Two-stage Joint Bidding and Pricing Optimization Strategy for Load Aggregators in Demand Response Market

Abstract

Load aggregators (LA) can incentivize residential consumers to participate in demand response programs and provide grid services through market-based transactions. However, existing researches on market bidding and pricing strategies for load aggregators are often performed separately without considering the coupling between them, which may lead to suboptimal profits. To address this issue, we propose a two-stage joint bidding and pricing strategy that takes into account the coupling relationship between bidding and pricing. In the first stage, a pricing plan is set to predict the response capacity of consumers and formulate a bidding strategy accordingly. In the second stage, the actual bidding results and market-clearing price are obtained, and the pricing plan is optimized accordingly. The proposed strategy is evaluated using real-world bidding data from the California DR market. The results show that the two-stage pricing strategy can significantly increase the profit of LAs compared to the traditional one-stage strategy. Additionally, we employ robust optimization to analyze uncertainty in the DR market. The proposed pricing strategy can provide valuable insights for LAs to participate in the DR market effectively and efficiently.