Improved Grey Verhulst model with the constant term and its application to forecast energy demand

Abstract

The importance of accurate energy demand modeling has increased to support the decision-making of policy makers for ensuring a safe energy supply. However, forecasting energy demand has several difficulties due to the complexity in the supply line, demand increase, nonlinearity of data and volatility of energy usage. In this study, an improved Grey Verhulst model with the Constant Term (GVMCT), which is based on the Grey model, is introduced for improving the accuracy of energy demand prediction models. Within this context, total residential electricity demand of the U.S. and Turkey are modeled via linear and quadratic trend models as well as 3 grey models, including the proposed GVMCT model. The effectiveness of the models is assessed based on the Mean Absolute Error, Mean Squared Error, and Root-Mean Square Error. The results show that linear trend is the best performing model with a MAE of 34564.81844 for the U.S. data whereas the proposed GVMCT with a MAE of 4130.086917 outperforms all models for the data of Turkey.