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1.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
2.国网北京市电力公司电力科学研究院,北京市 100076
3.国网冀北电力有限公司计量中心,北京市 102208
Received:02 March 2021,
Revised:2021-06-07,
Published Online:30 July 2021,
Published:25 October 2021
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石锦凯,鲍谚,陈振等.计及充电负荷不确定性的充电站储能鲁棒优化配置方法[J].电力系统自动化,2021,45(20):49-58.
SHI Jinkai,BAO Yan,CHEN Zhen,et al.Robust Optimization Configuration Method of Energy Storage for Charging Stations Considering Charging Load Uncertainty[J].Automation of Electric Power Systems,2021,45(20):49-58.
石锦凯,鲍谚,陈振等.计及充电负荷不确定性的充电站储能鲁棒优化配置方法[J].电力系统自动化,2021,45(20):49-58. DOI: 10.7500/AEPS20210302005.
SHI Jinkai,BAO Yan,CHEN Zhen,et al.Robust Optimization Configuration Method of Energy Storage for Charging Stations Considering Charging Load Uncertainty[J].Automation of Electric Power Systems,2021,45(20):49-58. DOI: 10.7500/AEPS20210302005.
针对充电站充电负荷的波动性和不确定性特点,提出了计及充电负荷不确定性的充电站储能鲁棒优化配置方法。首先
建立了多面体不确定集描述电动汽车充电负荷的波动性与不确定性。随后
建立了储能系统容量优化配置模型,同时,在优化配置模型中利用储能电池可变寿命模型,实现多约束条件下的储能系统综合成本最小化,使得充电站可以在增加较少综合成本的情况下应对负荷的随机波动。最后
基于鲁棒优化理论实现不确定模型从随机参数到确定性参数模型的转换,结合网格自适应直接搜索算法得到储能系统最佳配置参数。算例通过与确定性算法的对比,验证了所提方法的可行性。
Aiming at the characteristics of the fluctuation and uncertainty of the charging load in the charging station
a robust optimization configuration method for energy storage of the charging station considering the charging load uncertainty is proposed. Firstly
a polyhedral uncertain set is established to describe the fluctuation and uncertainty of charging load of electric vehicles. Then
the optimal configuration model of energy storage system capacity is established. At the same time
the variable life model of the energy storage battery is used in the optimal configuration model to minimize the comprehensive cost of the energy storage system under multiple constraints
so that the charging station can cope with the random fluctuation of load with less comprehensive cost. Finally
based on the robust optimization theory
the uncertain model is transformed from the stochastic parameter optimization model to the deterministic parameter model
and the optimal configuration parameters of the energy storage system are obtained by combining the mesh adaptive direct search algorithm. Compared with the deterministic algorithm
the feasibility of the proposed method is verified by a case.
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