Abstract

This paper presents a MATLAB based dynamic simulation tool for estimating demand response potential from residential loads. First, a review of residential demand response strategies is conducted. Next, the modeling approach used during the development of this tool is described. Markov chain based occupant behavior models constructed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with models of the most common residential loads to predict the dynamic changes in residential power demand on a one-minute time scale. Separate control schemes are used along with these models to simulate different demand response strategies. Finally, simulation results showing the benefits and trade-offs associated with residential demand response programs are presented. Future work will involve using this tool to examine specific utility areas and the development of real-time pricing and incentive program components.

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