Price-based demand response in retail electricity trading with prosumers in homogeneous oligopoly market: A game-theoretical approach

The coordination of energy consumption and pricing strategies in multi-cluster retail electricity markets is essential for achieving efficient power utilization and mitigating peak–valley fluctuations. Even though existing approaches have addressed the coupling among end-users in multi-cluster retail electricity markets, the role of prosumers who possess both consumption and local generation capabilities have not yet been fully incorporated into the modeling framework. This paper investigates the price-based demand response problem in multi-cluster retail electricity markets, aiming to coordinate the energy consumption decisions of prosumers and the retail pricing strategies of utility companies. By adopting a hierarchical game-theoretic framework, we develop a power system trading model that captures the interaction between the retail electricity price and the energy demand of PV-enabled prosumers within each cluster, while also incorporating the impact of shared energy storage. To model the competition among prosumers at the lower layer, in addition to the generation of local energy, we consider a scenario where prosumers are the manufacturing firms who generate homogeneous goods and sell them in an external economic market by electricity. Considering that each firm has different characteristics, a Cournot competition model is formulated, where each prosumer selects its energy consumption as an individual strategy with a linear electricity utilization function. The proposed method improves the overall production capacity of the system, even during peak demand periods, by enabling prosumers to better manage their local generation and storage resources. The existence and uniqueness of both Nash equilibrium and Stackelberg Nash equilibrium are rigorously established for the proposed hierarchical structure, and a distributed algorithm is developed to compute the Stackelberg equilibrium solution. Furthermore, numerical simulations based on a realistic residential retail electricity market demonstrate the effectiveness of the proposed model and algorithm with the ratio of social welfare improvement being 4.80% for a 4-prosumers case.