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Reliability evaluation of distribution network based on fuzzy spiking neural P system with self-synapse

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Abstract

This paper proposes a fuzzy spiking neural P system with self-synapse (in short, FSNPSS) which is applied to the reliability assessment of distribution networks. The method maps the operation or fault states of the distribution network component and the load to the excited or resting states of neurons, and converts electrical relationships among components, loads and targeted systems into a synaptic connection relationship. Then, the occurrence probabilities of the states are transmitted by spikes, and reliability indices are computed by accumulating pulse values of the spikes. Finally, the feasibility and effectiveness of solving reliability assessment of distribution networks by membrane systems are verified in case studies.

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Acknowledgements

This work was supported by a grant from Sichuan Provincial Department of Science and Technology (No. 2019122).

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Authors and Affiliations

  1. School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, People’s Republic of China

    YuLei Huang, Tao Wang & Jun Wang

  2. Key Laboratory of Fluid Power Machinery, Ministry of Education, Xihua University, Chengdu, People’s Republic of China

    YuLei Huang, Tao Wang & Jun Wang

  3. School of Computer and Software Engineering, Xihua University, Chengdu, People’s Republic of China

    Hong Peng

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  1. YuLei Huang
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  2. Tao Wang
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  4. Hong Peng
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Correspondence to YuLei Huang.

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Huang, Y., Wang, T., Wang, J. et al. Reliability evaluation of distribution network based on fuzzy spiking neural P system with self-synapse. J Membr Comput 3, 51–62 (2021). https://doi.org/10.1007/s41965-020-00035-1

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  • DOI: https://doi.org/10.1007/s41965-020-00035-1

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