首页> 外文会议>International Conference on Advanced Electronic Materials, Computers and Software Engineering >Research on Scheduling Strategy of Electric Vehicle Fast Charging Station Combined with Photovoltaic Generation and Energy Storage
【24h】

Research on Scheduling Strategy of Electric Vehicle Fast Charging Station Combined with Photovoltaic Generation and Energy Storage

机译:电动汽车快速充电站调度策略与光伏发电和储能储存

获取原文

摘要

The random fluctuation of photovoltaic(PV) generation and the random charging load of electric vehicles(EVs) will have a great impact on the power grid. It is an effective scheme to equip the fast charging station with photovoltaic and Energy Storage System(ESS), which has the advantage of suppressing the fluctuation of the power grid and absorbing the renewable energy. To solve the problem of energy management in Fast Charging Stations(FCS), a power prediction model based on EV charging behavior and PV data is studied, and a multi-objective optimization mathematical model is established considering the economic benefit of charging stations and the smooth load fluctuation, a dynamic ESS charging and discharging power constraint strategy considering both charging load and real-time electricity price is proposed, which is solved by Multi-Objective Particle Swarm Optimization(MOPSO) algorithm with mutation links based on grid sorting. The simulation results show that compared with the conventional charging station scheme, the scheme can improve the economic performance, improve the use of new efficient energy, and effectively reduce the impact of the original charging load on the peak load of distribution network, to reduce grid fluctuations.
机译:光伏(PV)生成的随机波动和电动车辆(EVS)的随机充电负荷对电网产生很大影响。它是装备具有光伏和能量存储系统(ESS)的快速充电站的有效方案,其具有抑制电网的波动和吸收可再生能量的优点。为了解决快速充电站(FCS)中的能量管理问题,研究了基于EV充电行为和PV数据的功率预测模型,考虑到充电站的经济效益和平滑的多目标优化数学模型提出了考虑充电负荷和实时电价的动态ES充电和放电功率约束策略,通过多目标粒子群优化(MOPSO)算法解决了基于网格分类的突变链路解决。仿真结果表明,与传统的充电站方案相比,该方案可以提高经济性能,改善新的高效能量,有效地降低原始充电负荷对分销网络峰值负荷的影响,减少网格波动。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号