Residential customers elasticity estimation and clustering based on their contribution at incentive based demand response

Incentive-based demand response (IBDR) is an important category of demand response (DR) programs with large untapped potential, especially in the residential sector. Understanding customers elasticity is key to effective design of incentives. However due to limited information, price-based elasticity is needed in IBDR modeling as well. In this work, customer elasticity for an IBDR program is calculated using data from two national surveys and integrated with a detailed residential load model. There are three important aspects about elasticity estimation in this work. First, the elasticity is specific to the structure of the incentives. Second, an elasticity at the individual appliance level in residential sector is more effective for designing incentives than one for aggregate load of the feeder. Third, if elasticity can be classified based on customers contribution and incentive expectations, then targeted incentives can be developed. All of these factors are novel idea for elasticity estimation. Main motivation behind this study is to show necessity of accurate customer modeling for IBDR programs. Distinction between elasticity of each appliance as well as each customer group could lead to huge difference in results of IBDR programs.