Non-Cooperative Game-Theoretic Approach for Virtual Power Plants with Diverse Transaction Objectives in Demand Response-Driven Local Energy Market

With the evolution of energy systems towards decentralization and intelligence, Virtual Power Plants (VPPs), as flexible entities aggregating distributed energy resources, have positioned multi-objective collaborative optimization and multi-agent market game mechanisms as a focal point of research. This study constructs a non-cooperative game model for heterogeneous VPP agents driven by demand response (DR), integrating peer-to-peer (P2P) energy interaction scenarios, and establishes a bi-level Stackelberg game framework with the Local Energy Market Operator (LEMO). By employing distributed algorithms to solve for the optimal Nash equilibrium, it ensures that VPPs with diverse objectives achieve their respective optimization goals. Case studies validate the dual advantages of this method in enhancing market efficiency and promoting renewable energy integration.