Optimal planning of municipal-scale distributed rooftop photovoltaic systems with maximized solar energy generation under constraints in high-density cities

作者：Ren, Haoshan; Ma, Zhenjun; Chan, Antoni B.; Sun, Yongjun^*

来源：Energy, 2023, 263: 125686.

DOI：10.1016/j.energy.2022.125686

• Distributed rooftop PV
• Optimal planning
• High -density city
• Building shading effect
• Rooftop availability
• Integer linear programming

Deployment planning of distributed rooftop photovoltaic (PV) systems remains a critical challenge for high -density cities, due to complex shading effects and diversified rooftop availabilities. Furthermore, such plan-ning for large-scale systems could be extremely complex due to high dimensionality caused by the enormous number of buildings. To tackle the challenge, this study proposed an optimal planning strategy for municipal -scale distributed rooftop PV systems in high-density cities. The optimization problem was solved by integer learning programming, based on high-accuracy solar energy potentials characterization. By selecting proper rooftops for PV, the electricity generation was maximized, considering the conflicting budget and peak-export -power constraints. A Hong Kong-based case study (including 582 real building rooftops) was conducted. The effectiveness of the proposed strategy was verified by comparing with 5,000,000 Monte-Carlo-generated alter-natives. The strategy more effectively identified the proper rooftops for PV installations, achieving up to 17.7% improvements in performance-cost ratio. Furthermore, the optimal planning strategy was systematically compared with two heuristic planning methods, i.e., total-energy-prioritized and energy-intensity-prioritized methods. The strategy outperformed the heuristic methods by up to 23.3% through well considering trade-off between rooftop total energy and energy intensity. The developed strategy can be used to facilitate rooftop PV deployments, and thus contribute to urban decarbonization.