Photovoltaic material selection and multi-objective building design optimization for enhancing energy performance of building integrated photovoltaics (BIPV) systems

Building-integrated photovoltaic (BIPV) systems hold significant potential for on-site renewable energy generation, reducing reliance on grid-supplied energy and lowering carbon emissions from building operations. Despite these advantages, BIPV systems have rarely been leveraged to inform architectural design or comprehensively evaluated when incorporating diverse solar cell technologies. This study systematically analyzes five photovoltaic materials for BIPV applications, including crystalline silicon (Si), cadmium telluride (CdTe), copper indium gallium selenide (CIGS), perovskite, and organic solar cells. A multi-objective optimization framework is employed to determine optimal building design parameters, including window-to-wall ratio (WWR), orientation, aspect ratio, and roof tilt angle. Results reveal that the most energy-efficient BIPV system combines Si solar cells for roofs, CdTe for walls, and perovskite for windows. The minimization of optimal WWR is preferred under the state-of-the-art PV technologies. Contrary to the conventional design of individual PV panels (south-facing with a tilt angle matching local latitude), the highest power generation for BIPV systems is achieved when the building's long axis and roof are oriented southwest, with the roof tilt angle adjusted within ±10° of local latitude. Optimization enhances the system's power generation by an average of 16.6 % and reduces net energy consumption by 17.4 %. If implemented in the design of newly constructed buildings across China, this strategy could reduce CO 2 emissions by over 805 million tons annually. • A novel method is proposed to optimally select PV materials for different BIPV envelope components. • A multi-objective BIPV optimization framework using four design variables is developed based on Iterated Local Search (ILS). • The optimized strategies are estimated to increase power generation by 16.6 % and reduce net energy usage by 17.4 % in China.