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An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset

Author

Listed:
  • Madeleine McPherson

    (Department of Civil Engineering, University of Toronto, 35 St. George Street, Toronto, ON M5S 1A4, Canada)

  • Theofilos Sotiropoulos-Michalakakos

    (Department of Civil Engineering, University of Toronto, 35 St. George Street, Toronto, ON M5S 1A4, Canada)

  • LD Danny Harvey

    (Department of Geography, University of Toronto, 100 St. George Street, Toronto, ON M5S 3G3, Canada)

  • Bryan Karney

    (Department of Civil Engineering, University of Toronto, 35 St. George Street, Toronto, ON M5S 1A4, Canada)

Abstract

Wind and solar energy resources are an increasingly large fraction of generation in global electricity systems. However, the variability of these resources necessitates new datasets and tools for understanding their economics and integration in electricity systems. To enable such analyses and more, we have developed a free web-based tool (Global Renewable Energy Atlas & Time-series, or GRETA) that produces hourly wind and solar photovoltaic (PV) generation time series for any location on the globe. To do so, this tool applies the Boland–Ridley–Laurent and Perez models to NASA’s (National Aeronautics and Space Administration) Modern-Era Retrospective Analysis for Research and Applications (MERRA) solar irradiance reanalysis dataset, and the Archer and Jacobson model to the MERRA wind reanalysis dataset to produce resource and power data, for a given technology’s power curve. This paper reviews solar and wind resource datasets and models, describes the employed algorithms, and introduces the web-based tool.

Suggested Citation

  • Madeleine McPherson & Theofilos Sotiropoulos-Michalakakos & LD Danny Harvey & Bryan Karney, 2017. "An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset," Energies, MDPI, vol. 10(7), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:1007-:d:104865
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    2. Kena Likassa Nefabas & Lennart Söder & Mengesha Mamo & Jon Olauson, 2021. "Modeling of Ethiopian Wind Power Production Using ERA5 Reanalysis Data," Energies, MDPI, vol. 14(9), pages 1-17, April.
    3. McPherson, Madeleine & Ismail, Malik & Hoornweg, Daniel & Metcalfe, Murray, 2018. "Planning for variable renewable energy and electric vehicle integration under varying degrees of decentralization: A case study in Lusaka, Zambia," Energy, Elsevier, vol. 151(C), pages 332-346.
    4. McPherson, Madeleine & Tahseen, Samiha, 2018. "Deploying storage assets to facilitate variable renewable energy integration: The impacts of grid flexibility, renewable penetration, and market structure," Energy, Elsevier, vol. 145(C), pages 856-870.
    5. Lim, Kai Zhuo & Lim, Kang Hui & Wee, Xian Bin & Li, Yinan & Wang, Xiaonan, 2020. "Optimal allocation of energy storage and solar photovoltaic systems with residential demand scheduling," Applied Energy, Elsevier, vol. 269(C).
    6. Arjmand, Reza & Monroe, Jacob & McPherson, Madeleine, 2023. "The role of emerging technologies in Canada's electricity system transition," Energy, Elsevier, vol. 278(PA).
    7. Miri, Mohammad & McPherson, Madeleine, 2024. "Demand response programs: Comparing price signals and direct load control," Energy, Elsevier, vol. 288(C).
    8. Olauson, Jon, 2018. "ERA5: The new champion of wind power modelling?," Renewable Energy, Elsevier, vol. 126(C), pages 322-331.

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