Optimal Configuration of Wind-Photovoltaic-Storage-Electric Vehicle Capacity in Distribution Network Based on Non-Cooperative Game

The optimization of capacity configuration for distribution networks with multiple distributed energy sources is an important aspect of distribution network planning and design. This study focuses on the capacity allocation issues of wind farms, photovoltaic power stations, energy storage, and electric vehicle distribution network systems. Firstly, the system establishes four investors: wind power, photovoltaic, energy storage, and electric vehicles as game participants. Considering the costs of wind and solar energy curtailment and load interruption penalties, an optimization model based on non-cooperative game theory is developed to maximize the profits of each investor. Then, using intelligent optimization algorithms and setting parameters for particle swarm optimization, the capacity allocation for each participant is optimized individually to determine the capacity allocation that maximizes their profits. Finally, typical monthly wind and solar output data along with electric vehicle load power from a specific region are used for case studies on distribution network capacity allocation. The results show that the model can optimize the capacity allocation of the distribution network system in an economical and reasonable manner while ensuring supply reliability, promoting the effective integration and efficient utilization of renewable energy.