Novel input variable selection for ANN short-term load forecasting

It is important to select input variables for ANN based load forecasting. Whether the input variables, representing the cause of change of expected output, are selected or not is relevant to the performance of ANN forecasting. A novel method of input variable selection for ANN short-term load forecasting based on OLS method is presented. An example of forecasting Nanjing 1998 and 1999 summer day peak load is given and the results obtained by both OLS method and correlation coefficient analysis method are compared. The comparison shows that smaller and more accurate input variables set can be obtained via OLS method, thus its effectiveness is demonstrated.