A Weighted Combination Forecasting Model for Power Load Based on Forecasting Model Selection and Fuzzy Scale Joint Evaluation

Abstract

To solve the medium and long term power load forecasting problem, the combination forecasting method is further expanded and a weighted combination forecasting model for power load is put forward. This model is divided into two stages which are forecasting model selection and weighted combination forecasting. Based on Markov chain conversion and cloud model, the forecasting model selection is implanted and several outstanding models are selected for the combination forecasting. For the weighted combination forecasting, a fuzzy scale joint evaluation method is proposed to determine the weight of selected forecasting model. The percentage error and mean absolute percentage error of weighted combination forecasting result of the power consumption in a certain area of China are 0.7439% and 0.3198%, respectively, while the maximum values of these two indexes of single forecasting models are 5.2278% and 1.9497%. It shows that the forecasting indexes of proposed model are improved significantly compared with the single forecasting models.