Estimating Energy and Exergy Production and Consumption Values Using Three Different Genetic Algorithm Approaches. Part 1: Model Development

Abstract

Abstract The present study, consisting of two parts, proposes new models for estimating energy and exergy production and consumption values using the genetic algorithm approach. Part 1 of this study deals with the model development, while the application and testing with various scenarios will be treated in Part 2. In this regard, the genetic algorithm energy (GAEN) and genetic algorithm exergy (GAEX) estimating models have been proposed. During the energy and exergy estimation, independent variables are the GDP, population, and the ratio of export to import. The three forms of the GAEN and GAEX are developed, of which one is linear, second is exponential and the third is a mix of the exponential and linear form of the equations. Among them, the best fit models in terms of average relative errors and for the testing period are selected for future estimation and proposed both for GAEN and GAEX. It may be concluded that the models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques.