Energy Transmission Optimization in Multilayer Glass Models Using Particle Swarm Optimization

The intensification of global climate change and rising temperatures have underscored the need for energy-efficient building designs, particularly in southern China. This study proposes a particle swarm optimization (PSO) approach to optimize the thickness of triple-glazed windows (L1, L2, L3) to minimize sunlight transmission energy within the wavelength range of 300-2000 nm. A multilayer glass model was constructed, accounting for light transmission, reflection, and absorption properties. By simulating various thickness combinations, the transmitted energy was calculated across the wavelength spectrum. The PSO algorithm was then employed to search for the optimal thickness configuration that minimizes the total transmitted sunlight energy. Experimental results indicate that the proposed method significantly reduces indoor sunlight transmission compared to traditional design methods, enhancing both energy efficiency and occupant comfort. The findings highlight the importance of optimizing glass thickness and material selection in window design, balancing light transmission and shading to suit specific architectural needs. Additionally, this study underscores the impact of PSO parameters on convergence and solution diversity, suggesting further refinements for practical applications. The approach provides a scientific basis for building energy-saving designs and can be adapted to various climatic conditions and material specifications. Future work should focus on incorporating weather variations and expanding model complexity to enhance the algorithm's applicability in real-world scenarios.