{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T17:20:58Z","timestamp":1771003258930,"version":"3.50.1"},"reference-count":26,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T00:00:00Z","timestamp":1746576000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Scientific and Technological Research Projects in Henan Province","award":["242102240122"],"award-info":[{"award-number":["242102240122"]}]},{"name":"Key Project of Natural Science, Hebi Institute of Engineering and Technology, Henan Polytechnic University","award":["2023-ZRZZ-002"],"award-info":[{"award-number":["2023-ZRZZ-002"]}]},{"name":"School-level teaching reform project, Hebi Institute of Engineering and Technology, Henan Polytechnic University","award":["2023-JGZZ-007"],"award-info":[{"award-number":["2023-JGZZ-007"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Computational Methods in Sciences and Engineering"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>Aiming at the problems such as slow convergence speed, precocious convergence and poor fault tolerance performance of dung beetle optimizer (DBO) algorithm in solving active distribution network fault location, a partition fault location method for active distribution network based on adaptive chaotic DBO (AC-DBO) algorithm is put forward. Firstly, an improved Tent chaotic map is introduced to realize population initialization, so as to improve the quality of initial population distribution in the search space and its global search efficiency. Secondly, the adaptive T-distribution mutation mechanism is incorporated into the dung beetle position update to elevate the global exploration and local exploitation abilities of the algorithm. Finally, the equivalent partition model for active distribution network is established based on the \u201cblack box\u201d theory to reduce the solving dimension of the algorithm and improve the location rate. The comparative experimental results of multi-verse optimization (MVO), red-tailed hawk (RTH), slime mould algorithm (SMA), and AC-DBO algorithm and the effectiveness simulation test results of hierarchical positioning model show that the average positioning accuracy of AC-DBO algorithm is increased by 15%, 10%, and 3%, respectively, compared with MVO, RTH, and SMA algorithms. After introducing the equivalent partition strategy, the average positioning time of AC-DBO hierarchical positioning model is reduced by 36.8% and 29.4%, respectively, compared with AC-DBO single-layer positioning model and DBO hierarchical positioning model and the average positioning accuracy is increased by 21% and 8%, respectively. The AC-DBO partition model has obvious advantages in solving speed, accuracy and fault tolerance, which is especially suitable for solving the fault location problem of active distribution network.<\/jats:p>","DOI":"10.1177\/14727978251341481","type":"journal-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T02:50:49Z","timestamp":1750819849000},"page":"4710-4723","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Partition fault location of active distribution network based on AC-DBO"],"prefix":"10.1177","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3481-8050","authenticated-orcid":false,"given":"Zhao","family":"Min","sequence":"first","affiliation":[{"name":"Hebi Institute of Engineering and Technology, Henan Polytechnic University, Hebi, China"}]},{"given":"Kang","family":"Zhihui","sequence":"additional","affiliation":[{"name":"Hebi Institute of Engineering and Technology, Henan Polytechnic University, Hebi, China"}]}],"member":"179","published-online":{"date-parts":[[2025,5,7]]},"reference":[{"key":"e_1_3_3_2_2","article-title":"Resilience enhancement of active distribution networks under extreme disaster scenarios: a comprehensive overview of fault location strategies","volume":"189","author":"Liangyu T","year":"2024","unstructured":"Liangyu T, Yang H, Zalhaf AS. Resilience enhancement of active distribution networks under extreme disaster scenarios: a comprehensive overview of fault location strategies. Renew Sustain Energy Rev 2024; 189.","journal-title":"Renew Sustain Energy Rev"},{"issue":"10","key":"e_1_3_3_3_2","first-page":"3926","article-title":"Fault section location of active distribution network based on feeder terminal unit information distortion correction","volume":"45","author":"Tao Z","year":"2021","unstructured":"Tao Z, Long M, Bowen L. Fault section location of active distribution network based on feeder terminal unit information distortion correction. Power Syst Technol 2021; 45(10): 3926\u20133935.","journal-title":"Power Syst Technol"},{"issue":"5","key":"e_1_3_3_4_2","first-page":"64","article-title":"An improved general matrix algorithm for fault locating in distribution system","volume":"40","author":"Mei L","year":"2012","unstructured":"Mei L, Honggeng Y. An improved general matrix algorithm for fault locating in distribution system. Power System Protection and Control 2012; 40(5): 64\u201368.","journal-title":"Power System Protection and Control"},{"issue":"1","key":"e_1_3_3_5_2","first-page":"1","article-title":"Fault location method of active distribution network based on graph theory and matrix algorithm","volume":"2121","author":"Yalei L","year":"2021","unstructured":"Yalei L, Xiaohong Z. Fault location method of active distribution network based on graph theory and matrix algorithm. J Phys Conf 2021; 2121(1): 1\u20136.","journal-title":"J Phys Conf"},{"key":"e_1_3_3_6_2","first-page":"1","article-title":"A comprehensive method for fault location of active distribution network based on improved matrix algorithm and optimization algorithm","volume":"2022","author":"Zhen L","year":"2022","unstructured":"Zhen L, Jian Q, Yikai W. A comprehensive method for fault location of active distribution network based on improved matrix algorithm and optimization algorithm. International Transactions on Electrical Energy Systems 2022; 2022: 1\u201311.","journal-title":"International Transactions on Electrical Energy Systems"},{"issue":"5","key":"e_1_3_3_7_2","first-page":"152","article-title":"Fault location for distribution network based on matrix algorithm and optimization algorithm","volume":"43","author":"Biao X","year":"2019","unstructured":"Biao X, Xianggen Y, Zhe Z. Fault location for distribution network based on matrix algorithm and optimization algorithm. Autom Electr Power Syst 2019; 43(5): 152\u2013161.","journal-title":"Autom Electr Power Syst"},{"issue":"11","key":"e_1_3_3_8_2","first-page":"3684","article-title":"Fault section location method for DG-DNs based on integer linear programming","volume":"42","author":"Ruijiang H","year":"2018","unstructured":"Ruijiang H, Zhijian H, Yan L. Fault section location method for DG-DNs based on integer linear programming. Power Syst Technol 2018; 42(11): 3684\u20133692.","journal-title":"Power Syst Technol"},{"issue":"3","key":"e_1_3_3_9_2","first-page":"29","article-title":"Fault location in distribution network based on BBPSO algorithm","volume":"31","author":"Jianwei Z","year":"2019","unstructured":"Jianwei Z, Jianfeng Z, Xiuchao H. Fault location in distribution network based on BBPSO algorithm. Proc CSU-EPSA 2019; 31(3): 29\u201334.","journal-title":"Proc CSU-EPSA"},{"issue":"12","key":"e_1_3_3_10_2","first-page":"3475","article-title":"Research on distribution network fault location based on bayesian compressed sensing theory","volume":"39","author":"Ke J","year":"2019","unstructured":"Ke J, Lun L, Zhe Y. Research on distribution network fault location based on bayesian compressed sensing theory. Proceedings of the CSEE 2019; 39(12): 3475\u20133485.","journal-title":"Proceedings of the CSEE"},{"issue":"2","key":"e_1_3_3_11_2","first-page":"396","article-title":"Fault location for active distribution network based on quantum computing and immune optimization algorithm","volume":"47","author":"Fengyang G","year":"2021","unstructured":"Fengyang G, Zhaojun L, Cheng Y. Fault location for active distribution network based on quantum computing and immune optimization algorithm. High Volt Eng 2021; 47(2): 396\u2013406.","journal-title":"High Volt Eng"},{"issue":"18","key":"e_1_3_3_12_2","first-page":"1","article-title":"Fault location of a distribution network hierarchical model with a distribution generator based on IBES","volume":"50","author":"Guohua Y","year":"2022","unstructured":"Guohua Y, Ji F, Xuan L. Fault location of a distribution network hierarchical model with a distribution generator based on IBES. Pow Sys Protec Cont 2022; 50(18): 1\u20139.","journal-title":"Pow Sys Protec Cont"},{"issue":"20","key":"e_1_3_3_13_2","first-page":"83","article-title":"Research on fault location in a distribution network based on an immune binary particle swarm algorithm","volume":"48","author":"Qiao Z","year":"2020","unstructured":"Qiao Z, Zengping W, Wenna D. Research on fault location in a distribution network based on an immune binary particle swarm algorithm. Pow Sys Protec Cont 2020; 48(20): 83\u201389.","journal-title":"Pow Sys Protec Cont"},{"issue":"2","key":"e_1_3_3_14_2","first-page":"8","article-title":"Fault location of distribution network with distribution generations based on BAS-IGA","volume":"33","author":"Bin Q","year":"2021","unstructured":"Bin Q, Tianyuan L, Bo N. Fault location of distribution network with distribution generations based on BAS-IGA. Proc CSU-EPSA 2021; 33(2): 8\u201314.","journal-title":"Proc CSU-EPSA"},{"issue":"18","key":"e_1_3_3_15_2","first-page":"108","article-title":"Fault location of power distribution network based on fruit fly optimization algorithm","volume":"47","author":"Weizhang W","year":"2019","unstructured":"Weizhang W, Chun W, Xin A. Fault location of power distribution network based on fruit fly optimization algorithm. Pow Sys Protec Cont 2019; 47(18): 108\u2013114.","journal-title":"Pow Sys Protec Cont"},{"issue":"3","key":"e_1_3_3_16_2","first-page":"1","article-title":"Fault section location for distribution network containing DG based on IBQPSO","volume":"20","author":"Min Z","year":"2020","unstructured":"Min Z, Yanfang Z. Fault section location for distribution network containing DG based on IBQPSO. J Comput Methods Sci Eng 2020; 20(3): 1\u201313.","journal-title":"J Comput Methods Sci Eng"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3123180"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110973"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1002\/cta.3954"},{"issue":"7","key":"e_1_3_3_20_2","first-page":"7305","article-title":"Dung beetle optimizer: a new meta-heuristic algorithm for global optimization","volume":"79","author":"Jiankai X","year":"2022","unstructured":"Jiankai X, Bo S. Dung beetle optimizer: a new meta-heuristic algorithm for global optimization. J Supercomput 2022; 79(7): 7305\u20137336.","journal-title":"J Supercomput"},{"key":"e_1_3_3_21_2","first-page":"1","article-title":"Grey wolf optimizer with an enhanced hierarchy and its application to the wireless sensor network coverage optimization problem","volume":"96","author":"Zhaoming M","year":"2020","unstructured":"Zhaoming M, Xianfeng Y, Fengyu Z. Grey wolf optimizer with an enhanced hierarchy and its application to the wireless sensor network coverage optimization problem. Appl Soft Comput 2020; 96: 1\u201321.","journal-title":"Appl Soft Comput"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/4235.585893"},{"issue":"1","key":"e_1_3_3_23_2","first-page":"300","article-title":"Slime mould algorithm: a new method for stochastic optimization","volume":"111","author":"Shimin L","year":"2020","unstructured":"Shimin L, Huiling C, Mingjing W. Slime mould algorithm: a new method for stochastic optimization. Future Gener Comput Syst 2020; 111(1): 300\u2013323.","journal-title":"Future Gener Comput Syst"},{"issue":"2","key":"e_1_3_3_24_2","first-page":"672","article-title":"Multi-verse optimizer: a nature-inspired algorithm for global optimization","volume":"45","author":"Mirjalili S","year":"2021","unstructured":"Mirjalili S, Mirjalili SM, Hatamlou A. Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput Appl 2021; 45(2): 672\u2013679.","journal-title":"Neural Comput Appl"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-38778-3"},{"issue":"22","key":"e_1_3_3_26_2","first-page":"5327","article-title":"The technology on fault location of distribution network based on hierarchical model and intelligent checking algorithm","volume":"33","author":"Qiujie W","year":"2018","unstructured":"Qiujie W, Tao J, Hong T. The technology on fault location of distribution network based on hierarchical model and intelligent checking algorithm. Trans China Electrotech Soc 2018; 33(22): 5327\u20135337.","journal-title":"Trans China Electrotech Soc"},{"issue":"5","key":"e_1_3_3_27_2","first-page":"693","article-title":"Fast fault location technology for distribution network based on quantum ant colony algorithm","volume":"58","author":"Zhongqin B","year":"2024","unstructured":"Zhongqin B, Xiaowan Y, Baonan W. Fast fault location technology for distribution network based on quantum ant colony algorithm. J Shanghai Jiaot Univ 2024; 58(5): 693\u2013708.","journal-title":"J Shanghai Jiaot Univ"}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14727978251341481","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/14727978251341481","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14727978251341481","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T16:31:46Z","timestamp":1771000306000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/14727978251341481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,7]]},"references-count":26,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["10.1177\/14727978251341481"],"URL":"https:\/\/doi.org\/10.1177\/14727978251341481","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,7]]}}}