Fault Location of Distribution Networks Based on Combination of Quantum Computing and Ant Colony Algorithm

doi:10.3969/j.issn.1008-0198.2024.04.019

Hunan Electric Power ›› 2024, Vol. 44 ›› Issue (4): 132-137.doi: 10.3969/j.issn.1008-0198.2024.04.019

• Faults and Analysis • Previous Articles Next Articles

Fault Location of Distribution Networks Based on Combination of Quantum Computing and Ant Colony Algorithm

YANG Hailin¹, HUANG Cunqiang¹, TIAN Xu¹, AN Juan¹, ZHANG Shunzhen¹, BI Zhongqin²

1. State Grid Qinghai Electric Power Company Economic and Technological Research Institute, xining 810000, China;
2. College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201306, China

Received:2024-04-08 Revised:2024-04-25 Online:2024-08-25 Published:2024-09-09

Abstract

Abstract: Aiming at the drawbacks of slow convergence speed and low success rate of intelligent optimization algorithms in dealing with fault location problems in distribution networks, a quantum ant colony algorithm based on the combination of quantum computing and ant colony algorithm is proposed for fault location in distribution networks. Firstly, considering the distortion and loss of information uploaded by the feeder terminal unit (FTU), a hierarchical positioning mathematical model is proposed that takes into account the false alarm information of FTU. Secondly, the basic principles and application schemes of quantum ant colony algorithm are introduced. Finally, simulation is conducted on MATLAB to verify the effectiveness of the quantum ant colony algorithm and the hierarchical localization mathematical model that takes into account FTU false alarm information.

Key words: fault location of distribution network, quantum ant colony algorithm, FTU false alarm, hierarchical positioning model

CLC Number:

TM911

YANG Hailin, HUANG Cunqiang, TIAN Xu, AN Juan, ZHANG Shunzhen, BI Zhongqin. Fault Location of Distribution Networks Based on Combination of Quantum Computing and Ant Colony Algorithm[J]. Hunan Electric Power, 2024, 44(4): 132-137.

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Fault Location of Distribution Networks Based on Combination of Quantum Computing and Ant Colony Algorithm

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