Multi-objective optimization of office building envelopes properties and Venetian blinds using NSGA-II to save energy consumption and enhance thermal and visual comfort

Abstract

Since the building industry has grown to be a significant energy user, offering practical solutions can aid in addressing this significant problem. Windows are among the most crucial architectural elements since they let in the majority of the natural light that enters the structure. On the one hand, improper window and associated component design causes the space to overheat and consume more energy; on the other hand, it compromises the inhabitants of the building's thermal and visual comfort. This research presents a novel method for multi-objective optimization of control parameters for smart shade curtains and architectural standards. By using this suggested method, building energy consumption is significantly reduced and thermal and visual comfort are improved. EnergyPlus software is used to run simulations about energy. Subsequently, JEPLUS software has considered 28 design aspects, such as hour groove angle, building cover requirements, material dimensions and specifications, control techniques and adjustment points, and shading position and direction. These simulations are run for nine cities with varying climates in four distinct geographic orientations throughout the year. The program JEPLUS + EA is utilized for data improvement. To extract the ideal points on the Pareto front, the data is optimized using the NSGA-II algorithm. The optimization findings indicate that the inner curtain outperforms the outside curtain. Additionally, the visual comfort improves with a narrower slat angle (SA), but the illumination requires more power. The multi-objective optimization of the controlled blind characteristics yielded results that, depending on the building's geographical orientation, reduced the building's overall energy consumption by 4–30 % annually while improving thermal and visual comfort, with ranges of 64–11 % and 60–81 %, respectively.