湖北电力2024，Vol.48Issue(5)：8-14,7.DOI:10.19308/j.hep.2024.05.002
基于改进多目标粒子群算法的分布式电源集群优化调度研究
Research on Optimal Scheduling of Distributed Generation Cluster Based on Improved Multi-Objective Particle Swarm Algorithm
摘要
Abstract
With the increasingly serious problems of energy shortage and environmental pollution,the introduction of clean energy has become an important trend in the research and development of distributed generation cluster.In order to achieve the coordinated and optimized operation of distributed power clusters in terms of economic performance and environmental benefits,and for the grid-connected distributed power cluster including photovoltaic generator set,wind generator set,energy storage system and diesel generator set,a multi-objective optimal scheduling model with the lowest operation and maintenance cost and environmental protection cost is established.The model is solved by using improved multi-objective particle swarm optimization(PSO)to simulate agricultural and rural scenarios.The volatility and intermittency characteristics of wind power and photoelectric power is fully considered;the capacity of wind turbine,photovoltaic generator and energy storage device is rationally optimized,and simulation results are analyzed to verify the feasibility of optimal configuration and scheduling.The simulation and optimization results provide a reference for the study of the optimal operation of the multi-objective distributed power cluster,and also provide a reference for the study of the optimal allocation and scheduling of the wind-wind storage capacity of the economy and environmental protection.关键词
分布式电源集群/优化调度/改进粒子群算法/风力发电机组/储能系统/清洁能源Key words
distributed generation cluster/optimal scheduling/improved particle swarm optimization algorithm/wind turbine/energy storage system/clean energy分类
信息技术与安全科学引用本文复制引用
刘江东,朱健,孔伯骏,王升波,王乐,丰颖..基于改进多目标粒子群算法的分布式电源集群优化调度研究[J].湖北电力,2024,48(5):8-14,7.基金项目
国网江苏省电力有限公司科技项目(项目编号:J2022119). （项目编号:J2022119）
