工作场所光伏电动汽车充电站可行性研究
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摘要
基于某工厂员工的电动汽车使用数据,分析了员工上下班出行行为及电动汽车电量分布情况,使用蒙特卡洛模拟方法仿真了100辆电动汽车的出行及充电行为.设计搭建了光伏电动汽车充电站仿真平台用于对电站进行评估分析.基于仿真数据,使用粒子群算法对工作场所建设电站进行了系统方案设计和可行性研究.结果表明,模拟数据能很好地描述员工出行和充电行为,设计的光伏充电站系统能够基本满足员工充电需求,从而促进工厂的可持续化发展并节约成本.
Based on the electric vehicle usage data of factory employees,we analyze the employees' commute behavior and the distribution of vehicles' state of charge,and simulate the commute and charging behavior of 100 electric vehicles using Monte Carlo simulation method. A photovoltaic charging station simulation platform is designed to evaluate and analyze the station.Based on the simulation data,the feasibility and system design for photovoltaic EV charging station in the workplace are detailed analyzed and designed by using particle swarm optimization method. The results show that the simulation data can well describe the employees' travel and charging behavior. The designed photovoltaic charging station system can basically meet the charging demand,so as to promote the sustainable development of the factory and save cost.
Based on the electric vehicle usage data of factory employees,we analyze the employees' commute behavior and the distribution of vehicles' state of charge,and simulate the commute and charging behavior of 100 electric vehicles using Monte Carlo simulation method. A photovoltaic charging station simulation platform is designed to evaluate and analyze the station.Based on the simulation data,the feasibility and system design for photovoltaic EV charging station in the workplace are detailed analyzed and designed by using particle swarm optimization method. The results show that the simulation data can well describe the employees' travel and charging behavior. The designed photovoltaic charging station system can basically meet the charging demand,so as to promote the sustainable development of the factory and save cost.
引文
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[2] Schey S L,Smart J G,Scoffield D R. A first look at the impact of electric vehicle charging on the electric grid in the EV project[R]. Idaho Falls:Idaho National Laboratory(INL),2012.
[3]许健,刘念,于雷,等.计及重要负荷的工业光伏微电网储能优化配置[J].电力系统保护与控制,2016,44(9):29-37.(Xu Jian,Liu Nian,Yu Lei, et al. Optimal allocation of energy storage system of PV microgrid for industries considering important load[J]. Journal of Power System Protection and Control, 2016, 44(9):29-37.)
[4] Jones L E. Renewable energy integration:practical management of variability,uncertainty, and flexibility in power grids[M]. Cambridge:Academic Press,2017.
[5]刘东奇,王耀南,袁小芳.电动汽车充放电与风力/火力发电系统的协同优化运行[J].电工技术学报,2017,32(3):18-26.(Liu Dong-qi,Wang Yao-nan,Yuan Xiao-fang,et al.Cooperative dispatch of large-scale electric vehicles with windthermal power generating system[J]. Transactions of China Electro-technical Society,2017,32(3):18-26.)
[6]李洪美,崔翰韬,万秋兰.考虑电动汽车充电策略的配网重构二阶锥规划模型[J].中国电机工程学报,2015,35(18):4674-4681.(Li Hong-mei,Cui Han-tao,Wan Qiu-lan. Distribution network reconfiguration based on second-order conic programming considering EV charging strategy[J]. Proceedings of the CSEE,2015,35(18):4674-4681.)
[7] Hu J,Morais H,Sousa T,et al. Electric vehicle fleet management in smart grids:a review of services,optimization and control aspects[J]. Renewable and Sustainable Energy Reviews,2016,56:1207-1226.
[8] Meteonorm Software[EB/OL].(2018-05-01)[2018-05-10]. http://www. meteonorm. com/.
[9] King D L,Boyson W E,Kratochvil J A. Photovoltaic array performance model[R]. Washington,DC:Department of Energy,2004.
[10] Go Solar California. PV modules[EB/OL].(2018-05-01)[2018-05-10]. http://www. gosolarcalifornia. ca. gov/equipment/pv_modules. php.
[11] Orosz M S,Quoilin S,Hemond H. Technologies for heating,cooling and powering rural health facilities in sub-Saharan Africa[J]. Proceedings of the Institution of Mechanical Engineers,Part A:Journal of Power and Energy,2013,227(7):717-726.
[12] Ekren O,Ekren B Y. Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing[J]. Applied Energy,2010, 87(2):592-598.
[13] Kennedy J,Eberhart R. Particle swarm optimization[C]//Proceedings of the IEEE International Conference on Neural Networks. Perth, 1995:1942-1948.