A trigonometric grey prediction approach to forecasting electricity demand

Electricity demand forecasting plays an important role in electricity systems expansion planning. In this paper, we present a trigonometric grey prediction approach by combining the traditional grey model GM(1,1) with the trigonometric residual modification technique for forecasting electricity demand. Our approach helps to improve the forecasting accuracy of the GM(1,1) and allows a reasonable grey prediction interval to be obtained. Two case studies using the data of China are presented to demonstrate the effectiveness of our approach.