Active distribution network fault location method based on the NSGA-III algorithm

Feng Wang; Yiquan Li; Minghui Hang; Qian Tan

doi:10.1117/12.2639901

27 June 2022 Active distribution network fault location method based on the NSGA-III algorithm

Feng Wang, Yiquan Li, Minghui Hang, Qian Tan

Proceedings Volume 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022); 122530P (2022) https://doi.org/10.1117/12.2639901
Event: Second International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 2022, Qingdao, China

Abstract

Traditional active distribution networks generally use single-objective optimization algorithms for fault location. The objective function of the single-objective optimization model is weighted by each sub-objective function. Improper selection of weights will affect the location results, resulting in misjudgment or missed judgment. In this paper, a multiobjective optimization model suitable for fault location of active distribution network is proposed, and a non-dominant sorting genetic algorithm with elite strategy (NSGA-III) is used to solve the optimization problem. NSGA-III algorithm does not need to consider the weight problem, has good convergence and will not fall into local optimum. Finally, a modified IEEE33-nodes distribution network model is built by PSCAD, the three cases of information mistransmission of the intelligent terminal unit are considered, and the simulations are carried out from two aspects of single and multiple faults. It is verified that the active distribution network fault location method based on NSGA-III algorithm can still accurately locate fault segments with high reliability under single or multiple types of information misinformation.

Citation Download Citation

Feng Wang, Yiquan Li, Minghui Hang, and Qian Tan "Active distribution network fault location method based on the NSGA-III algorithm", Proc. SPIE 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 122530P (27 June 2022); https://doi.org/10.1117/12.2639901

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