Journal of Guangxi Normal University(Natural Science Edition) ›› 2024, Vol. 42 ›› Issue (4): 64-73.doi: 10.16088/j.issn.1001-6600.2023041407
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WU Yi, WEN Zhong*, FENG Ling, QIN Zhiyin, ZHENG Lianhua, TANG Weizhao
[1] 缪希仁,赵丹,刘晓明,等.含分布式电源配电网短路保护研究综述[J].高电压技术,2023,49(7):3006-3019. DOI: 10.13336/j.1003-6520.hve.20220922. [2] 马新娜,赵猛,祁琳.基于卷积脉冲神经网络的故障诊断方法研究[J].广西师范大学学报(自然科学版),2022,40(3):112-120. DOI: 10.16088/j.issn.1001-6600.2021070808. [3] 邹艳丽,汪洋,刘树生,等.带有邻居度信息的容量负载模型下电网级联故障研究[J].广西师范大学学报(自然科学版),2019,37(4):27-36. DOI: 10.16088/j.issn.1001-6600.2019.04.003. [4] 詹惠瑜,刘科研,盛万兴,等.有源配电网故障诊断与定位方法综述及展望[J].高电压技术,2023,49(2):660-671. DOI: 10.13336/j.1003-6520.hve.20211604. [5] AZEROUAL M, BOUJOUDAR Y, ALJARBOUH A, et al. A multi-agent-based for fault location in distribution networks with wind power generator[J]. Wind Engineering, 2022, 46(3): 700-711. DOI: 10.1177/0309524X211044507. [6] 徐彪,尹项根,张哲,等.矩阵算法和优化算法相结合的配电网故障定位[J].电力系统自动化,2019,43(5):152-158. DOI: 10.7500/AEPS20180115002. [7] HE H Y, LU Z G, GUO X Q, et al. Optimized control strategy for photovoltaic hydrogen generation system with particle swarm algorithm[J]. Energies, 2022, 15(4): 1472. DOI: 10.3390/en15041472. [8] 郑涛,潘玉美,郭昆亚,等.基于免疫算法的配电网故障定位方法研究[J].电力系统保护与控制,2014,42(1):77-83. DOI: 10.7667/j.issn.1674-3415.2014.01.011. [9] 张颖,周韧,钟凯.改进蚁群算法在复杂配电网故障区段定位中的应用[J].电网技术,2011,35(1):224-228. DOI: 10.13335/j.1000-3673.pst.2011.01.032. [10] 吉兴全,张朔,张玉敏,等.基于IELM算法的配电网故障区段定位[J].电力系统自动化,2021,45(22):157-166. DOI: 10.7500/AEPS20210121007. [11] 卫志农,何桦,郑玉平.配电网故障区间定位的高级遗传算法[J].中国电机工程学报,2002,22(4):127-130. DOI: 10.3321/j.issn:0258-8013.2002.04.026. [12] 颜景斌,夏赛,王飞,等.基于改进遗传算法的有源配电网故障定位分析[J].电力系统及其自动化学报,2019,31(6):107-112. DOI: 10.3969/j.issn.1003-8930.2019.06.017. [13] 周湶,郑柏林,廖瑞金,等.基于粒子群和差分进化算法的含分布式电源配电网故障区段定位[J].电力系统保护与控制,2013,41(4):33-37. DOI: 10.7667/j.issn.1674-3415.2013.04.006. [14] 舒凡娣,谢嘉晟,廖晓娇,等.结合粒子群算法和穷举法的配电网故障诊断方法[J].智慧电力,2019,47(1):94-99. DOI: 10.3969/j.issn.1673-7598.2019.01.017. [15] 陈磊,詹跃东,田庆生.基于改进二进制灰狼优化算法的配网故障定位[J].电子测量技术,2019,42(1):1-5. DOI: 10.19651/j.cnki.emt.1802075. [16] 任志玲,刘卫东,杨柳,等.基于改进鸽群算法的含分布式电源配电网故障定位[J].电源学报,2022,20(4):171-178. DOI: 10.13234/j.issn.2095-2805.2022.4.171. [17] KHISHE M, MOSAVI M R. Chimp optimization algorithm[J]. Expert Systems with Applications, 2020, 149: 113338. DOI: 10.1016/j.eswa.2020.113338. [18] 谢国民,陈天香.改进黑猩猩算法的光伏发电功率短期预测[J].电力系统及其自动化学报,2024, 36(2): 135-143. DOI: 10.19635/j.cnki.csu-epsa.001241. [19] 黄倩,刘升,李萌萌,等.多策略黑猩猩优化算法研究及其工程应用[J].计算机工程与应用,2022,58(19):174-183. DOI: 10.3778/j.issn.1002-8331.2101-0520. [20] 刘琨,赵露露,王辉.一种基于精英反向和纵横交叉的鲸鱼优化算法[J].小型微型计算机系统,2020,41(10):2092-2097. DOI: 10.3969/j.issn.1000-1220.2020.10.012. [21] BABU S S, JAYASUDHA K. A simplex method-based bacterial colony optimization algorithm for data clustering analysis[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2022, 36(12): 2259027. DOI: 10.1142/S0218001422590273. |
[1] | XIAO Zhiheng, LIU Huijia. Improved TOPSIS for Node Vulnerability Assessment of Distribution Network Based on Game Theory [J]. Journal of Guangxi Normal University(Natural Science Edition), 2023, 41(3): 20-30. |
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