Simulation and Optimization Research on Photovoltaic Power Generation in Rural Office Buildings in Hot Summer and Cold Winter Regions

Against the backdrop of rural energy transitions and the large-scale implementation of Building-Integrated Photovoltaics (BIPV), the photovoltaic (PV) design for rural office buildings in hot summer and cold winter regions faces a conflict between maximizing power generation and minimizing net energy consumption, along with a lack of refined multi-objective optimization frameworks. Taking a typical rural double-sloped-roof office building in the Jianghan Plain as the research subject, this study establishes a multi-objective optimization framework that integrates parametric modeling and a multi-objective genetic algorithm to obtain a Pareto-optimal solution set. Three scenarios—no PV, the original design, and the optimized design—were simulated and compared. The results indicate that: (1) The optimal installation parameters are a 27° tilt angle and an 18° east-of-south azimuth. Compared to the original design, the optimized system increases the average annual power generation by 56% (from 8.9 × 104 kWh to 13.7 × 104 kWh). (2) The optimized design reduces the building’s net energy consumption to −9.86 × 104 kWh, achieving a comprehensive energy-saving rate of 288.11%, significantly outperforming the original design’s 179.76%. (3) This synergistic design enables the building to completely eliminate grid dependence, achieving energy self-sufficiency and a net energy surplus. This study provides a scientific reference for the refined BIPV design and low-carbon retrofitting of rural public buildings in similar climatic zones.