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含光伏分布式电源配电网的电动汽车充电站机会约束规划

ISSN号：1003-8930
期刊名称：《电力系统及其自动化学报》
时间：0
分类：TM76[电气工程—电力系统及自动化]
作者机构：[1]广东电网公司佛山供电局,佛山528000, [2]湖南大学电气与信息工程学院,长沙410082
相关基金：国家自然科学基金资助项目（61102039,51107034）;高等学校博士学科点专项科研基金资助项目（20120161110009）;湖南省自然科学基金资助项目（14JJ7029）;中央高校基金和湖南省教改课题资助项目

关键词：分布式电源, 电动汽车充电站, 选址定容, 多目标优化, 机会约束规划, distributed generation, electric vehicle charging station, optimal site selection and capacity determination, multi-objective optimization, chance-constrained programming

中文摘要：

针对我国某些主要地区的光伏分布式电源与电动汽车充电站的联合利用问题,提出了电动汽车充电站在含光伏分布式电源的配电网中的联合选址规划问题。针对光伏电源出力与充电站负荷的随机性分布,引入机会约束原则,对充电站选址规划的目标函数与约束条件基于置信区间进行相应处理。引入两层级中心选址模型,建立了考虑投资成本、系统有功损耗、交通网络评估指标的多目标函数,在约束条件下选用组合优化问题性能上表现优异的蝙蝠算法对充电站选址模型进行全局寻优,得到优化问题的最优解。通过对IEEE 33节点算例进行仿真计算,体现该理论良好的寻优性能,从而验证其应用在含随机出力光伏分布式电源配电网电动汽车充电站选址规划领域的合理性与有效性。

英文摘要：

Considering the combined utilization of photovoltaic distributed generations （DGs） and electric vehicle charging stations in some key areas in China, a combined programming for the location of electric vehicle charging stations in distribution network containing photovoltaic DGs is put forward. In light of the stochastic distribution of the output of photovoltaic power and the loads of electric vehicle charging stations, a chance-constrained principle is introduced, and the objective function and constraint conditions are processed based on confidence interval. A double-level center location model is introduced to establish a multi-objective function, which considers investment cost, system active loss and traffic network evaluation index. Under constraint conditions, the bat algorithm with a good performance in combinatorial optimization problems is used to perform a global optimization searching of the location model, thus an optimal solution is obtained. The simulation of an IEEE 33-node example indicates a good optimization performance of the proposed method, and verifies the rationality and validity of its applications to the location of electric vehicle charging stations in distribution network containing photovoltaic DGs with stochastic output.

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