This dataset translates solar irradiance into estimated daily photovoltaic energy output (kWh) for individual buildings, incorporating panel characteristics and temperature efficiency losses to deliver actionable generation estimates.
Covering approximately 16,000 footprints, the dataset provides monthly daily average PV potential values that account for panel efficiency (27%), temperature coefficient (-0.5%/°C), and optimal panel layout within each rooftop geometry. These values represent realistic generation expectations from standard mid-performance panels (0.96 x 1.64m, 300W), enabling direct comparison of building-level solar capacity across the urban area.
The dataset was created to bridge the gap between raw irradiance data and practical energy planning. By incorporating panel specifications and calculating maximum feasible panel counts per rooftop (accounting for edge setbacks and spacing), it delivers estimates directly usable for installation feasibility studies and energy self-sufficiency analysis.
Target users include building owners evaluating solar investment opportunities, property developers assessing renewable energy contributions, and municipal planners setting district-level clean energy targets. The daily average format provides accessible seasonal generation patterns without requiring specialised photovoltaic modelling software.
Estimates assume flat-mounted panels in optimal orientation and do not account for actual roof pitch, shading, or site-specific installation constraints. For hourly generation profiles needed for grid integration studies or battery sizing, reference the hourly PV potential dataset. For customised panel specifications, apply your parameters to the irradiance datasets.
Comprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in here; software stack details and calculation workflows are documented in here.