摘要
微电网是一种将分布式电源集成到电网中的有效方法,微电网的优化运行可以有效提高可再生能源的利用效率。综合考虑微电网运行的经济性、不同时段分布式电源的波动性以及环境保护等多方面约束和要求创建目标优化模型,提出基于改进粒子群优化算法的调度优化方法,通过动态调整权重和认知因子得到最优解,并与遗传算法进行对比。算例分析表明,改进粒子群优化算法收敛速度更快,在解决分布式电源波动性和微电网经济调度优化方面更加合理有效。
Microgrid is an effective method to integrate distributed power supply into power grid.The optimal operation of microgrid can effectively improve the utilization efficiency of renewable energy.The objective optimization model was established,considering the economy of microgrid operation,the volatility of distributed power sources in different periods,environmental protection and other constraints and requirements.The scheduling optimization method based on improved particle swarm optimization(IPSO)algorithm was proposed.The optimal solution was obtained by dynamically adjusting weights and cognitive factors.The IPSO algorithm was compared with genetic algorithm.The analysis of example shows that the IPSO algorithm has faster convergence speed and is more reasonable and effective in solving the volatility of distributed power sources and the optimization of microgrid dispatching.
作者
于新海
王鑫
苏日古格
张晓菊
YU Xinhai;WANG Xin;SU Riguge;ZHANG Xiaoju(Department of Mechanical and Electrical Engineering,Hetao College,Bayannur 015000,Nei Monggol,China;Key Laboratory of Civil Aircraft Airworthiness Technology,Civil Aviation University of China,Tianjin 300300,China;Research and Application Center of Automation,Hetao College,Bayannur 015000,Nei Monggol,China)
出处
《电气传动》
2022年第22期38-43,共6页
Electric Drive
基金
国家自然科学基金(61901162)
内蒙古自治区高等学校科研项目(NJZY20222)
河套学院科学技术研究项目(HYZZ201930)。
关键词
微电网
经济调度
改进粒子群优化算法
遗传算法
microgrid(MG)
economic dispatch
improved particle swarm optimization(IPSO)algorithm
genetic algorithm(GA)