极端灾害情况下虚拟电厂调度优化研究OA

The article focuses on the extreme and persistent high-temperature weather in Chengdu and studies the optimal scheduling problem of virtual power plants under extreme disaster conditions.By aggregating distributed power sources,energy storage,and load resources,a multi-objective optimization scheduling model is constructed,which is solved using an improved particle swarm optimization algorithm.The model comprehensively considers cost,energy efficiency,and grid stability,introducing dynamic parameter adjustment and density analysis to enhance the algorithm's global search and convergence performance.The results show that the optimized scheduling scheme can effectively reduce operating costs,improve energy utilization,and significantly enhance voltage and frequency stability under extreme high temperatures.This study provides a reference for intelligent scheduling and emergency response of virtual power plants under extreme weather conditions.