刘岩,彭鑫霞,郑思达.基于改进LS-SVM的短期电力负荷预测方法研究[J].电测与仪表,2021,58(5):176-181. Liu Yan,Peng Xinxia,Zheng Sida.Research on Short-term Power Load Forecasting Method Based on Improved LS-SVM[J].Electrical Measurement & Instrumentation,2021,58(5):176-181.
基于改进LS-SVM的短期电力负荷预测方法研究
Research on Short-term Power Load Forecasting Method Based on Improved LS-SVM
Aiming at the problems of strong randomness, poor stability and unsatisfactory forecasting accuracy of power load, a short-term power load forecasting method combining particle swarm optimization PSO and least squares support vector machine LS-SVM is proposed in this paper.The input factors of the model are load data and meteorological information, particle swarm optimization algorithm is adopted to realize the automatic selection of the parameter of the support vector machine,the least squares support vector machine short-term load forecasting model optimized by particle swarm optimization is established.The accuracy and validity of the improved prediction method are verified by simulation, the results show that the improved method brings benefits to convergence, thinking accuracy and training speed.This study provides a reference for the development of short-term load forecasting methods in China.
