xenergy (which also runs their commercial audits}, SRC, and AMS. NU has been developing and using what they call an Integrated Demand/Supply Planning System (IDSP) during the past few years. The corporate planning staff consists of only three people, reporting to the same VP responsible for consumer research and load research/rates. The planners serve primarily as coordinators among various offices within NU. Thus, the corporate planners oversee the process, ensure that consistent assumptions are used by the different groups, and help define
41 overall demand/supply strategies to test with these models. Analyses are run on NU's production costing model and financial model. My sense is that the process is dominated by the supply planners since much of the analytical horsepower is in their shop. Dick Brown, the NU corporate planner, assures me that although much of the analytical work is done in supply planning, the process is unbiased. NU investigated LMSTM but found the results did not calibrate with their in-house production costing simulation model. The discrepancies were due primarily to NU's large pumped storage facility. Because of these discrepancies and the cost of maintaining a separate integrated model (about two full-time people), NU decided to use their existing models for IDSP. The first IDSP cycle started in late 1983 and ended in early 1985. The second cycle began in Fall 1985 and will be completed in 1986. The process is lengthy because NU considers a broad range of individual demand and supply options, carefully screens these options for inclusion in IDSP, combines these options in various ways to develop useful portfolios for NU management to consider, and then carefully assesses each portfolio with extensive sensitivity analyses. Full IDSP cycles will probably be run only every second or third year in the future. NU's IDSP process represents a substantial improvement in integrated planning over the original NU 80s/90s programs, the first of which was written in 1980. NU's demand-side focus is on conservation rather than load management. This is a consequence of their supply system, which uses oil as the marginal fuel throughout most of the year and which includes a 1000 MW pumped storage unit (an enormous load management capability for a 5000 MW system). In addition, their CT and MA regulators strongly pushed NU into conservation programs in the early 1980s. During the next few years, NU expects to expand their radio control water heating program, convert more customers to mandatory time-of-use rates (probably down to a minimum size of 100 kW), and undertake more load management research projects (e.g., cool storage). NU has mandatory time-of-day rates for large C&I customers. The cutoff for these TOD rates is being lowered steadily, from 1 MW today to 500 kW in two years. There is considerable discussion within NU over the relative merits of proper price signals and conservation programs (especially subsidies). Interestingly, both state PUGs are now adopting more of a business view towards NU demand-side programs and are less concerned about the social service aspects (especially saving oil) of the programs than they were a few years ago, perhaps because oil prices are declining and increasing recognition that utility conservation programs can affect electricity rates. The MA Commission is particularly aggressive in its view of demand-management programs as an electricity resource that should be considered primarily on its economic merits. The MA PUC is pushing hard on the shared-savings idea. NU recently completed contract negotiations with energy service companies to purchase energy savings in Massachusetts. After MA Commission approval, the programs will begin.
42
Although NU is very open to demand-management activities on the part of the utility, they are concerned about the quality of data they have on their C/LM programs. They (and their regulators) recognize the need to develop much better data on the characteristics of relevant demandside technologies, customer response to different types of programs, and the actual energy and load effects of these programs. The role of evaluation (examining past program performance) in assessing the likely value of future programs is a critical and unresolved issue. Niagara Mohawk Company (Syracuse, NY). NiMo is a major combination company in upstate NY, serving 1.4 million customers. I visited with staff in their Corporate Development Department (Chris Turner, VP). This group of about 60 people was formed in Fall 1984 and is responsible for design and implementation of conservation, load management, and marketing programs; RCS energy audits; economic, energy and load forecasting; economic development; load research; rates; and market research. NiMo recently began a major demand-side research program. The program was stimulated by a 1984 NY PSC order, requiring the New York utilities to spend "up to 0.25% of annual revenues ••• " on conservation R&D. The order stemmed from continuing controversy over the need for NiMo's Nine Mile Point 2 nuclear plant (as well as other nuclear units in New York) and the Environmental Defense Fund's assertion that utility purchase of conservation would be both feasible and more cost-effective than completion of the power plant. The PSC approved completion of the plant and required the utilities to carefully investigate their conservation-resources. NiMo is taking the Commission's order seriously and is implementing a variety of projects (at a cost of almost $5 million a year). These projects include several load research efforts to determine customer and end-use load shapes for electric heating and nonheating residential customers, farm customers, new homes, small commercial customers, and large commercial customers. Various types of financial incentives will be tested in pilot settings to determine market penetration and costs associated with rebates or shared-savings in the residential, farm, commercial, and public sectors. Surveys and other data sources will be used with a variety of analytical techniques to develop baseline information (equipment holdings, building types, energy use levels) for each sector. Much of the work associated with these projects will be contracted out. However, NiMo intends to work closely with these contractors so that their staff can conduct future projects. That is, as time progresses a larger fraction of the work will be conducted with NiMo staff. Interestingly, NiMo currently has excess capacity. When Nine Mile Point 2 becomes operational next year, NiMo will have even more capacity. Further, their service area is experiencing very slow economic
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growth (the rust belt syndrome). Nevertheless, they are quite interested in these demand-side pi'Ograms because of the opportunities they present to learn more about their customers. Like some other utilities, NiMo is concerned about competition and recognizes the need to become more market-oriented - to understand customer needs and to help satisfy them. Alternative electricity rate designs and efficiency-improvement programs can help NiMo meet customer needs. They also recognize that New York's facility siting process will not permit construction of another large central-station power plant unless NiMo can demonstrate that they have fully exploited all lower-cost demand and alternative supply options. In part because of the problems and controversy associated with Nine Mile Point 2 and in part because of the facility siting process, NiMo would like to defer construction of the next large power plant for as long as possible; C/LM programs are an obvious way to do that. Finally, C/LM programs offer potential payoffs relative to generating plants in 10 - 15 years, but may offer payoffs much sooner with respect to transmission lines and the distribution network. Specifically, part of their service area is experiencing rapid growth in electricity demand. Meeting this demand would require construction of additional transmission lines. Kowever, it may be less expensive for NiMo to target demand-side programs to this part of their service area and defer the need for additional transmission lines. NiMo has an Interdisciplinary Studies Committee, made up of eight members (mostly VPs}, who are responsible for developing their integrated resource plan. In addition, NiMo has a "group of 56," composed of officers and middle managers that meet regularly to develop corporate goals. Recommendations from the group of 56 are reviewed by the Strategic Planning Committee, NiMo's senior officers. The engineering, power supply planning, and financial planning staffs have several large models used to support these functions. Currently, these models are exercised to help develop their integrated plans. In addition, the Corporate Development Department uses EPRI's Load Management Strategy Testing Model. Participants recognize, however, that independent of which models are used, the data on demandside programs are weak. As John Endrie, Senior VP, said, they have two questions about conservation and load management programs: Will they work? Are they good -(i.e., cost-effective) for NiMo and its customers? NiMo's winter and summer peaks are quite similar. Their load factor is typically in the mid-70s, which suggests that reducing peak demands is not a critical factor for them. Much of their generation is in the western portion of their service area, while most of the demand growth is in the eastern part. Kence, their short-term concerns are focused more on transmission than generation. Also, most of their generating units are large, which limits their flexibility in meeting varying load shapes.
44 General Public Utilities (Parsippany, NJ). GPU is a holding company with three operating utilities, one in New Jersey and two in Pennsylvania. I met with staff in the Demand Programs Group (headed by Jim McConnell). This group of 18 is responsible for GPU's demand-side modeling, load research, energy and load forecasts, and C/LM program planning and evaluation. Two other groups concerned with supply planning and financial planning report to the same Vice President. Because of the 1979 accident at Three Mile Island and GPU's subsequent loss of both TMI nuclear units, their interest in C/LM programs is unique. Unlike most of the other utilities I visited (except perhaps Puget Power), GPU views conservation as an important- and currentresource that it must purchase. Put another way, GPU's costs of purchased power are sufficiently high that many aggressive conservation programs (which would be economically unattractive in other utilities) are very cost-effective to GPU. GPU's 1986-~988 C/LM plan includes a variety of interesting programs. A major continuing program is their residential water heater control/ time-of-day rate. First implemented on a small scale in 1983, this program is gradually converting more and more customers to the time of day rate with water heater control. GPU also began the innovative Residential Energy Conservation Action Program (RECAP), which involves GPU's purchase of electricity savings from contractors. The program, similar in concept to the shared-savings idea, places most of the risk on contractors who sign-up households, conduct energy audits, and install appropriate retrofit measures. This program has attracted nationwide attention because of its emphasis on saving energy, rather than providing information (audit-only programs) or subsidizing retrofits (loan or rebate programs.). GPU recently purchased the Good Cents Home Program from Gulf Power to improve efficiency of new homes. GPU is also initiating shared-saving programs among their commercial and industrial customers. The content and format of the program, called Partners in Conservation (PIC), varies according to the electricity consumption of the customer. For example, small C&I customers (who use less than 50,000 kWh/year) can participate in a program much like RECAP. For large C&I customers, GPU will help energy service companies by providing GPU legitimacy to their efforts and by guaranteeing to the building owner the first year's energy saving. GPU has yet a third program for the very largest C&I customers. GPU' s planned budget for the three year period from 1986 through 1988 is almost $130 million, an indication of how seriously they are committed to C/LM programs. Because these programs are essential to GPU, they have carefully evaluated some of their programs. However, many gaps exist in their knowledge about the effectiveness of their programs, primarily because they have so many programs, most of which have not yet been evaluated.
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The regulatory environments are quite different in the two states, with NJ being very aggressive and sometimes hostile to Jersey Central Power & Light (the GPU operating company in NJ). GPU staff are concerned with delays resulting from detailed reviews conducted by the NJ Board of Public Utilities (their PUC) and the prior approval required from the BPU for all their programs. In PA, on the other hand, the regulators seem to have more respect for GPU and focus more on overall policy direction and less on detailed program prescriptions. GPU's integrated resource planning is quite informal. Initial load forecasts are developed in the Demand Programs group. They are intended to incorporate the effects of past C/LM programs; engineering calculations prepared by program planning staff are used to judgmentally adjust the forecast to account for planned C/LM programs. The final forecast, after approval by top management, is then given to the supply planning staff, who develop a suitable capacity expansion plan to meet the forecast loads. Although the demand and supply planners discuss their activities and results, there is no formal integration process or feedback loops built into the present system. Thus, sensitivity analyses cannot be readily conducted. However, given GPU's substantial energy shortfall during the past seven years (because of TMI), there has been little need for a very sophisticated IRP process. GPU's need for low-cost conservation resources has been clear. Also, GPU's financial situation prevented consideration of any capital-intensive projects. Finally, GPU's participation in the PJM power pool makes it easy for GPU to determine their marginal costs as a function of time, which further simplifies GPU's internal IRP process. Now that GPU's situation [both financial and generating resources (with the recent restart of TMI-1)] is changing, the need for better planning tools and processes is becoming apparent to GPU staff. Wisconsin Power & Light (Madison, WI • WP&L is a small combination ut1 1ty, serving most of southern Wisconsin. I visited with people in their Electric Marketing and Customer Service Department, headed by Paul Koeppe. This group of 35 people is responsible for WP&L's electricity sales and load forecasting, load research, rate design, analysis of alternative supply options, market research, contact with major industrial customers, design of pilot programs, and management of systemwide conservation programs. (An analogous department deals with similar issues concerning natural gas.) The WI PSG has long been active in promoting utility conservation programs. For example, the PSG has required (since 1976) that utilities file biennial reports, called Advance Plans, to set forth the utilities' plans for meeting and managing future electricity demands. WP&L's Load Forecasting Committee is being reconstituted as their Integrated Planning Committee, in part to develop better Advance Plans. WP&L and PSC staff agree that the utility is making progress in its
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efforts to integrate demand- and supply-side planning, but both groups agree that much more needs to be done. Currently, the process is ad hoc, relying primarily on informal interactions among a few key people in various departments. Fortunately, WP&L is a small enough utility that this kind of process can work. According to Bill Register, the Vice President who chairs their Integrated Planning Committee, the key issues in their Advance Plans concern reliability of demand-side resources: How much, how quickly, and at what cost can WP&L purchase these electricity savings, and how long will the savings last? WP&L staff recognize the importance of careful evaluations of thoughtful pilot programs in reducing the uncertainties associated with C/LM programs; see discussion below. Improveme~ts to WP&L's demand forecasting models are also important in strengthening their ability to develop integrated plans. In response to a PSC order two years ago, WP&L conducted a major study to examine their conservation resources and programs that would deliver these resources. The final report on their Market Price Study, published in Fall 1984, forms the basis for much of their present C/LM work. For example, like many utilities, WP&L has several information-only conservation programs, including RCS and CACS. They also operate a lowincome weatherization program, which offers subsidies to retrofit these homes. They are beginning a program to improve efficiency of new homes, using the Good Cents Home Program. Based on ideas developed in last year's Market Price study, they are testing financial incentives in a pilot settng. They are testing various types and levels of rebates for purchase of energy-efficient refrigerators in three communities. They are also testing the effectiveness of a rebate for efficient water heaters.
47 APPENDIX B.
NOTES ON INTEGRATED PLANNING MODELS
Load Management Strategy Testing Model. LMSTM was developed by Decision Focus, Inc. for EPRI in 1982. Since then, it has been used by many utilities throughout the country. LMSTM's main attraction is its integration of several functions within one model. Specifically, LMSTM has four major submodels - Demand, Supply, Finance, and Rates. The Demand submodel computes system load shapes for an entire year, based on detailed (end-use) inputs to this submodel. These load shapes are then passed to the Supply submodel, which dispatches power plants to meet the load for that year. The costs to operate these plants (including direct control devices, forced outages, and scheduled plant maintenance) are fed to the Rates submodel and cash flows associated with power plant construction are passed to the Finance submodel. This portion of LMSTM computes income statements, balance sheets, and assets and liabilities for the utility. Outputs from the Finance submodel are used in the Rates submodel to allocate costs to each customer class and set rates for the following year. These rates are then input to the Demand submodel and the cycle continues. LMSTM is very data intensive. Development of the input data sets is complicated by the fact that the data must come from several different departments within a utility - Conservation and Load Management, Marketing, Operations, Power Supply Planning, Rates, and Treasury. The demand submodel of LMSTM is, from mY perspective, weak. All the important work associated with development of energy and load forecasts for the utility, changes in saturation and efficiency of end-use devices, changes in operating characteristics of these technologies, estimation of customer participation in C/LM programs, and estimation of the energy and load effects of participation in programs must be done off-line (i.e., before one prepares inputs to LMSTM). Thus, the model user must either estimate (guess at?) the important inputs or have available relevant program evaluations and load research data. Thus, LMSTM operates primarily as a giant accounting tool. The beauty of LMSTM is its ability to easily estimate (after all the input data sets have been prepared and validated) the electric system impacts of demand-side programs. Thus, a program to control residential water heaters or to install efficient lighting in office buildings can be quickly examined in terms of how power pla"nts are dispatched, the total costs of operating the power system, uti 1i ty revenue requirements, rates, changes in the future need for power, and the possibility of deferring capacity additions. Most evaluations of utility demand-side programs (including ours at ORNL) include very limited benefit/cost analyses. Exogenously specified average and marginal costs are used to determine whether the program is economically attractive. Such analyses cannot include the time-
48
differentia ted aspects of electricity savings and marginal costs, nor can they account for feedbacks among demand-side programs and operation of existing power plants, construction of new plants, and the financial and rate implication s of these interaction s. LMSTM automatically does all this. Other utility lannin models. I also looked at a few other similar models. Lotus Consulting Palo Alto, CA) offers their Utility System Analysis Model (USAM}. Its main attraction is that it runs on an IBM-PC or compatible microcomputer. Thus, interaction with a mainframe computer and associated computer service department personnel are not required to use USAM. In some respects, USAM is similar to LMSTM. USAM submodels do monthby-month production costing, capacity expansion planning, load planning, and financial projections . However, USAM does production costing with seasonal load duration curves rather than with direct simulation. Also, USAM cannot handle alternative rate structures; that is, changes in load shape and changes in revenues due to various rates cannot be computed with USAM. Also, USAM does not endogenously compute marginal costs as does LMSTM. USAM does not have a benefit/cos t module (as does LMSTM). USAM has a separate model (Utility Marginal Cost Model) that computes marginal costs based on the USAM production costing algorithm. A key feature of the USAM models is their easy-to-use interactive nature. For example, USAM writes its output to a Symphony spreadsheet , which is very easy for the user to manipulate to produce desired outputs. LOADCALC (developed by Applied Energy Group in Kew Gardens Hills, New York} is an even simpler microcomputer model than USAM. It has similar end-use detail to that found in USAM and LMSTM, but less detail on the supply side. Supply-side characteris tics are embodied in five primary inputs to LOADCALC: avoided costs for generation, transmission and distributio n, marginal fuel costs (up to four rating periods) and average electricity cost. LOADCALC is a screening tool for evaluating the cost-effecti veness and load impacts of demand-side strategies (conservatio n and load management) at the end use level, given a set of supply side assumptions. Analyses and subsequent sensitivitie s can be quickly performed for all assumptions (e.g., end-use efficiency, end-use load shapes, demand-side program design and cost, speed of implementation, customer growth, peak period and escalation rates). Cost/benefi t tests are performed from four different perspective s: the utility, participatin g customer, nonparticipatin g customer and society. Like USAM, LOADCALC uses a popular spreadsheet program (LOTUS 1-2-3) for inputs and outputs, which makes the model quite user-friend ly. The Conservation Policy Analysis Model (CPAM) was developed by the Los Alamos National Laboratory and Applied Energy Services for the Office of Conservation, Bonneville Power Administrat ion. The model,
