Study of Support Vector Machines Based on immunogenetic particle swarm algorithm in Short-Term Power Load Forecasting Model

摘要

Accurate power load forecasting is important for electric power system, it must guarantee its economical and safe operation. In this article, an improved support vector machine mode was applied in predicting the load forecasting and calculating the optimum solution of the SVM model by new immunogenetic particle swarm algorithm. Applying the presented forecasted method to actual load forecasting and the comparing among the forecasted results single SVM and BP method, it is shown that the presented forecasting method is more accurate and efficient.