Microgrid fault diagnosis method for optimizing extreme learning machine based on whale algorithm

Abstract

The invention relates to a microgrid fault diagnosis method for optimizing an extreme learning machine based on a whale algorithm. The method comprises the steps of: S1, building a microgrid grid-connected operation simulation model comprising a wind driven generator, a photovoltaic cell and a storage battery, and collecting three-phase fault voltage signals at two ends of a line; S2, selecting adb6 wavelet as a wavelet basis, decomposing and reconstructing the three-phase fault voltage signals containing the phase A, the phase B and the phase C obtained by simulation according to a wavelet packet analysis related formula, calculating the energy entropies of the three-phase fault voltage signals to obtain a feature vector X= [x1, x2,..., x24] T containing 24 wavelet packet energy entropies, and taking the feature vector as a data sample; and S3, utilizing a whale algorithm WOA to optimize an input weight and a hidden layer threshold of an extreme learning machine ELM to establish a WOA-ELM fault diagnosis model, and substituting the data sample obtained in the S2 into the WOA-ELM model to carry out training and verification. A BP neural network, an RBF neural network and the ELM are utilized to establish the diagnosis model, the diagnosis model and the WOA-ELM model are subjected to comparative analysis, and the effectiveness and reliability of the WOA-ELM model are verified.

Description

technical field [0001] The invention relates to a fault diagnosis method for a wind-solar-storage micro-grid, which belongs to the field of fault detection and protection of a micro-grid, and specifically relates to a fault diagnosis method for a micro-grid based on a whale algorithm to optimize an extreme learning machine. Background technique [0002] Distributed power generation is the main direction of new energy development. Microgrid is one of the effective means of integrating distributed energy and an important part of the power system. Microgrid uses renewable energy such as wind turbines, solar power generation equipment, and fuel cells to generate electricity. It has the advantages of green environmental protection, safety and reliability, simple energy conversion, and low operation and maintenance costs. It can effectively solve the shortage of traditional energy sources and the increasingly serious environmental problems. pollution problem. During the operation...

AI Technical Summary

Problems solved by technology

By using the Whale Algorithm to optimize the input weights and hidden layer thresholds of the extreme learning machine to establish a fault diagnosis model, it solves the problem that the network performance is difficult to achieve optimal due to the artificial setting of the initial weights and hidden layer thresholds of the extreme learning machine, which is conducive to further development. Improve recognition accuracy

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