Multi-Objective Optimization of Window Configuration to Provide Integrated Visual Comfort Components and Energy Efficiency by the Genetic Algorithm (The Case Study: Primary School Classroom in Tehran- Iran)

Moving towards sustainable buildings requires more emphasis on accurate assessment of daylighting and energy performance. This is particularly important for educational buildings, because providing sufficient light while preventing the glare and reducing energy consumption in these spaces is a major challenge. In this article the main purpose is the optimized design of window configuration in terms of daylighting and energy performance in educational buildings (primary school classroom) in Tehran city to provide integrated visual comfort components (increase illuminance and decrease glare) and energy efficiency (reduced overall energy consumption). In the process of achieving this purpose the basic models of the South classroom were modeled parametricly by Grasshopper and dynamic simulation of daylight and energy was performed on them. Then simulation-based automated optimization process through the Genetic algorithm was accomplished in multi-objective.The results indicated that adjustment of the conditions with a higher weight for daylighting performance is necessary. The best Pareto solution, based on the minimum distance to the global optimum performs better than base model, indicating that improvements in UDI, DGP, and EUI purpose are 11, 15, and 22 percent respectively.