Hybrid forecasting model of electric heating load based on CART decision tree regression

Abstract

Electric heating load forecasting of power system plays an important role in the safe and economic stability based on historical data is the key feature of regression tree model and based on the behavior characteristics, building electrical heating load forecasting model, through the change of the external electricity price incentives, to obtain dynamic characteristic of the electric heating load data, access to electricity heating static characteristic and dynamic characteristic data of variation, According to the variation of dynamic response, the application value of dynamic characteristics of electric heating load on the power grid side is analyzed. Data analysis shows that the method has good prediction accuracy and potential application of dynamic characteristics.