The feasibility of electricity production via solar energy in the Middle East is high due to the enormous value of solar radiation. Building-integrated photovoltaics (BIPV) are systems used to utilise the unused spaces that can be installed on the façade or roof by replacing the building’s main element. However, the main problem associated with electricity production by BIPV is partial shading on the roof, which can produce multiple hot spots and disturbances to the system if the insolation values within the whole BIPV array vary. Partial shading, in this case, is observed due to the complexly shaped roof. This paper studies the partial shading effect on one of Qatar’s most recent projects (metro stations), and models the Education City station, which is a major station. The rooftop is complex, and it has many wavy shapes that can affect the BIPV system’s performance. The station is modelled using building-information modelling (BIM) software, wherein all of the station’s models are gathered and linked using BIM software to illustrate the BIPV and indicate the solar insolation distribution on the rooftop by simulating the station’s rooftop. The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. The outcomes from the algorithm are based on clustering the solar insolation values and then applying a genetic algorithm optimisation to indicate the optimum BIPV array layout for maximum yield.