| 引用本文: | 吴游龙,韩正庆,刘淑萍.基于GA-PSO的牵引供电系统自愈重构策略研究[J].电力系统保护与控制,2025,53(14):80-89.[点击复制] |
| WU Youlong,HAN Zhengqing,LIU Shuping.Research on self-healing reconfiguration strategy for traction power supply systems based on GA-PSO[J].Power System Protection and Control,2025,53(14):80-89[点击复制] |
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| 摘要: |
| 为提升牵引供电系统在故障工况下的供电恢复能力，针对光储接入的牵引供电系统提出了一种基于遗传算法与二进制粒子群混合算法的自愈重构恢复方法。首先，利用图论方法构建了系统的节点边等效模型，结合铁路故障应急处置原则，考虑系统相关拓扑和潮流约束条件，以恢复节点数最多和开关操作费用最少为目标建立了自愈重构目标函数。然后，使用广度优先搜索算法缩短个体编码长度，并引入混沌映射实现种群初始化，增加初始种群的均匀性和多样性，并对算法的部分参数进行了改进。最后，运用改进的混合算法求解了牵引供电系统典型故障工况下的自愈重构方案，并与其他算法进行对比验证。算例结果表明，所提方法具有良好的收敛速度与寻优能力，提高了牵引供电系统的故障恢复能力。 |
| 关键词: 牵引供电系统 拓扑分析 自愈重构 混合算法 |
| DOI：10.19783/j.cnki.pspc.241400 |
| 投稿时间：2024-10-21修订日期：2024-11-19 |
| 基金项目:国家自然科学基金项目资助(52177116)；国家重点研发计划项目资助(2021YFB2601500) |
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| Research on self-healing reconfiguration strategy for traction power supply systems based on GA-PSO |
| WU Youlong,HAN Zhengqing,LIU Shuping |
| (School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China) |
| Abstract: |
| To enhance the power restoration capability of traction power supply systems under fault conditions, a self-healing reconfiguration and recovery strategy based on a hybrid genetic algorithm and binary particle swarm optimization (GA-PSO) is proposed for traction power supply systems integrated with photovoltaic and energy storage. First, a node-edge equivalent model of the system is established using graph theory. In accordance with the principles of railway fault emergency handling and considering system topology and power flow constraints, a self-healing reconfiguration objective function is formulated with the aims of maximizing the number of restored nodes and minimizing switch operation costs. Subsequently, the breadth-first search algorithm is used to reduce the individual encoding length, and chaotic mapping is introduced for population initialization to enhance the uniformity and diversity of the initial population. And some parameters of the algorithm are improved. Finally, the improved hybrid algorithm is used to solve the self-healing reconfiguration schemes for typical fault conditions in traction power supply systems, and comparisons with other algorithms are made for validation. The case study results indicate that the proposed method achieves excellent convergence speed and optimization capability, significantly improving the fault recovery ability of the traction power supply system. |
| Key words: traction power supply system topological analysis self-healing reconfiguration hybrid algorithm |
