The Influence of Genetic Algorithm Parameters Over the Efficiency of the Energy Consumption Estimation in a Low–energy Building

Dynamic mathematical models are widely used for estimating the energy consumption in buildings. This paper presents the procedure to follow in order to optimize a simplified gray-box model by using an improved Genetic Algorithm (GA), which can find the nearly-optimum solution to a given problem. The purpose of this paper is to analyze the influence of the parameters required in the implementation of the Genetic Algorithm to estimate the energy consumption in a low–energy building. The variable parameters of the model were modified trough the GA in order to obtain the minimum error between the model and measured data. The influence of the GA parameters variation over the estimation efficiency and convergence time was also analyzed.