City-scale roof-top photovoltaic deployment planning

Under the trends towards large-scale utilization of renewable energy in cities, Distributed Solar Photovoltaic (DSPV) systems installed on roof-tops are gradually attracting more attention as a solution for urban building renovations in China. For a mega city, strategically planning the deployment of numerous scattered DSPV systems is essential due to the long deployment cycle and complex decision-making factors involved. In this study, a city-scale PV deployment decision-making model is proposed. The K-medoid algorithm is used to conduct a multi-step urban unit clustering process based on morphology features. Six indicator categories, including initial PV condition, hourly matching degree, flexible resource dependency, installation scheme stability, deployment difficulty, and ground development potential, are evaluated to assess the deployment potential. The Analytic Hierarchy Process (AHP) and entropy method are employed to comprehensively rank all urban unit clusters and make pilot deployment decisions. A case study is conducted in Shenzhen, China, where 4687 urban units comprising 577,648 buildings are effectively clustered into 30 typical urban units. If the deployment targets of 20%, 40%, 60%, 80% and 100% are pursued, the distribution trend across the city shows the deployment direction from the urban units of more in the north and suburbs, near parks, and less in the high-density urban center. These deployment targets can respectively meet 4.1%, 8.39%, 12.08%, 16.39% and 20.06% of the city's electricity demand.