Grid search of exponential smoothing method: a case study of Ho Chi Minh City load demand

Abstract

The exponential smoothing method is one of the widely used methods for load forecasting. The taxonomy of exponential smoothing method shows that its trend and seasonal component affect the results of exponential smoothing method. This paper proposed a framework for grid search with the optimal model of exponential smoothing method based on math formulas. The training process will specify the optimal models which satisfy requirement of minimum of akaike information criterion, accuracy scores of the root mean square error, mean absolute percentage error, and mean absolute error. The testing process will evaluate the accuracy scores between the optimal models and all other ones. The results indicated that the optimal models have accuracy scores near the minimum values. The load demand data collected in Ho Chi Minh City were used to verify the accuracy and reliability of the grid search framework.