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State Maintenance Decision of Secondary Equipment of Distribution Automation Based on Neural Network Algorithm

机译:基于神经网络算法的分销自动化二级设备的国家维修决策

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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.
机译:随着能源互联网的发展,智能电网及其自动化需要更精确的维护。分销自动化设备的维护模式已从传统的计划维护改变为国家维护。国家监测技术用于通过分析影响分布式自动化系统的二级设备状态的因素来评估二级设备健康状况。基于神经网络算法,根据次级设备状态的评估结果进行分布式自动化的二级设备的状态维护决策方法,然后选择合理的维护模式。在案例研究中,证明了基于神经网络算法的维护决策模型通过与模糊理论评价方法进行比较是可行和有效的,这为配电自动化的二级设备提供了良好的决策依据。

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