基于H-WOA-GWO和区段修正策略的配电网故障定位研究

doi:10.16088/j.issn.1001-6600.2024042401

摘要/Abstract

摘要： 分布式电源的并网和逐渐扩大的配电网规模使得传统故障定位方法难度增大。针对这一问题,本文提出一种多策略改进的混合鲸鱼灰狼优化算法(H-WOA-GWO)结合区段修正的故障定位方法。首先将WOA包围收缩和螺旋更新机制融入GWO,构建混合算法来有效改善收敛速度;然后运用非线性收敛因子、改进领导狼位置和自适应狩猎权重来增强搜索自适应性、全局开发能力和缩短迭代时间。建立不同定位模型选择基于评价函数值法构建目标函数,通过分析伪最优解潜在信息提出区段修正策略。经仿真验证,三重故障下:混合算法正确率高于单一算法11个百分点,迭代时间可节约0.326 7 s;结合区段修正策略后正确率和求解时间较单纯混合算法分别提高17个百分点和74.88%,表明改进混合算法和修正策略可准确识别多重和多畸变节点故障,具备高效的求解速度和稳定性。

关键词: 灰狼优化算法, 鲸鱼优化算法, 容错性, 分布式电源, 故障定位

Abstract: The grid-connection of distributed generations and the gradually expanding scale of distribution networks make the traditional fault location methods more difficult. A multi-strategy improved Hybrid Whale Optimization Algorithm Gray Wolf Optimization (H-WOA-GWO) combined with region correction fault location method is proposed to address this problem. Firstly, the WOA encircling contraction and spiral updating mechanisms are integrated into GWO to construct a hybrid algorithm to effectively improve the convergence speed; then the nonlinear convergence factor, improved leader wolf position and adaptive hunting weights are applied to enhance the search adaptability, global development capability and shorten the iteration time. Different location models are established to choose in constructing the objective function based on the evaluation function value method, and the region correction strategy is proposed by analyzing the potential information of the pseudo-optimal solution. After simulation verification, under triple faults: the correct rate of hybrid algorithm is 11 percentage points centa higher than that of single algorithm, and the iteration time can be saved by 0.326 7 s; the correct rate and solution time after combining with the region correction strategy are improved by 17 percentage points and 74.88%, respectively, compared with that of pure hybrid algorithm. It shows that the proposed algorithm and correction strategy can quickly and accurately recognize multiple and multi-deformed node faults with efficient solution speed and stability.

Key words: improved binary gray wolf optimizer, whale optimization algorithm, region correction, distributed generations, fault location

中图分类号: TP18;TM73

宋铭楷, 朱成杰. 基于H-WOA-GWO和区段修正策略的配电网故障定位研究[J]. 广西师范大学学报（自然科学版）, 2025, 43(4): 24-37.

SONG Mingkai, ZHU Chengjie. Research on Fault Location of Distribution Network Based on H-WOA-GWO and Region Correction Strategies[J]. Journal of Guangxi Normal University(Natural Science Edition), 2025, 43(4): 24-37.

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