Research and Prediction of Distribution Network Operation and Maintenance Cost
Reliability value analysis is an important tool for planning and operating distribution systems,and the interruption cost prediction model directly affects the accuracy of reliability value assessment.Based on this,this paper uses radial basis function(RBF)neural network combined with orthogonal least squares(OLS)learning method to construct two kinds of interruption cost prediction models,namely average or aggregate model(AAM)and probability distribution model(PDM).The proposed neural network technology was used to integrate the costs of residential and industrial interruptions in AAM and PDM,and Monte Carlo time series simulation technology was used for value evaluation and prediction.The reliability value of the installation of disconnect switches,transverse fuses,transformers,and backup power sources in the Taiwan Power System was evaluated,and the technology was tested.The results indicate that the two cost models generated different interruption costs,and PDM's modeling of the system is more in line with reality.
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