Short-term scheduling of electricity retailers in the presence of Demand Response Aggregators: A two-stage stochastic Bi-Level programming approach

Abstract

This article proposes a novel short-term decision-making model for electricity retailers within the electricity market and in the presence of Demand Response Aggregators (DRA). In this framework, retailers provide their required energy through the Day-ahead market, Real-time market and forward bilateral contracts. On the other hand, retailers participate in demand response (DR) programs based on the DRA’s DR offers to maximize their benefits. In this study, to cope with the uncertainty, the two-stage stochastic programming scheme is utilized. In the first stage, the participation of retailers in the Day-ahead market, as well as power purchased from the forward contracts are decided. In the second stage, the power exchanged with the Real-time market, and the DRA are determined after the realization of stochastic parameters. On the contrary, the DRA enhances its profit through submitting offers to retailers for two DR options. For solving the problem, a strategy based on the Game Theory, the Bi-Level stochastic programming approach is exploited to maximize the profit of both players in a competitive environment. The model is turned into a Single-Level problem by substituting the lower-level with its Karush–Kuhn–Tucker conditions. Finally, merits of the presented method are illustrated in a typical case study.