Multi-Objective Optimization of Building-Integrated Photovoltaics for Office Buildings in Solar-Poor Regions: Balancing Energy, Economic, and Daylighting Performance

Building-integrated photovoltaics (BIPVs) have been extensively studied in solar-rich regions, whereas the research in solar-poor regions remains limited, particularly regarding the combined assessment of economic and daylighting performance. This study investigated BIPV optimization for office buildings in solar-poor regions by jointly considering the net energy consumption (Enet), static payback period (SPP), and daylight autonomy (DA). Three representative building morphologies were identified through a cluster analysis. NSGA-II was used to generate Pareto-optimal solutions, and TOPSIS was applied to select representative compromise solutions using the building orientation (BO), window-to-wall ratio (WWR), photovoltaic transmittance (PVT), and photovoltaic coverage ratio (PVR) as the decision variables. The Pareto-optimal solutions were frequently concentrated at BO = 80–130°, WWR = 1.0, PVT = 30–40%, and PVR = 0.9–1.0. The PVR and PVT showed the strongest standardized associations with performance. Compared with the baseline cases, the representative solutions reduced the SPP by 8.34% and 11.94% for Types II and III, respectively, while Type I remained nearly unchanged. The DA increased by 4.58–15.46%. These results demonstrate morphology-dependent trade-offs and provide a transferable framework for BIPV façade optimization in solar-poor regions.