New CEC Pier Report: Distributed Energy Resource (DER) Implementation: Testing Implementation of a Demand - Response Program within a Small Business Population

The CEC has released a new report entitled "Distributed Energy Resource (DER) Implementation: Testing Implementation of a Demand- Response Program Within a Small Business Population" that is part of a larger, multi-year research effort that examined whether a combination of “distributed energy resources” – distributed generation, energy efficiency, and demand response – can beneficially smoothen the load usage and improve power quality at the distribution feeder level; estimate the benefits and costs of a diverse array of actually implemented distributed energy resources from the perspective of the utility, customers, and society; and evaluate the “real world” challenges to distributed energy resources adoption by a diverse set of energy consumers, including those in the public and private sectors. Download a copy here . This project element extended and narrowed the original research questions to focus on a unique demand-response pilot initiative implemented within a population of small (that is, less than 200 kilowatts of peak demand) commercial class ratepayers. In particular, the extension project investigated whether small electricity users will effectively participate in demand response programs without the use of enabling devices; examined the benefits and costs of an actually implemented demand response program within this customer class; and evaluated the practical challenges to demand response adoption by commercial customers. This customer class is responsible for more than one-third of statewide electricity use and is considered “hard-to-reach” by policy makers and utilities. The research project team consisted of San Francisco Community Power, a community-based nonprofit organization specializing in implementing demand management programs, and M. Cubed, a consulting firm with expertise in public policy analysis and resource economics. Collectively the participants reduced their load by an average of 4.9 percent across all curtailment call hours. However, use of this average masks the fact that the customers exhibited a split distribution of responses, in which during most curtailment periods the great majority of customers reduced their electricity use in response to a call while during some periods a minority of customers increased their use. In particular, and as reflected in Figure 1, during 81 percent of customers-days collective load was lower than the calculated baseline. However, on 19 percent of customer-days collective load exceeded the calculated baseline. 81 percent of the combined load, a total of 84,576 kWh, dropped by 9.2 percent, a reduction of 7,794 kWh as compared with the baseline. This reduction is less than the 11 percent decrease found in the earlier analyses, which was based on a different calculation that relies on a statistical regression method and focused on a much smaller participant population; but is somewhat higher than the approximately 9 percent reduction that has previously been found for the residential class in other studies. However, 19 percent of combined load, a total of 31,404 kWh, exceeded the calculated curtailment period baseline by 6.6 percent, or 2,083 kWh. These data strongly suggest that small customers can participate effectively in demand response programs. However, individual customers may not perform as expected, particularly at a given meter level. This factor is what prompts the need to appropriately lump together groups of customers as a way of spreading risks, but, more important, points to the need to quickly eliminate non-performing customers or meters, or, better yet, to screen them out before they are enrolled in the program. In addition, the baseline, though simple and transparent to calculate, omits what temperature effects could have been on the load and may not accurately measure actual reductions relative to what a customer would have demanded during the curtailment period. Other possible reasons for the estimated behavior include the possibility that demand response payments, or the absence of penalties may not be high enough to effectively induce participants to consistently curtail. For example, the value to the customer of continuing full operations outweighed the incentives to do otherwise, and/or these energy users may not have the capacity (for example, personnel) to reduce their electricity use when called upon. Key barriers to effective demand response implementation within the commercial class include the following: Energy users’ reluctance to adopt measures with which they are not immediately familiar. Lack of sufficient incentives for behavioral changes. Lack of information about energy consumption patterns. Negative previous experience with an energy management program.

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New CEC Pier Report: Distributed Energy Resource (DER) Implementation: Testing Implementation of a Demand – Response Program within a Small Business Population

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