Research on Line Loss Rate Prediction of 10kV Distribution Network Based on SVR Optimized by Gray Wolf Algorithm
Effective control of line loss rate can not only bring economic benefits to power enterprises,but also improve the utilization rate of primary energy.In order to achieve accurate prediction of 10kV distribution network line loss rate,a Support Vector Regression prediction method based on Gray Wolf Optimizer was proposed.The outlier test based on Mahalanobis distance and Principal Components Analysis are used to preprocess the original data to ensure the cleanliness of the data and eliminate the redundant information in the original data.The strong search ability of GWO algorithm was combined with SVR to establish the model.Compared with the pre-diction results of original SVR,ABC-SVR and BP neural network models,the prediction accuracy of GWO-SVR model was the highest,and its root mean square error(RMSE)and mean absolute error(MAE)were 0.233 2 and 0.195 8,respectively.The maximum relative error is 14.4%,and this model has the fastest computing speed.
gray wolf algorithm10kV distribution networkMahalanobis distanceprincipal component analysisline loss rate
万方数据
维普
