计及电动汽车和光伏-储能的微网能量优化管理

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计及电动汽车和光伏-储能的微网能量优化管理

更新时间：2025-08-13

- 计及电动汽车和光伏-储能的微网能量优化管理
- Automation of Electric Power Systems Vol. 39, Issue 9, Pages: 164-171(2015)
- 作者机构：
  
  北京交通大学国家能源主动配电网技术研发中心,北京市,100044
- 作者简介：
- 基金信息：
- DOI：
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- Published：2015
- 稿件说明：
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SU Su. [J]. Automation of electric power systems, 2015, 39(9): 164-171.
DOI：

SU Su. [J]. Automation of electric power systems, 2015, 39(9): 164-171. DOI：

摘要

随着光伏发电和电动汽车的快速发展

电网的安全和经济运行受到了更多的关注

开展关于能量管理问题的研究有助于保证电网的稳定和高效运行。文中针对并网模式下计及电动汽车和光伏-储能的微网能量管理问题

研究了根据电动汽车电池的荷电状态进行能量管理的功率计算模型

提出了兼顾光伏出力、电动汽车充放电功率、电网电价时段划分及储能能量状态的能量管理策略。在此基础上

建立了以电动汽车充放电功率为优化变量

以减少微网运行费用为目标的能量管理模型

并采用基于遗传算法与粒子群算法的混合优化算法(GAPSO)进行求解。最后以实际微网为例进行仿真

结果验证了所述方法的有效性和可行性。

Abstract

With the rapid development of photovoltaic and electric vehicles (EVs)

the security and economical operation of power systems is drawing greater attention

while research on energy management is beneficial to its stable and efficient operation. According to energy management of microgrids considering EVs and photovoltaic (PV)-energy storage in the grid-connected mode

the energy characteristics and the method of power calculation of EVs considering each EV’s state of charge (SOC) are studied first. A strategy with the power of PV and EVs

the period division of time of use price and the SOC of energy storage taken into account is then proposed. On this basis

an energy management model is developed to reduce the operation cost

while the power of EVs is used as optimization variables. The method based on the hybrid genetic algorithm and particle swarm optimization (GAPSO) algorithm is used for solution. Finally

the simulation results of an example show the effectiveness and feasibility of the proposed model. This work is supported by International S&T Cooperation Program of China (No. 2013DFA60930) and Fundamental Research Funds for the Central Universities (No. 2010JBZ002).

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