Canadian Solar Capacity Sizing Maps: A high-resolution open dataset for PV and battery storage design (564 CWEEDS Stations)
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Solar Capacity Sizing Maps and Reliability Metrics for Canada (CWEEDS 564 Stations) This comprehensive open-access dataset provides high-resolution solar photovoltaic (PV) capacity sizing maps and detailed performance metrics for all 564 Canadian weather stations in the Canadian Weather Energy and Engineering Datasets (CWEEDS). Going beyond conventional annual solar irradiance maps, this dataset delivers practical engineering guidance for solar-plus-storage system design by integrating hourly meteorological data, battery storage dynamics, and a statistical reliability framework. It is specifically designed to support renewable energy engineers, microgrid developers, and researchers developing AI-driven sizing tools. Key Features Complete national coverage across all 564 CWEEDS stations Six key performance metrics for every station and every possible PV orientation (tilt 0–90°, azimuth 0–360°): Capacity Ratio (C<sub>r</sub>) Storage Ratio (S<sub>r</sub>) Excess Ratio (E<sub>r</sub>) Battery Cycling Ratio (B<sub>c</sub>) Average charging C-rate (Bc<sub>c</sub>) Average discharging C-rate (Bc<sub>d</sub>) Six reliability levels (5/8σ to 3σ), corresponding to load fulfillment from ~46% to 99.97% Annual and monthly results included High-resolution visual maps (PDF) with contour plots for every station Machine-readable tabulated data (Excel/CSV) optimized for analysis and AI training Full reproducible Python source code (using pvlib) for transparency and adaptability Content of This Upload Complete dataset for all 564 Canadian stations High-resolution PDF maps (annual + monthly) Tabulated performance metrics Sample detailed results for Winnipeg International Airport (included as demonstration) Complete Python source code and documentation This resource enables users to quickly determine optimal PV and battery sizes required to meet specific reliability targets for any location in Canada. It serves as a valuable tool for solar microgrid design, techno-economic analysis, energy policy planning, and the development of next-generation AI renewable energy design agents. Citation If you use this code or the derived maps in your work, please cite the original paper (will be updated later this year when accepted for publication): Agyei-Agyemang, K.H., Bibeau, E.L. (2026). Worldwide mapping of solar resources to support the design process of microgrids: open‑access methodology and capacity sizing maps for Canada. Mechanical Engineering Department, University of Manitoba. Authors: Kwasi H. Agyei-Agyemang, Eric L. Bibeau Version: 1.0 Date: April 2026
