The BP neural network microgrid fault diagnosis method based on optimisation of pelican algorithm

Mingze Sun; Yanbing Guo; Yongkang Hou

doi:10.1117/12.3039728

4 September 2024 The BP neural network microgrid fault diagnosis method based on optimisation of pelican algorithm

Mingze Sun, Yanbing Guo, Yongkang Hou

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 132590D (2024) https://doi.org/10.1117/12.3039728
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

In this study, a fault diagnosis method combining the Pelican algorithm and BP neural network is proposed for improving the fault diagnosis accuracy and efficiency of microgrid systems. Pelican algorithm is a new optimisation algorithm developed in recent years, which can effectively optimise the weights and deviations of BP neural networks. Based on this characteristic, the Pelican algorithm is used to process the data of the actual microgrid system, and compared and analysed with the traditional BP neural network and RNF neural network. The experimental results show that the BP neural network optimised by the Pelican algorithm exhibits higher accuracy and robustness in microgrid fault diagnosis, which provides an important support for the reliability of microgrid systems.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mingze Sun, Yanbing Guo, and Yongkang Hou "The BP neural network microgrid fault diagnosis method based on optimisation of pelican algorithm", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 132590D (4 September 2024); https://doi.org/10.1117/12.3039728

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