Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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基于改进海鸥优化算法的有源配电网故障定位

来源:电工电气发布时间:2025-07-24 13:24 浏览次数:10

基于改进海鸥优化算法的有源配电网故障定位

朱谢琰
(扬州三新供电服务有限公司宝应分公司,江苏 扬州 225800)
 
    摘 要:分布式电源接入配电网后,故障电流特性发生改变,使得故障定位难度增加。针对有源配电网故障定位问题,提出一种基于改进海鸥优化算法的有源配电网故障定位方法。对传统配电网故障电流编码方式进行改进使其适用于有源配电网,同时提出有源配电网故障定位的开关函数;对基本海鸥优化算法进行改进,通过改进型 Logistics 混沌映射丰富初始化海鸥种群的多样性;对线性参数 H 进行非线性化处理,使其与收敛过程更匹配;引入正弦、余弦算子使算法在全局搜索和局部开发之间达到平衡,以提升寻优质量,并实施自适应 t 分布变异以提升寻优速度。通过在 IEEE 33 节点配电网算例中进行仿真验证,经与其他智能优化算法对比,结果表明改进后的海鸥优化算法在定位速度、迭代次数、容错性能方面具有显著优势。
    关键词: 分布式电源;配电网;故障定位;改进海鸥优化算法;容错性能
    中图分类号:TM711 ;TM727     文献标识码:B     文章编号:1007-3175(2025)07-0052-08
 
The Fault Location of Active Distribution Network Based on
Improved Seagull Optimization Algorithm
 
ZHU Xie-yan
(Baoying Branch of Yangzhou Sanxin Power Supply Service Co., Ltd, Yangzhou 225800, China)
 
    Abstract: After distributed power sources are connected to the distribution network, the characteristics of fault currents change, increasing the difficulty of fault location. Aiming at the problem of fault location in active distribution networks, a fault location method for active distribution networks based on the improved seagull optimization algorithm is proposed. This paper improves the traditional fault current coding method of distribution networks to make it applicable to active distribution networks, and at the same time proposes the switch function for fault location in active distribution networks, then, the basic seagull optimization algorithm is improved, and the diversity of the initialized seagull population is enriched through the improved Logistics chaotic mapping. Perform nonlinearization processing on the linear parameter H to make it more compatible with the convergence process; the sinusoidal and cosine operators are introduced to achieve a balance between global search and local development of the algorithm, so as to improve the optimization quality, and adaptive t-distribution variation is implemented to enhance the optimization speed. Through simulation verification in the IEEE 33-node distribution network example and comparison with other intelligent optimization algorithms, the results show that the improved seagull optimization algorithm has significant advantages in positioning speed, the number of iterations, and fault-tolerant capability.
    Key words: distributed generation; distribution network; fault location; improved seagull optimization algorithm; fault-tolerant performance
 
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