中国电力 ›› 2017, Vol. 50 ›› Issue (3): 161-167.DOI: 10.11930/j.issn.1004-9649.2017.03.161.07

• 新能源 • 上一篇    下一篇

考虑电动汽车的微电网复合储能容量优化配置

王帅, 赵兴勇, 贺天云, 刘健   

  1. 山西大学 电力工程系,山西 太原 030013
  • 收稿日期:2016-08-20 出版日期:2017-03-20 发布日期:2017-03-17
  • 作者简介:王帅(1990—),男,山西运城人,硕士研究生,从事智能微电网运行与控制以及电动汽车方面的研究。E-mail:617941253@qq.com
  • 基金资助:
    山西省“十二五”科技重大专项(2060901); 国网山西省电力公司科技项目(05161A)

Hybrid Energy Storage Capacity Configuration Optimization in Micro Grids Considering Electric Vehicles

WANG Shuai, ZHAO Xingyong, HE Tianyun, LIU Jian   

  1. Department of Electric Power Engineering, Shanxi University, Taiyuan 030013, China
  • Received:2016-08-20 Online:2017-03-20 Published:2017-03-17
  • Supported by:
    This work is supported by the 12th Five-year Plan of Shanxi for Major Science and Technology Projects (No.2060901) and Science and Technology Project of SXEBC (No.05161A)

摘要: 复合储能在微电网功率平衡、平抑可再生能源波动、提高电池使用寿命等方面有着显著作用,是未来微电网储能发展方向之一。针对含有风力发电和光伏发电的微电网,考虑微电网中电动汽车有序充放电,建立复合储能容量优化模型。通过经验模态分解分割平抑任务,最后利用粒子群优化算法对所搭建模型进行求解。比较无电动汽车、电动汽车随机充电和有序充放电3种模式下的容量优化配置结果。通过搭建仿真,对有序充放电模式下复合储能的功率分解以及荷电状态进行分析,验证了该方法在平抑波动方面的有效性。

关键词: 复合储能, 经验模态分解, 粒子群优化算法, 电动汽车, 微电网, 风力发电, 光伏发电

Abstract: Hybrid energy storage has significant effect in micro grid power balance, renewable energy fluctuation suppression and battery life improvement. It is one of the future development directions of energy storage in micro power grid. An optimization model of energy storage capacity is established for micro power grid containing wind power and photovoltaic power generation with consideration of coordinated charging/discharging of electric vehicle. Empirical Mode Decomposition(EDM) is used to split and stabilize charging/discharging task. The model is finally solved by Particle Swarm Optimization method(PSO). The capacity configuration is compared under different modes including no electric vehicles, uncoordinated charging and coordinated charging/discharging. The state of charge and power distribution of hybrid energy storage are analyzed through simulation. The simulation result verifies effectiveness of proposed model in energy fluctuation suppression.

Key words: hybrid energy storage, empirical mode decomposition, particle swarm optimization algorithm, EV, micro-grid

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