This paper provides a brief introduction to building integrated photovoltaic (BIPV). It utilized a particle swarm algorithm to optimize the arrangement scheme of the photovoltaic array on a concrete flat roof. Furthermore, the performance of the particle swarm algorithm was improved through a genetic algorithm (GA). Subsequently, an experimental analysis was conducted using an office building in a joint salinization factory in Henan Province. First, the effectiveness of the building energy model constructed using PKPM-Energy and Daysim software was validated. Then, a comparison was made between the GA, the particle swarm algorithm, and the improved particle swarm algorithm. The results indicated that the building energy consumption model constructed by the simulation software calculated the building's energy consumption effectively, which was used to guide the optimization algorithm. All three optimization algorithms successfully optimized the initial scheme. Moreover, the improved particle swarm algorithm exhibited the best optimization performance among the three algorithms.