Data-driven Building Integrated Photovoltaics (BIPV) envelope design optimization

The building sector's high energy consumption and greenhouse gas emissions highlight the need for renewable energy solutions, with Building Integrated Photovoltaics (BIPV) offering significant potential. BIPV integrates photovoltaic cells into building envelopes, providing energy savings, environmental benefits, and improved aesthetics. However, optimizing BIPV systems is complex due to conflicting goals like energy production, thermal performance, cost-effectiveness, and aesthetics. Current tools lack integration with building performance simulations, limiting design optimization and reliable power generation predictions. This study aims to develop a comprehensive multi-objective optimization framework for BIPV systems within a parametric Building Information Modeling (BIM) environment. The framework will address energy, thermal, electrical, and economic performance, while also considering indoor comfort and social value. It will enable detailed simulations and performance analysis, helping to optimize BIPV retrofit designs for non-residential buildings across various Australian climates. Using case studies and evaluating diverse BIPV configurations, the research will explore their impact on building performance and urban renewal. Additionally, machine learning methods will streamline the optimization process, making BIPV design more accessible and efficient. This research aims to provide a comprehensive approach to BIPV retrofits, supporting more sustainable building practices and promoting wider adoption of BIPV systems in the built environment.