Accurate load forecasting is the key to ensure the orderly operation of the power market. In view of the limited environment of single factor forecasting and the ill- considered problems of the split and interaction of variables in the comprehensive model

a generalized additive short- term load forecasting model considering subdivided characteristic variables such as temperature

holidays and load is proposed. Firstly

the correlation coefficients of different factors and loads are subdivided and calculated

and the eigenvalues are selected according to the correlation degree. Secondly

the load fluctuation basis function is determined

and the whole forecasting model is formed according to the subdivided characteristic variables. Finally

the actual operation data of Guangzhou is used to calculate and analyze. The example shows that the generalized additive model based on eigenvalue subdivision is an effective method for short-term load forecasting.