Self-Sufficiency Building Energy Modelling from Urban to Block-Scale with PV Technology

Decarbonisation policies are often implemented in cities through the promotion of rooftop solar resources. However, urban solar assessments need to identify favourable locations and appropriate sizing to effectively support these strategies. This research aims to estimate the potential for photovoltaic (PV) systems in a dense urban context, as a basis for future policy support. The downtown district of Toronto, Ontario (Canada) is examined as a case study using the 2030 online platform. This work adopts a multi-scalar methodology to model the potential of roof-mounted PV systems for the main residential archetypes. An urban-scale GIS-LiDAR assessment, informed by environmental criteria, is followed by a block-level optimization using URBANopt, which considers energy and economic parameters. The rooftop GIS-based analysis estimates that up to 20% of electricity consumption for detached houses could be satisfied, primarily in the summer, and 5% for apartment buildings. Optimization with URBANopt shows that solar collective configurations can provide significant benefits to users, primarily in terms of economics. When optimization is performed by clusters for each block, the benefits over single-building analysis are evident, particularly in reducing lifecycle costs. In the selected case study, polycrystalline panels with net metering can achieve self-sufficiency levels ranging from 18% to 41% for residential blocks. This study confirms that solar PV systems can increase local production, reduce grid energy dependency, and support energy communities.