Day-ahead Market Optimal Bidding Strategy of Load Aggregator Engaging Demand Response Program Considering Price Uncertainty

In order to help the residential customers participate in the electricity markets, a new entity called load aggregator (LA) is emerged. The load aggregator (LA) bids in the wholesale market to purchase electricity and meet the expected demand of its customers in the retail market. Because of the uncertainty of the wholesale market price (WMP), the LA has to undertake all the risk caused by the price volatility in the wholesale market. Although some existing literatures take the uncertainty of WMP into account, most of them determine a constant energy bid for each trading period regardless of the WMP. To this end, this paper proposes a scenario-based optimal bidding strategy model for the LA that implements the demand response program (DRP), which enables the LA to reduce the risk of profit loss caused by price volatility. Moreover, with the implementation of the DRP, not only can the LA bids in the wholesale market, but also it is able to aggregate the demand response (DR) resources from its customers and provide DR service to the power system operator such as the independent system operator (ISO) or regional transmission organization (RTO). The case study using a dataset from the Thames valley vision (TVV) verifies the effectiveness of the proposed model.