Profit Allocation for Virtual Power Plants Based on Adaptive Optimization Algorithm and Game Theory

The operation and management of Virtual Power Plants (VPPs) require effective strategies for profit allocation and trading optimization to ensure fairness among participants and maximize overall profitability. This paper proposes a novel algorithm that integrates cooperative game theory with optimization techniques to address these challenges. The cooperative game theory framework ensures equitable profit distribution among participants based on their contributions to the VPP, while the trading optimization algorithm maximizes revenue by dynamically responding to market conditions and operational constraints. A Shapley value-based approach is employed to allocate profits fairly, reflecting each participant's marginal contribution. Experimental results demonstrate that the proposed method enhances participant satisfaction, ensures fairness in profit distribution, and significantly improves the economic performance of the VPP. This study provides a robust foundation for the sustainable operation of VPPs in dynamic and competitive electricity markets.