可再生能源2023，Vol.41Issue(12)：1579-1586,8.
基于MGWO-SD模型的户用光伏装机容量预测研究
Research on installed capacity forecast of household PVs based on MGWO-SD model
摘要
Abstract
This paper analyzes the influencing factors of the development of household photovoltaic(PV)installed capacity,and establishes a forecast model based on the improved gray wolf optimizer(MGWO)combined with the system dynamics(SD)model.Firstly,various factors that affect the growth of household PV installed capacity are analyzed.Based on the SD theory,a prediction model of household PV installed capacity is built.Then,in order to optimize the parameters in the model,the linearly reduced convergence factor in the traditional Grey Wolf optimizer(GWO)is changed into nonlinear parameter,and finally a prediction model based on MGWO-SD model is established.The prediction results show that the prediction model proposed in this paper is more accurate than other prediction methods,and the average absolute percentage error and root mean square error are smaller.Moreover,the MGWO proposed in this paper can reach the convergence faster than GWO.The accurate forecast of household PV installed capacity is also helpful for the power grid to build a new power system scientifically and orderly under the background of'double carbon',which has certain theoretical and practical value.关键词
光伏装机容量/预测模型/系统动力学/改进灰狼优化算法Key words
photovoltaic installed capacity/forecast model/system dynamics/modified gray wolf optimizer分类
能源科技引用本文复制引用
孙乐平,郭小璇,李景顺,刘朋超,杨小林..基于MGWO-SD模型的户用光伏装机容量预测研究[J].可再生能源,2023,41(12):1579-1586,8.基金项目
国家自然科学基金(52107177). （52107177）
