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State maintenance decision of secondary equipment of distribution automation based on neural network algorithm

With the development of energy Internet, smart grid and its automation needs more precise maintenance. The maintenance mode of the distribution automation equipment has been changed from the traditional plan maintenance to the state maintenance. The state monitoring technology is used to evaluate the secondary equipment health status by analyzing the factors influencing the secondary equipment status of the distribution automation system. Based on the neural network algorithm, the state maintenance decision method of the secondary equipment of the distribution automation is carried out according to the evaluation results of the secondary equipment state, and then the reasonable maintenance mode is selected. In the case study, it is proved that the maintenance decision model based on the neural network algorithm is feasible and efficient by comparing with the fuzzy theory evaluation method, which provides a good decision basis for the conditional maintenance of the secondary equipment of the distribution automation.