Abstract
In the event of failures, it is essential that the distribution network can autonomously adjust its topology structure to satisfy the power supply requirements. Therefore, how to reconstruct the distribution network is crucial for the development of smart grids. To improve the accuracy and reliability of fault reconstruction in distribution networks, we propose a discrete multimodal multi-objective particle swarm algorithm based on the nearest neighbor algorithm (DMMPSO-NNS) in this study, which employs the nearest neighbor search method to maintain population diversity. The results prove that the DMMPSO-NNS performs better than other selected algorithms on the IEEE 33-bus distribution network.
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Acknowledgements
This work was partially supported by the Power Planning Special Research Project of Guangdong Power Grid Company (031900QQ00230001), the Humanities and Social Sciences on Planning Foundation of the Ministry of Education in China (Research on cross-domain collaborative maritime unmanned search and rescue methods and strategies, 23YJAZH029), the Shanghai Pujiang Program (No. 22PJD030), the National Nature Science Foundation of China (No. 61603244).
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Li, J., Zeng, Z., Ye, J., Yue, M., Mo, H., Fan, Q. (2024). Fault Reconfiguration of Distribution Networks Using an Enhanced Multimodal Multi-objective Evolutionary Algorithm. In: Tan, Y., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2024. Lecture Notes in Computer Science, vol 14788. Springer, Singapore. https://doi.org/10.1007/978-981-97-7181-3_23
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