Optimization of Extreme Natural Disaster Warning Mechanism for Power Grid Based on Cluster Analysis and Time Series Prediction
An optimization method for the extreme natural disaster warning mechanism of the power grid was proposed based on cluster analysis and time series prediction so as to warn the extreme natural disasters in the power grid and reduce the impact of extreme natural disasters in the power grid.Based on the coupling relationship between the power grid and the extreme natural disasters,a framework was established for warning extreme natural disasters in the power grid.Using the timed observation dataset of meteorological observation stations processed from multiple angles as the original sample dataset for extreme natural disaster warning work in the power grid;then,the random forest algorithm was used to determine meteorological elements highly correlated with extreme natural disasters in the power grid,forming a brand new sample dataset as an effective input for improving the long short-term memory(LSTM)network;after multiple effective studies,the possible extreme natural disasters were predicted in the area where the power grid is located,and the corresponding warnings based on the prediction results were issued.The experimental results show that the proposed method has strong practicality in the warning of extreme natural disasters in the power grid,and can effectively warn of extreme natural disasters in the power grid,ensure the safe operation of the power grid,and prevent it from being damaged by extreme natural disasters.
cluster analysistime series predictionextreme natural disastersearly warning mechanismpower networkdata preparation
万方数据
维普
