Total Energy Demand Estimation in Iran Using Bees Algorithm

Abstract

Many studies are performed by researchers to estimate energy demand but the bees algorithm (BA) technique has never been used for such a study. This paper presents application of the BA technique to estimate total energy demand in Iran, based on socioeconomic indicators.

The BA demand estimation models (BA-DEM) are first developed in two forms (exponential and linear) in order to estimate energy demand based on population, gross domestic product, import and export data. Then, two scenarios are designed for forecasting each socioeconomic indicator in the years 2006–2030. Finally, these two scenarios are used to forecast energy demand up to year 2030 using demand estimation models. Energy consumption in Iran from 1981–2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal, values of the weighting parameters (1981–1999) and partly for testing the models (2000–2005). In order to show the accuracy of the BA, obtained results of BA-DEM models are compared with particle swarm optimization and genetic algorithm demand estimation models which are developed for the same problem.

Keywords:

• Bees Algorithm
• demand
• energy
• forecasting
• Iran

Notes

^a Mboe: Million barrel of oil equivalent.

1 barrel of oil equivalent (boe) = 6,119 × 10⁶ joule (J).