摘要
电动汽车随机进入充电站进行快速充电,容易造成电网过负荷和不确定性峰荷。为提高电网稳定性,减小随机充电带来的功率波动,提出了充电负荷离散化储能配置模型。将时间上连续的充电负荷曲线离散为等间隔时段的充电序列,电网供电功率上限和储能容量量化为可服务的充电桩个数,在设定的时间内用排队理论描述负荷状态,并以二维离散时间马尔科夫链建立系统负荷状态转移关系,确立单个储能式快速充电站随机充电模型。根据离散化负荷的状态空间和概率分布,进行不同负荷状态下的经济性分析,最后通过算例仿真,在电网供电功率和储能功率的不同配比下,分析电动汽车到达量对服务质量和经济性的影响,验证模型的有效性。
Fast and random charging of electric vehicles(EVs)in the charging station can easily cause the overload and uncertain peak load of the grid.In order to improve the stability of the grid and reduce the power fluctuation caused by random charging,a charging load discrete model for energy storage configuration is proposed.The time-continuous charging load curve is discretized into charging sequences at equal intervals,the power supply cap of the grid and energy storage capacity are quantified to the number of available charging piles,and the load status is described by applying queuing theory within the set time.Then the system load state transition relation is established by applying two-dimensional discrete time Markov chain,thus a random charging model of a single energy storage fast charging station is established.According to the state space and probability distribution of the discretized load,the economics under different load statuses are analyzed.Finally,through the case study,the impact of the EV arrival rate on the service quality and economy is analyzed under different ratios of grid power and energy storage power,so that the feasibility of the model is verified.
作者
何阳
张宇
王育飞
方超明
方陈
薛花
HE Yang;ZHANG Yu;WANG Yufei;FANG Chaoming;FANG Chen;XUE Hua(School of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China;State Grid Shanghai Electric Power Research Institute,Shanghai 200437,China;State Grid Suining Electric Power Supply Company,Suining 629000,China)
出处
《电力科学与技术学报》
CAS
北大核心
2021年第5期72-78,共7页
Journal of Electric Power Science And Technology
基金
国家重点研发计划(2016YFB0101800)
国家电网公司总部科技项目(520940170017)。
关键词
电动汽车
储能配置
快速充电
排队理论
马尔科夫链
electric vehicle
energy storage configuration
fast charging
queuing theory
Markov chain
