基于粒子群优化算法的智慧微电网风光储容量优化配置

Optimal allocation of a wind‒PV‒battery hybrid system in smart microgrid based on particle swarm optimization algorithm

随着“双碳”目标的提出,国内多地鼓励建筑屋顶建设清洁能源发电系统,由风光储组成微电网,通过新能源发电有效降低区域生产活动的碳排放,并提高生活办公区的供电可靠性。针对微电网投资的经济性,其风光储容量配比一直属于研究热点。依托海南省特有的地理环境,根据当地的光照、风速条件,利用粒子群优化算法,以最大经济效益为寻优目标,选取最优风光储装机容量配比,并利用节能办公住宅区智能微电网建设示范项目所采集的数据进行经济性分析,可以为智能微电网节能改造提供理论和数据基础。

With the proposal of the goals of carbon peaking and carbon neutrality,constructing clean energy generators on roof tops is widely recommended in different regions of China.The microgrid consisting of wind power,photovoltaic power and energy storage devices,can reduce carbon emissions from regional production activities through new energy generation,and improve the power supply reliability of living and office areas.To optimize the return of the investment on microgrid,the ratio of wind power,photovoltaic power and energy storage capacity of a hybrid system has been the focus of researches.According to the light condition,wind speed and other unique geographical features in Hainan Province,the optimal allocation of a wind‒PV‒battery hybrid system in smart microgrid is calculated by particle swarm optimization algorithm.Data collected from the living and office areas of the smart microgrid demonstrative project are used in an economic analysis,which provide theoretical basis and data resources for the further energy efficiency retrofit of smart microgrids.