A hybrid dynamic and fuzzy time series model for mid-term power load forecasting

摘要: Abstract A new hybrid model for forecasting the electric power load several months ahead is proposed. To allow distinct responses from individual sectors, this model, which combines dynamic (i.e., air temperature dependency of load) and fuzzy time series approaches, applied separately to household, public, service, industrial sectors. The tested using actual data Seoul metropolitan area, its predictions are compared with those two typical models. Our investigation shows that, in case four-month forecasting, proposed gives monthly every sector only less than 3% absolute error satisfactory reduction errors other models previous studies.