Day-ahead Market Decision of Load Aggregator Considering Response Uncertainty

Aiming at the problem that load aggregator (LA) faces greater risk when participating in day-ahead market demand response(DR) due to uncertainty of user response, a day-ahead market decision model of LA considering the uncertainty of response is proposed in this paper. The basic process of LA participating in the day-ahead DR is described in this paper. A DR model considering the uncertainty of response is constructed. Conditional value at risk (CVaR) is used as measurement indexes of decision risk. A benefit-risk portfolio decision model of LA is constructed, and the adaptive particle swarm optimization embedded in Latin hypercube sampling is used to solve the model. The effects of risk preference and response reliability on the benefits and risk losses of LA are discussed. The validity and rationality of the model are verified by an example, which provides a theoretical reference for LA to participate in the operational decision-making of the day-ahead market DR.