A Market-Oriented Trading Method for Integrated Community Energy System Based on Hierarchical Stackelberg Game Method

In response to escalating environmental concerns and the shortage of traditional energy resources, it is essential to enhance energy management within multienergy markets to facilitate the integration of renewable energy sources with end-users. To this end, our research focuses on the optimization of community-level integrated energy systems (CIESs) equipped with combined cooling, heating, and power (CCHP), utilizing a multiagent system (MAS) and a hierarchical Stackelberg game approach. The research begins with the development of an MAS-based optimization framework for game participants, followed by the establishment of a Stackelberg game model where the multienergy seller acts as the leader and the consumer as the follower. The model is thoroughly validated through the formulation and solution of a mixed-integer linear program (MILP)–based multiobjective optimization, which not only demonstrates effective strategies for optimizing power dispatch but also enhances economic returns and ensures fast game convergence. The results significantly validate the approach of maximizing the utilization of clean energy in energy transactions, clarifying the dynamic relationship between price fluctuations and load in the pricing mechanism. These insights are vital for promoting environmental sustainability and conserving resources, proving essential for future energy management practices.