含光-储-充的微电网日前经济调度方法研究  

Research On The Day-ahead Economic Dispatch Method of Microgrid Including Solar-ESS-EV

作　　者：郭杉[1] 郭洋[1] 刘小恺 董文娟[1] GUO Shan;GUO Yang;LIU Xiaokai;DONG Wenjuan(Inner Mongolia Power Research Institute,Hohhot 010020,China)

机构地区：[1]内蒙古电力科学研究院,内蒙古呼和浩特010020

出　　处：《山东电力技术》2025年第3期1-11,共11页Shandong Electric Power

基　　金：内蒙古“双碳”科技创新重大示范工程“揭榜挂帅”项目(2022JBGS0043)。

摘　　要：为提高微电网的供电可靠率和能源利用率,提出一种计及分时电价的日前经济优化调度方法。首先建立光伏、储能(energy storage system,ESS)、电动汽车(electric vehicles,EV)等主体的功率或能量模型,然后分别采用光伏功率模型及双向长短期记忆(bidirectional long short term memory,Bi-LSTM)模型预测日内光伏及常规负荷功率。结合EV的柔性负荷特性,以最小化系统运维总成本(包括设备运维成本、外网取电成本、储能电池衰减成本等)及EV充电成本建立目标函数。考虑优化问题的多目标、高维特性,选用线性规划求解器求解目标函数。最后选取含光-储-充的某工业园区微电网2021年全年的历史运行数据,首先测试了本文提出的常规负荷及光伏功率预测模型,进而根据光伏出力与常规负荷的匹配差异,选取4种典型日场景测试本文提出的调控算法。结果证明所提功率预测模型及经济调度算法的有效性。In order to improve the power supply reliability and energy utilization rate of microgrids,a day-ahead economic optimization scheduling method considering time-of-use electricity prices is proposed.First,the power or energy model of photovoltaic,energy storage system(ESS),electric vehicles(EV)and other entities is established,and then the photovoltaic power model and Bi-LSTM model are used to predict the photovoltaic and conventional load power during the day,respectively.Combined with the flexible load characteristics of electric vehicles,the objective function is established to minimize the total system operation and maintenance cost(including equipment operation and maintenance cost,external network power cost,energy storage battery attenuation cost,etc.)and the charging cost of electric vehicles.Considering the multi-objective and high-dimensional characteristics of the optimization problem,a linear programming solver is used to solve the objective function.Finally,the historical operational data of a microgrid in an industrial park with solar-ESS-EV for the whole year of 2021 is selected,and the conventional load and photovoltaic power prediction model proposed in this paper is first tested.Then,according to the matching difference between photovoltaic output and conventional load,four typical daily scenarios are selected to test the control algorithm proposed in this paper.The results prove the effectiveness of the power prediction model and economic scheduling algorithm in this paper.

关 键 词：微电网 分时电价 经济调度 柔性负荷 线性规划 

分 类 号：TM74[电气工程—电力系统及自动化]