摘要
“双碳”背景下,光储充一体站不仅能够缓解大量电动汽车充电对电网带来的冲击,而且能够利用新能源减少二氧化碳排放,逐渐成为未来电动汽车充电站的一种主流形式。为使光储充一体站在满足负荷需求的前提下减少碳排放,并且获取最优的运行经济性,提出一种考虑碳排放的光储充一体站日前运行策略。首先,通过数据-模型混合驱动的方式进行场景生成,采用改进的kernelk-means算法对历史数据进行聚类,进而生成光伏出力场景,并通过变分自编码器生成负荷场景。然后,建立以购电成本、碳排放成本、容量电费等为目标函数的日前经济运行策略的数学模型。最后,基于北京地区某光储充一体站的历史运营数据开展算例分析,对比结果表明,光储充一体站使用所提日前策略能够获得更高的经济效益,验证了所提策略的有效性。
Given a background of"dual carbon",an integrated photovoltaic storage and charging station(IPSCS)can not only alleviate the impact of a large number of electric vehicles charging on the grid,but also can use new energy to reduce carbon dioxide emissions.It is gradually becoming a mainstream form of electric vehicle charging station.In order to reduce carbon emissions and obtain the optimal operating economy of the IPSCS while meeting load demand,a day-ahead operation strategy of the IPSCS considering carbon emissions is proposed.First,a scene generation is made in a data-model hybrid manner,and the improved kernel k-means algorithm is used to cluster historical data.This in turn generates photovoltaic power scenarios.The load scene is generated by a variational autoencoder.Then,a mathematical model of day-ahead economic operation strategy with the objective function of power purchase cost,carbon emission cost,and capacity electricity fee is established.Finally,based on the historical operating data of an IPSCS in the Beijing area,the results show that the IPSCS uses the above-mentioned day-earlier strategy to obtain higher benefits and verify the validity of the strategy.
作者
薛贵挺
汪柳君
刘哲
刘长江
陈涵冰
孙伟卿
XUE Guiting;WANG Liujun;LIU Zhe;LIU Changjiang;CHEN Hanbing;SUN Weiqing(State Grid Beijing Haidian Electric Power Supply Company,Beijing 100195,China;School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2022年第7期103-110,共8页
Power System Protection and Control
基金
国家自然科学基金项目资助(51777126)
国网北京市电力公司科技项目资助(520204200068)。
关键词
电动汽车
光储充一体站
碳排放
数据-模型混合驱动
日前运行策略
electric vehicle
photovoltaic storage and charging station
carbon emission
hybrid data and model driven
day-ahead operation strategy