Incorporation of Survey-based Data into an Aggregation Algorithm for Residential Demand Response

Survey-based data of three home appliances are included in a residential demand response (DR) aggregation algorithm that performs resource re-allocation for peak demand reduction in a notional electric distribution system. In addition, new constraints are integrated into the resource allocation approach to alleviate the inconvenience of the participating customers due to rescheduling their home appliances. Our effort replaces some assumptions from prior work on the mathematical model of customer preferences with actual data from a survey to validate the prior work. The results confirm the feasibility of the DR aggregation approach in achieving profits for the aggregator while considering the comfort of the participating customers.