Multi-objective optimization for energy consumption, visual and thermal comfort performance of educational building (case study: Qeshm Island, Iran)

Abstract

Energy consumption in educational spaces, as one of the main consumers of fossil fuels, has been a challenging issue in recent years. The present study seeks to develop a multi-purpose approach for optimizing classrooms in the hot and humid climate of Qeshm island. Variables such as the features of window and shading devices and building orientation reduce energy consumption from energy cooling, heating energy, and electric lighting energy and increase daylight factors of UDI 100–2000 lx and sDA, which are essential for providing visual comfort. This research used PMV and PPD factors in assessing thermal comfort inside the classroom. Further, the genetic algorithm, Rhinoceros 3D software, and Grasshopper plugin were used to simulate the optimization process and achieve multi-objective optimization. The optimization showed that the sDA factor in model E has poor performance in the optimal state, accounting for only 49.26 %. Among the optimized models, model A, with 34.84 %, model B, with 34.84 %, and model F, with 33.6 %, had the highest increase in performance. Model A, with 93.66 %, and model B, with 90.26 %, have the highest UDI among optimization models, while model E, with 69.33 %, and model F, with 79.10 %, show the lowest UDI100-2000 lx in the optimization results.