Short-term load forecasting using Holt-Winter's method and Kalman filtering. - Nerves, Allan C.
A comparative study of two methods for short-term forecasting of substation load is presented. Holt-Winter's method predicts the load using a weighted average of past load values that decrease exponentially with time. The Kalman filtering method with fading-memory implements a two0stage forecast where a first-stage mean is first determine and a second-stage correction is applied in real time using the forecast errors from the early hours of the day. Two years of hourly load data for an 110 kV substation are used to develop and test the forecasting models for the two methods. The performance of each method is evaluated using mean absolute error, mean absolute percent error, and mean square error.
Keywords: Exponential smoothing; Kalman filtering; Load forecasting; Substation load