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1.电力系统广域测量与控制四川省重点实验室(电子科技大学),四川省成都市 611731
2.西南科技大学信息工程学院,四川省绵阳市 621010
Received:21 August 2023,
Revised:2024-01-03,
Published Online:09 April 2024,
Published:25 July 2024
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YI Jianbo,HU Meng,WANG Zeyu,et al.Multi-objective Optimal Configuration Strategy for Improving Operation Efficiency of Photovoltaic Energy Storage Charging Stations[J].Automation of Electric Power Systems,2024,48(14):100-109.
易建波,胡猛,王泽宇等.提升光储充电站运行效率的多目标优化配置策略[J].电力系统自动化,2024,48(14):100-109. DOI: 10.7500/AEPS20230821005.
YI Jianbo,HU Meng,WANG Zeyu,et al.Multi-objective Optimal Configuration Strategy for Improving Operation Efficiency of Photovoltaic Energy Storage Charging Stations[J].Automation of Electric Power Systems,2024,48(14):100-109. DOI: 10.7500/AEPS20230821005.
光储充电站的运行效率直接影响到其经济效益及电网侧的电能质量。针对在进行容量配置时对运行效率考虑不足会导致非必要的电能损耗,文中提出一种提升光储充电站运行效率的多目标优化配置策略。通过分析光储充电站变换器与内源线路功率损耗对于运行效率的影响,提出充电站的运行效率评估指标与计算方法,并讨论光储充电站运行效率对其容量配置的影响。建立以充电站经济效益、运行效率、电网侧峰谷供电功率补偿能力最佳为优化目标的多目标容量优化配置策略。针对优化目标特性,提出一种改进二代非支配排序遗传算法得到优化策略求解方法。选取中国西南地区某典型光储充电站运营场景,通过算例验证了优化策略的有效性与优越性。
The economic benefits and grid-side power quality of photovoltaic energy storage charging stations are directly affected by their operation efficiency. As insufficient consideration of operation efficiency during the capacity configuration can lead to unnecessary power losses
this paper proposes a multi-objective optimal configuration strategy for improving the operation efficiency of photovoltaic energy storage charging stations. By analyzing the impact of power losses of both the converter and the internal source line on the operation efficiency of the photovoltaic energy storage charging stations
this paper proposes evaluation indicators and calculation methods for the operation efficiency of charging stations
and discusses the impact of operation efficiency of photovoltaic energy storage charging stations on their capacity configuration. A multi-objective optimal capacity configuration strategy is established with the optimal economic benefits of charging stations
operation efficiency
and grid-side peak-valley power compensation capacity as the optimization objectives. Aiming at the characteristics of the optimization objectives
an improved non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) is proposed to obtain the solution method for the optimization strategy. The effectiveness and superiority of the optimization strategy are verified through a case study on operation scenarios of a typical photovoltaic energy storage charging station in southwest China.
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