Architecture Engineers Award

Building Integrated Photovoltaic (BIPV) façades play a critical role in advancing net-zero and energy-positive building strategies by simultaneously serving as envelope elements and renewable energy generators. However, optimizing BIPV façades is challenging due to competing performance objectives, particularly photovoltaic energy generation and indoor daylighting quality. This study proposes a parametric optimization framework to systematically address these trade-offs during early-stage design. Challenges in Balancing Energy Generation and Daylighting Façade design decisions, such as window-to-wall ratio (WWR), directly influence solar exposure on opaque surfaces for photovoltaic efficiency while also affecting indoor daylight availability and visual comfort. Increasing PV-active areas often reduces daylight penetration, whereas excessive glazing can compromise energy generation potential. These conflicting requirements necessitate a multi-objective optimization approach. Paramet...

  Effective daylight management and visual comfort in office spaces remain crucial for occupant well-being and productivity. Traditional shading systems often fail to adapt to dynamic environmental conditions and individual preferences, leading to discomfort and energy inefficiency. This research explores AI-driven adaptive façades as a solution, integrating real-time control algorithms and predictive modeling to enhance indoor lighting quality and optimize energy usage. Problem Statement Current shading solutions in office environments are typically limited to static or manually adjustable systems. These fixed geometries cannot respond dynamically to variations in sunlight, glare, or occupant requirements. The lack of adaptability restricts optimal daylight utilization and visual comfort, highlighting the need for intelligent, real-time façade control systems that can respond to changing conditions. Methodology The study implements a real-time shading control algorithm that ...