广东电力2025，Vol.38Issue(6)：30-38,9.DOI:10.3969/j.issn.1007-290X.2025.06.004
基于改进灰狼优化算法的光储微电网经济优化调度
Optimal Dispatch of Photovoltaic and Energy Storage Microgrid Based on Improved Grey Wolf Optimization Algorithm
摘要
Abstract
In view of the problems of uneven population distribution and the tendency to fall into local optima when solving the microgrid optimization scheduling model in grid-connected mode,this study aims to improve the traditional grey wolf optimization(GWO)algorithm.Firstly,a Tent chaotic map is introduced to achieve diverse population initialization,thereby addressing the uneven coverage of the search space caused by random initialization.Secondly,based on the variation characteristics of the cosine function over the interval[0,π/2],a nonlinear convergence factor adjustment strategy is proposed to enhance optimization accuracy by using the balance algorithm having the abilities of global exploration and local exploitation.To address the problem of degradation of the energy storage system(ESS)due to frequent charging and discharging,the corresponding life loss cost is quantified,and an economic optimization scheduling model is established,incorporating photovoltaic maintenance costs,grid interaction costs,and the amortized cost of ESS life loss.The improved GWO algorithm is applied to solve the model and is compared with other optimization algorithms.The simulation results show that compared with traditional timed charging and discharging strategies and conventional energy allocation schemes,the proposed method achieves better economic performance under both sunny and cloudy conditions.It is verified that the improved GWO algorithm enables more flexible and economical operation of AC microgrids in grid-connected mode and provides a novel optimization scheduling strategy that balances both economic efficiency and practical applicability for microgrid systems with a high proportion of renewable energy.关键词
光储微电网/优化调度/收敛因子/灰狼优化算法Key words
photovoltaic and energy storage microgrid/optimal dispatch/convergence factor/grey wolf optimization algorithm分类
信息技术与安全科学引用本文复制引用
张贵辰,田磊,周京华..基于改进灰狼优化算法的光储微电网经济优化调度[J].广东电力,2025,38(6):30-38,9.基金项目
国家重点研发计划项目(2021YFE0103800) （2021YFE0103800）
