A virtual power plant master-slave game mechanism for flexible trading and energy balance

In today’s power system, the penetration rate of demand - side flexible resources in the distribution network is continuously increasing. However, the lack of coordination in their operation modes can easily lead to problems such as distribution network line congestion and node voltage out - of - limit. To effectively address these issues, this paper proposes a master -slave game mechanism for flexible trading and energy balance, and constructs a master - slave game two - layer scheduling framework with unified clearing of distribution network nodal marginal prices. In this framework, the upper - layer framework aims to minimize the electricity cost of users under the guidance of load aggregators. The load aggregators act as the leaders in the master - slave game, guiding users to participate in flexible trading and optimizing their electricity consumption behavior. The lower - layer framework focuses on maximizing social welfare by the distribution network system operator, who fully considers network power flow safety and voltage out - of - limit. As the follower in the master - slave game, the distribution network system operator conducts system scheduling based on the upper -layer decisions. To solve this master - slave game problem, the Karush - Kuhn - Tucker optimality conditions and the duality theorem are used to cleverly transform the original complex non -linear two - layer problem into a single - layer mixed - integer linear programming problem. Simulation examples are used to verify and analyze the proposed model. The results show that the model can significantly alleviate network congestion, fully demonstrating the crucial role of flexible resources in distribution network congestion management. It provides an innovative and practical solution for achieving flexible trading and energy balance in the distribution network.