Gene expression programming as a basis for new generation of electricity demand prediction models

• Gene expression programming is presented for the estimation of the electricity demand.
• Annual data collected through years 1986–2009 in Thailand are used to develop the model.
• GEP significantly outperform the existing electricity demand prediction methods.

This study proposes a new gene expression programming (GEP) approach for the prediction of electricity demand. The annual population, gross domestic product, stock index, and total revenue from exporting industrial products were used to predict the electricity demand of the same year in Thailand. Several statistical criteria were used to verify the validity of the model. Further, the contributions of the influencing variables to the prediction of the electricity demand were analyzed. Correlation coefficient, root mean squared error and mean absolute percent error were used to evaluate the performance of the model. In addition to its high accuracy, the derived model outperforms regression and other soft computing-based models.