Fault Graded Response Method of Power Grid Cloud Platform Application System Based on Time Series
In the application system of the power grid cloud platform,if rely on a single trigger event for fault classification,then goodness of fit of the response results is low.To solve this problem,a time series based on fault graded response method for the application system of the power grid cloud platform is proposed.This method uses fuzzy inference algorithm to divide the fuzzy level of power grid fault severity,and establishes fuzzy evaluation vector to normalize multi-source information data and extract fault feature information.The logical operation methods such as"and","or"and"not"operations are used to de-scribe the established operation rules between multiple trigger events,and combined with the autoregressive integral moving av-erage model to establish a stable time series containing multiple trigger events for subsequent fault graded response.For the a-larm information to be sent,the similarity diagnosis and coverage diagnosis are carried out,and the graded response optimiza-tion strategy is established.The experimental results show that the goodness of fit of the fault graded response results obtained by the proposed method is improved by 21％and 28％,respectively.The fault response of power grid cloud platform applica-tion system is carried out based on the hierarchical early warning results.
time seriesgrid failurecloud platformgraded responsetrigger eventalarm algorithm
万方数据
维普
