Optimal planning of building integrated photovoltaic windows through room-level economic analysis

Building-integrated photovoltaic (BIPV) window systems have significant potential to enhance energy efficiency and enable the realization of Net Zero-Energy Buildings (NZEB) in urban settings. However, their adoption is often impeded by high initial investment costs and the complex effect of surrounding buildings on performance. Accordingly, this study proposes a room-level optimal planning framework for BIPV window systems that incorporates the effects of shading and reflective radiation from surrounding buildings to maximize economic feasibility. The framework integrates energy simulations conducted with DesignBuilder and EnergyPlus, along with a genetic algorithm (GA)-based optimization model to identify the optimal type and installation timing of BIPV windows for individual rooms within a building. A case study was conducted on a 20-story residential building in Seoul, South Korea, located in a dense urban environment. The results demonstrate that the room-level optimal planning approach significantly improves economic returns by up to 20.49% compared to conventional planning methods that apply the same strategy across all rooms. The proposed framework offers practical implications for building owners, designers, and policymakers, providing a data-driven methodology to optimize BIPV adoption and support more economically viable decision-making in high-density urban environments.