分时电价下电动汽车参与虚拟电厂的经济优化调度方法  

Economic optimization scheduling method of electric vehicle participating in virtual power plant under time-of-use price

作　　者：王世谦 贾一博 白宏坤 王圆圆 华远鹏 卜飞飞 杨平[2] WANG Shiqian;JIA Yibo;BAI Hongkun;WANG Yuanyuan;HUA Yuanpeng;BU Feifei;YANG Ping(Economic Technology Research Institute,State Grid Henan Electric Power Company,Zhengzhou 450052,China;School of Electrical Engineering,Southwest Jiaotong University,Chengdu 611756,China)

机构地区：[1]国网河南省电力公司经济技术研究院,郑州450052 [2]西南交通大学电气工程学院,成都611756

出　　处：《电力需求侧管理》2023年第5期19-26,共8页Power Demand Side Management

基　　金：国网河南省电力公司科研项目(5217L0220007)。

摘　　要：随着物联网以及智慧电网的迅速发展,供需平衡中需求侧资源的作用逐渐增大。然而,大量无序应用需求响应技术会对配电网的运行可靠性产生影响。针对此类问题,提出了电动汽车基线负荷预测与负荷削减、负荷转移两种激励型需求响应策略相结合的虚拟电厂经济优化调度方法。首先,根据历史数据采用三次指数平滑法完成风/光电站出力及电动汽车基线负荷的数据预测,观测电力用户的可调能力;然后,基于分时电价机制以虚拟电厂经济最优为目标,增加功率平衡、风/光新能源预测出力和储能系统运行成本等系统约束条件,建立虚拟电厂经济最优调度模型;最后,以河南郑州某地5个电动汽车充电站和风光电站等实际数据验证所提出方法的精准性和有效性。With the rapid development of IoT and smart grid,the role of demand-side resources in supply-demand balance is gradually increasing.However,a large number of disorderly applications of demand response techniques can affect the reliability of distribution networks.To address such problems,a virtual power plant economic optimal scheduling method combining baseline load forecasting with load reduction and load transfer is proposed.Firstly,based on the historical data,the output of wind/optical power station and the baseline load of electric vehicles are forecasted by using the triple exponential smoothing method,and the adjustable capacity of power users is observed.Then,based on the time-sharing tariff mechanism with the objective of virtual power plant economic optimum,system constraints such as power balance,wind/light new energy forecast output and energy storage system operation cost are added to establish the electric virtual.Finally,the accuracy and effectiveness of the proposed method are verified by the actual data of 5 centralized charging stations and wind power stations in Zhengzhou,Henan Province.

关 键 词：电动汽车 虚拟电厂 负荷预测 需求响应技术 经济最优调度 

分 类 号：TK018[动力工程及工程热物理] F407[经济管理—产业经济]