Abstract
The supply and distribution fault location method of wavelet packet energy gray-level moment wavelet neural network based on dragonfly algorithm (DA) is proposed. First, it makes convolutional wavelet energy gray-level moment for faulted electrical information, and then extracts the energy gray-level moment of fault features as the eigenvector of wavelet neural network for training, while the network parameters of wavelet neural network are globally optimized by DA. Finally, compared with the supply and distribution network fault location algorithm of support vector machine based on the DA and the pure wavelet neural network for supply and distribution network fault location algorithm, the experimental simulation shows that the proposed method has faster convergence speed. It also has the advantages of rapid descent speed, high precision, less iterations, rapid convergence, high locating accuracy for faults, and short locating time.
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Fu, J., Yue, J., Chen, L., Leng, T. (2019). Fault Location of Distribution Network for Wavelet Packet Energy Moment of Dragonfly Algorithm. In: Fang, Q., Zhu, Q., Qiao, F. (eds) Advancements in Smart City and Intelligent Building. ICSCIB 2018. Advances in Intelligent Systems and Computing, vol 890 . Springer, Singapore. https://doi.org/10.1007/978-981-13-6733-5_40
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DOI: https://doi.org/10.1007/978-981-13-6733-5_40
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