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Estimation for the Demand Response Potential of Residential HVACs

It has been proved by industrial practice that reduction of power system peak load can be effectively achieved through Demand Response (DR) programs, especially those based on direct load control of heating, ventilation and air conditioning devices (HVAC). When considering DR resource in planning and operation strategy of distribution system, accurate estimation of demand response potential for HVACs is crucial for improving the planning and operation outcomes. This paper proposes a methodology for estimating the demand response potential for residential HVACs using half-hourly smart meter data. The specific contributions of this paper extend the prior studies by: 1) establishing an HVAC load extraction framework based on a pattern similarity searching strategy; 2) incorporating the uncertainty of the baseload (i.e. energy consumption of nonthermal appliances) into the HVAC temperature response parameter estimation process. We apply this methodology on a real premise dataset that contains 300 households and show how it can be utilized to assess the DR potential of residential HVACs.