Using deferrable demand in a smart grid to reduce the cost of electricity for customers
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The primary purpose of this paper is to evaluate the benefits of distributed storage capacity in the form of deferrable demand managed centrally by a system operator, and in particular, to determine the savings in the total annual cost of supplying electricity for a system that has a substantial amount of variable generation from wind turbines. Since the objective of a centrally controlled system is to minimize the expected daily operating costs subject to the availability of generating units and storage capacity, the basic economic question is whether the savings in the annual system cost of supply, including the capital cost of installed generating capacity, can offset the capital cost of installing deferrable demand capacity. The analysis uses a new multi-period model of a power grid that treats stochastic generation explicitly and determines the optimum hourly commitment of conventional generators and the charging/discharging of deferrable demand needed to maintain the reliability of supply. A simulation example shows that deferrable demand can reduce system costs by (1) shifting demand from expensive peak periods to less expensive off-peak periods, (2) providing ramping services to mitigate the variability of wind generation, and (3) reducing the amount of installed peaking capacity needed for System Adequacy and the associated capital costs. If customers pay rates for electricity that reflect the true system costs of supplying their patterns of purchases from the grid, customers with deferrable demand will pay lower bills for electricity and their savings will be substantially more than the cost of installing deferrable demand devices. The results also show that if customers pay typical flat rates for electric energy, the economic incentives for installing deferrable demand are perverse.
KeywordsPower system economics Energy storage Pricing and rate design
The authors would like to thank Ray D. Zimmerman, Carlos E. Murillo-Sanchez, Robert J. Thomas, Michael Crew and other participants at the Eastern and Western Rutgers Conferences organized by the Center for Research in Regulated Industries at the Rutgers Business School-Newark and New Brunswick for their comments and input. We also thank two anonymous reviewers for their constructive suggestions. This research was supported by the Lehigh Faculty Innovation Grant, the US Department of Energy through the Consortium for Electric Reliability Technology Solutions (CERTS), the Power Systems Engineering Research Center (PSERC), an NSF I/UCRC, and by NSF-Project 64581 “Cyber-Physical Energy Systems: Foundations for Smart Grids Supporting Intelligent Dependable Energy and Active Load.” The authors are responsible for all conclusions presented.
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