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Oppositional Brain Storm Optimization for Fault Section Location in Distribution Networks

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Brain Storm Optimization Algorithms

Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 23))

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Abstract

Fault section location (FSL) is an important role in facilitating quick repair and restoration of distribution networks. In this chapter, an oppositional brain storm optimization referred to as OBSO is proposed to effectively solve the FSL problem. The FSL problem is transformed into a 0–1 integer programming problem. The difference between the reported overcurrent and expected overcurrent states of the feeder terminal units (FTUs) is used as the objective function. BSO has been shown to be competitive to other population-based algorithms. But its convergence speed is relatively slow. In OBSO, opposition-based learning method is utilized for population initialization and also for generation jumping to accelerate the convergence rate. The effectiveness of OBSO is comprehensively evaluated on different fault scenarios including single and multiple faults with lost and/or distorted fault signals. The experimental results show that OBSO is able to achieve more promising performance.

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Acknowledgements

The authors would like to thank the editor and the reviewers for their constructive comments. This work was supported by the National Natural Science Foundation of China under Grant No. 51867005, the Scientific Research Foundation for the Introduction of Talent of Guizhou University (Grant No [2017] 16), and the Guizhou Province Science and Technology Innovation Talent Team Project (Grant No [2018] 5615), the Science and Technology Foundation of Guizhou Province (Grant No. [2016]1036), and the Guizhou Province Reform Foundation for Postgraduate Education (Grant No. [2016]02).

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Authors and Affiliations

  1. Guizhou Key Laboratory of Intelligent Technology in Power System, College of Electrical Engineering, Guizhou University, Guiyang, 550025, China

    Guojiang Xiong, Jing Zhang & Yu He

  2. State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Dongyuan Shi

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  1. Guojiang Xiong
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  2. Jing Zhang
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  3. Dongyuan Shi
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  4. Yu He
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Correspondence to Guojiang Xiong .

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Editors and Affiliations

  1. School of Computer Science, Shaanxi Normal University, Xi’an, China

    Shi Cheng

  2. Shenzhen Key Laboratory of Computational Intelligence, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Xiong, G., Zhang, J., Shi, D., He, Y. (2019). Oppositional Brain Storm Optimization for Fault Section Location in Distribution Networks. In: Cheng, S., Shi, Y. (eds) Brain Storm Optimization Algorithms. Adaptation, Learning, and Optimization, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-030-15070-9_3

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