Forecasting of Thailand Electricity Load Consumption Using Machine Learning Algorithms

Abstract

Electricity is important in our modern life and also essential to the development of the country. Since the electricity load consumption in Thailand increases almost every year, the power systems capacity expansion is unavoidable. The purpose of this paper was to apply the machine learning algorithms to forecast the long-term electricity load consumption in Thailand. Three algorithms employed were artificial neural network (ANN), support vector regression (SVR), and k-nearest neighbors (KNN). The performances were evaluated in terms of mean absolute percentage error (MAPE). The results showed that the ANN outperformed other algorithms with a MAPE of 2.586%.