Research | VaasaEtt Global Energy Think Tank

Understanding and Motivating Energy Conservation Via Social Norms

The purpose of this 3-year project was to examine the role of normative beliefs in an
individual’s decision to conserve energy. In our proposal we outlined three sets of studies, with
each set to be conducted over the course of a year. In the first set of studies, summarized in our
2002 Yearly Report, we examined the reasons that people gave for conserving energy, and the
role of normative beliefs in energy conservation behaviors. Data for these analyses were based
on random digit dialing telephone surveys of California residents. The second set of studies,
which were summarized in our 2003 Yearly Report, involved the development of conservation
messages that were placed in hotel rooms. A series of five experiments were conducted in
California and Arizona. The results from these studies clearly indicate that messages targeting
the normative aspects of energy conservation can significantly increase conservation behaviors.
The third and final set of studies, reported below, examined the effectiveness of a normative
feedback intervention for promoting household energy conservation among a diverse sample of
community residents.
Each of the studies involved collaboration between researchers at Arizona State
University (ASU) and California State University, (CSU) San Marcos. Over the course of the
past year, the research teams from ASU and CSU met three times for discussion and planning:
twice in Arizona, and once in Austin, Texas, for the annual meeting of the Society for
Personality and Social Psychology (SPSP). Each research team consisted of two graduate
students, and several undergraduate research assistants. The research meetings allowed us an
opportunity to develop research methodology and materials, discuss project activities, and
review and analyze data. Following is a summary of the activities and findings from the third and
final year of the project.

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Demand Response in Finland

This is a presentation made by Pekka Koponen of VTT about demand response in Finland.

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Successful EPC Schemes in Two Member States: An ECEEE Case Study

As part of its ongoing work to ensure the EU achieves the full benefits from the Energy
Performance of Buildings Directive, eceee has looked in detail at the way two Member
States – Portugal and Ireland – have implemented the requirement for Energy
Performance Certification (EPCs). These are contained within Article 7 of the existing
Directive1, or Article 10 of the proposed recast2.
Both countries recognised, at an early stage, the benefits of certification as a tool to
improve the building stock – both residential and non-residential. Common features of
both schemes are the attention put into the design of the overall system, rigorous criteria
for building assessors and the use of national databases to register both assessors and
certificates.

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Do Savings from Energy Education Exist?

This report provides the first thorough examination of the persistence of energy savings from energy efficiency education. It does so by comparing gas savings for low-income utility customers who received weatherization to similar customers who also received in-home education and a setback thermostat. Enegy use data is analyzed for savings both the first year after treatment and the third year after treatment to compare savings and determine persistence of savings.
This study compares the energy savings for two treatment groups. Weatherization Group households received traditional weatherization based on New York State’s Weatherization Assistance Program (WAP). The Education Plus Group received comprehensive energy management including weatherization, energy education and a setback thermostat; they also participated in an affordable payment plan.
The original first year analysis of the Niagara Mohawk Power Partnerships (PP) Pilot (Harrigan 1992) showed savings of 16.3 percent for the Weatherization Group and 25.5 and 25.9 percent for the two Education Groups. Because some households in the original analysis moved or had data that did not meet certain screening criteria, fewer households were included in this analysis, which changed the first year savings. Based on this new analysis, the Education Plus Group saved 456 therms (23.9 percent) of normalized annual consumption (NAC), and the Weatherization Group saved 255 therms (13.8 percent).
In the third year, the Education Plus Group saved 396 therms (20.1 percent) compared with 220 therms (12.6 percent) for the Weatherization Group. When third year savings for the Education Plus group are compared with the Weatherization Group, savings for the Education Group are almost 60 percent higher. First and third year savings for both groups are significant compared to their pre-treatment consumption. The differences in percent savings (heating and NAC) between the Education and the Weatherization Groups are significant in the first and third years.
Persistence of savings is approximately the same between the two groups. Eighty-five percent of first year savings were still evident in the third year for the Education Plus Group, and 90 percent of the Weatherization Group’s first year savings were evident the third year. The difference in persistence of savings between the groups was not significant.

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The Long-Run Effects of a Time-of-Use Demand Charge

Modifications in demand due to time-of-use (TOU) pricing have potential to improve the
efficiency of electric power supply. With long lead times for plant construction, utility planners
need long-run estimates of response to TOU rates. Existing evidence is primarily drawn
from short-run TOU experiments. We provide estimates of long-run response to a nonexperimental
residential TOU rate offered by Duke Power. The rate contains a demand charge
applied to the maximum rate of energy consumption during the peak period. We find that
customer response increases over time in a manner that enhances the ability of TOU rates
to reduce system peak.

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Residential Implementation of Critical-Peak Pricing of Electricity

This paper investigates how critical-peak pricing (CPP) affects households with different usage and income levels, with the goal of informing policy makers who are considering the implementation of CPP tariffs in the residential sector. Using a subset of data from the California Statewide Pricing Pilot of 2003-2004, average load change during summer events, annual percent bill change, and post-experiment satisfaction ratings are calculated across six customer segments, categorized by historical usage and income levels. Findings show that high-use customers respond significantly more in kW reduction than do low-use customers, while low-use customers save significantly more in percentage reduction of annual electricity bills than do high-use customers – results that challenge the strategy of targeting only high-use customers for CPP tariffs. Across income levels, average load and bill changes were statistically indistinguishable, as were satisfaction rates – results that are compatible with a strategy of full-scale implementation of CPP rates in the residential sector. Finally, the high-use customers earning less than $50,000 annually were the most likely of the groups to see bill increases – about 5% saw bill increases of 10% or more – suggesting that any residential CPP implementation might consider targeting this customer group for increased energy efficiency efforts.

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Dynamic Pricing, Advanced Metering, and Demand Response in Electricity Markets

Electricity restructuring, as it has been implemented in numerous U.S. states and around
the world, has been advocated as a means of producing and consuming electricity more
efficiently. In many cases, the results so far have fallen well short of the goals, with the
California electricity crisis of 2000-01 being just the most publicized disappointment.
While there has been heated debate about the reasons for these failings, there is
remarkable agreement over at least the broad outline of one response: the demand side of
the industry should play a more active role, receiving economic incentives to help
balance supply and demand. The way in which this notion should be implemented,
however, is still the subject of a great deal of debate.
In this monograph, we present an overview and analysis of the possible approaches to
bringing an active demand side into electricity markets. We begin in section I by
describing the ways in which economic incentives can be introduced on the demand side.
We discuss the fundamental economics of establishing these incentives and the economic
loss from systems that lack demand-side participation. We analyze the effect of these
incentives on the efficiency and competitiveness of the market, discuss how time-varying
electricity pricing need not conflict with the goals of customer bill stability and meeting
retailer revenue requirements, and we evaluate who the winners and losers are from
implementing price-responsive demand. In section II, we move from the more general to
specific issues of implementing time-varying prices. We discuss approaches to setting
the retail prices, what metering and communications equipment are necessary for various
forms of price-responsive demand, and how billing processes would have to change to
adapt to the more complex pricing system. We also examine the role that demand
response could play in matching supply and demand. In section III, we examine the
ways in which customer response to time-varying prices. We discuss both the potential
responses that are envisioned by those who study optimization of power use and the
actual responses that have taken place in pilot and long-term programs. We conclude in
section IV with some policy recommendations.

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Appendix F: Impact of Dynamic Pricing On Low-income Customers: Quantifying the Benefits of Dynamic Pricing In the Mass Market

Dynamic pricing offers electric customers lower prices during most hours of the summer while raising prices
significantly for a small percentage of hours when system conditions are critical (typically 2 to 3 percent of
all summer hours). The primary attraction of dynamic rates such as critical peak pricing (CPP) or real-time
pricing (RTP) is that these rates provide direct incentives to reduce electricity usage when the electrical
system is most stressed because they reflect daily peak marginal costs.1,2
Some have expressed concern that dynamic pricing may adversely impact low-income customers. In
jurisdictions where dynamic prices are under consideration, many utilities are currently pilot testing some
type of CPP rate.3 In this appendix, we summarize the impact of CPP on low-income customers based on
empirical results from the California Statewide Pricing Pilot (SPP) of 2003-04.4 The results show that there
is no statistically significant difference in bill-savings across income groups. This means that high-income
customers on a dynamic rate do not benefit more than low-income customers, on average. However, taking
usage into account, low-income customers in very high usage groups may find it difficult to “save” under a
CPP rate. From a policy perspective, alternative dynamic pricing options should be considered for this group
of high-usage, low-income customers. Depending on the definition of high usage, this represents about 2.2
percent to 5.7 percent of all households in the U.S. or 4.2 percent to 11 percent of all low-income
households. (See Tables F-1 and F-2).5 One obvious solution is to offer a peak-time rebate (PTR) rather than
CPP to this specific group of high-usage, low-income customers. In addition, low-income customers in the
low-usage group could be offered a choice between PTR and CPP. In the District of Columbia, as part of its
dynamic pricing pilot program, Pepco is currently offering a PTR (also called a critical peak rebate or CPR)
to customers that are currently on the Residential Aid Discount (RAD) program. The California SPP consisted of three tracks: Track A, which included a statistically representative sample of
customers; Track B, which focused on low-income customers in areas of San Francisco (located in close
proximity to a power plant); and Track C, which focused on customers in San Diego that had smart
thermostats.7 Track A comprised four climate zones while Tracks B and C focused on single climate zones.
In this appendix, we examine the impact of dynamic pricing on low-income customers based on the results
of the SPP. First, we summarize the results of a recent study that focused on the final three-month period of
the SPP: July 1 to September 30, 2004.8 These results are indicative of an established program. Second, we
provide results for Track B customers only, which represent low-income customers over the entire SPP (15 months from July 2003- September 2004). Finally, we provide results for Track A customers, which
represent the general population of California over the 15-month period. Using Track A, we compare lowincome
customers to other customers in the same track. As shown below, each of these comparisons shows
that low-income customers do respond to dynamic prices. However, as pointed out earlier, there may be very
specific groups of customers that should be targeted for PTR rather than CPP.

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Industrial Customer Response to Wholesale Prices in the Restructured Texas Electricity Market

This paper estimates the demand responsiveness of the 20 largest industrial energy consumers in the Houston area to wholesale price
signals in the restructured Electric Reliability Council of Texas (ERCOT) market. Statistical analysis of their load patterns employing a
Symmetric Generalized McFadden cost function model suggests that ERCOT achieved limited success in establishing a market that
facilitates demand response from the largest industrial energy consumers in the Houston area to wholesale price signals in its second year
of retail competition. The muted price response is at least partially because energy consumers who opt to offer their ‘‘interruptibility’’ to
the market as an ancillary service are constrained in their ability to respond to wholesale energy prices.

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Real Time Pricing and the Real Live Firm

Energy economists have long argued the benefits of real time pricing (RTP) of electricity. Their basis for modeling customers’ response to short-term fluctuations in electricity prices are based on theories of rational firm behavior, where management strives to minimize operating costs and optimize profit, and labor, capital and energy are potential substitutes in the firm’s production function. How well do private firms and public sector institutions’ operating conditions, knowledge structures, decision-making practices, and external relationships comport with these assumptions and how might this impact price response? We discuss these issues on the basis of interviews with 29 large (over 2 MW) industrial, commercial, and institutional customers in the Niagara Mohawk Power Corporation service territory that have faced day-ahead electricity market prices since 1998. We look at stories interviewees told about why and how they respond to RTP, why some customers report that they can’t, and why even if they can, they don’t. Some firms respond as theorized, and we describe their load curtailment strategies. About half of our interviewees reported that they were unable to either shift or forego electricity consumption even when prices are high ($0.50/kWh). Reasons customers gave for why they weren’t price-responsive include implicit value placed on reliability, pricing structures, lack of flexibility in adjusting production inputs, just-in-time practices, perceived barriers to onsite generation, and insufficient time. We draw these observations into a framework that could help refine economic theory of dynamic pricing by providing real-world descriptions of how firms behave and why.

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