Line Loss Rate Forecasting Based on Kernel Partial Least-Squares Regression Analyze
Haiyan Wang · Jisuanji fangzhen · 2012
Studied the line loss rate forecast.In order to improve the prediction accuracy and according to the characteristics of line loss rate,Kernel Partial Least-Squares(KPLS) algorithm was firstly applied in line loss rate forecasting.It used the line loss rate and associated data over years to build predictive models at first,and to forecast the line loss rate of next year.It used a power grid to simulate,and the simulation results was compared with the result obtained with other methods.The results show that the forecast of line loss rate based on KPLS regression analysis is of high accuracy.It can overcome the adverse effects of the variable correlation and nonlinear factors,and provide a theoretical basis for developing scientific and rational line loss rate plan by the power companies.