Behavioral demand response: Unlocking untapped assets on the smart grid

by Sanderson Hull, MBA ’17

This article was written in response to a seminar given by Pete Curtice, Vice President of Strategic Sales with Opower at Duke University in an EDGE Seminar on Dec. 2, 2015 at Duke University’s Fuqua School of Business. This article voices one student’s perspective and does not necessarily represent the views of either Duke University or the seminar speaker.

Over the past decade, behavioral demand response (BDR) has proven to be a valuable early application of smart meters and the massive data collection they allow. BDR programs, such as those run by OPower on behalf of utilities, encourage peak-shaving via targeted communications to electricity consumers that encourage consumers to save energy. By using smart meter data, the effects of BDR programs can be accurately measured and used to compensate consumers for changes to their typical energy consumption habits. As Pete Curtice, Vice President of Strategic Sales at the demand response company OPower, described during his Duke EDGE seminar presentation on Dec. 2, smart meter data can also be analyzed to identify different patterns of usage among consumers and to target such customer segments most effectively. While initial results of BDR programs have been promising, continued rate reform and technological innovation are required to unlock BDR’s vast potential.

Demand response potential limited without rate reform

Today, one of the major inefficiencies of power markets is the disconnection between the time-varying marginal cost of electricity and the primarily flat cost per kWh paid by utility customers. This disconnect means that customers have no price signal to reduce demand during periods when wholesale electricity costs the most and shift consumption to periods when electricity is cheapest. Spot prices for electricity vary enormously over the course of each day, from lows of under $40/MWh during the early morning to highs over $100/MWh on hot summer afternoons and evenings. These prices vary in a highly predictable manner based mostly upon the season and time of day. However, because customers do not face time-of-use pricing, expensive investments in generation and transmission must be made to support inefficient usage patterns.

BDR programs seek to alleviate this issue by targeting the lowest hanging fruit. They ask customers to reduce demand on the few days a year when the disconnection between wholesale and retail rates are greatest. These programs have been effective, but they are dealing with the tip of the iceberg when it comes to alleviating inefficient market design. Rate reform that includes seasonal and time-of-day pricing for electricity would create much more direct incentives to customers and a potentially enormous market for BDR companies.

Flexible rate design faces several challenges. First, customer education and equitable treatment are major concerns. Rate changes must be done slowly and transparently in order to educate customers, allow them time to adapt their behavior, and prevent large increases or decreases in electric bills overnight. Second, the utility business model must be steered slowly to improve incentives while preventing financial hardship or windfalls. With traditional rate-of-return regulation, utilities earn a profit based upon the amount of electricity they sell (a direct disincentive towards efficiency programs like BDR) or, under decoupled rates, the amount of investments they make (a perverse incentive to overinvest). (For the case for utility rate decoupling, see the Alliance to Save Energy’s position.)

Both types of regulation fail to adequately incentivize investments in energy efficiency programs like BDR. As regulators seek to improve the rates received by customers, they must find ways to encourage utilities to invest in energy efficiency while maintaining the industry’s historically low cost of capital and dedication to reliability. This may require a slow but deliberate evolution away from classic rate-of-return regulation or direct quantification of efficiency as a type of “negawatt” asset that can earn utilities a profit.

Automated demand response may unlock more savings

Finally, technological innovation can play an important role in facilitating better demand response programs of all types. Innovative energy management hardware, software, and interfaces, like Nest, can provide more granular data about electricity consumption patterns and automate simple cost-saving decisions. Better customer interfaces and communication systems are particularly necessary for automated demand response, wherein utilities singlehandedly reduce energy usage (e.g., cycling air conditioning on and off) during costly peak events via remote control of customer devices. Consider the case of PG&E, which has suffered from declining enrollment in its automated demand response program in the past year due to the program’s high frequency of reduction events. PG&E now faces the tradeoff of either lowering the frequency of demand reductions per customer each year or losing customers in greater numbers. Both would weaken the efficacy of the program. Advanced energy management devices and their data could help solve this problem by allowing PG&E to better target customers with easily reducible demand and high willingness to modify their energy consumption.

Behavioral demand response has started to illuminate the power of demand-side assets, a historically neglected resource. By harnessing smart meter data, BDR programs have shown that energy efficiency can be a cost effective asset for utilities despite the many disincentives in today’s market. However, in order to unlock the huge potential savings from demand response and energy efficiency, regulators must find ways to align rate structures more closely with the true costs of energy. A more efficient market that even remotely reflects time-of-use costs will encourage major changes in consumer behavior. Although consumer education is a definite concern and rate changes must be implemented incrementally over time, improvements in energy management technology will help facilitate this transition and attract the interest of new investors. A revolution in energy pricing and consumption will not be simple. Yet, the potential benefits from demand-side assets are too great to ignore.

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