Next-generation window design: Multi-criteria optimization for energy efficiency and comfort using improved thermal exchange optimization algorithm and DesignBuilder

Abstract

The strategic design of windows to increase a building's energy efficiency is critical for maximizing overall performance. To achieve the best results in reducing energy consumption, it is necessary to thoroughly investigate various issues related to window design. The determinants include the positioning of windows, the composition of the glass used, and the proportions of the windows. Consequently, it is critical to construct a comprehensive optimization strategy to effectively balance the interrelated aspects and generate an energy-efficient final design that provides a comfortable indoor atmosphere and meets the visual performance standards for the building. The present study utilized the Improved Thermal Exchange Optimization Algorithm through the DesignBuilder software for multi-objective optimization. Various parameters are investigated to determine their efficacy, and the Pareto technique is used to identify the most advantageous options. An initial examination of Pareto-optimum solutions is performed to highlight the orientation-related window parameters’ distribution. The study involves evaluating a model in a professional office setting, modifying window characteristics, and considering three unique design objectives. According to the findings, the proposed strategy produces the lowest annual average energy usage (70.4) for lighting, cooling, and heating. The current study's findings outperform those of earlier studies, indicating that the proposed model is more accurate and reliable.