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An improved global wind resource estimate for integrated assessment models

Author

Listed:
  • Eurek, Kelly
  • Sullivan, Patrick
  • Gleason, Michael
  • Hettinger, Dylan
  • Heimiller, Donna
  • Lopez, Anthony

Abstract

This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5MW composite wind turbines with 90m hub heights, 0.95 availability, 90% array efficiency, and 5MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

Suggested Citation

  • Eurek, Kelly & Sullivan, Patrick & Gleason, Michael & Hettinger, Dylan & Heimiller, Donna & Lopez, Anthony, 2017. "An improved global wind resource estimate for integrated assessment models," Energy Economics, Elsevier, vol. 64(C), pages 552-567.
    • Handle: RePEc:eee:eneeco:v:64:y:2017:i:c:p:552-567
    DOI: 10.1016/j.eneco.2016.11.015
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    References listed on IDEAS

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    1. Hoogwijk, Monique & de Vries, Bert & Turkenburg, Wim, 2004. "Assessment of the global and regional geographical, technical and economic potential of onshore wind energy," Energy Economics, Elsevier, vol. 26(5), pages 889-919, September.
    2. Leemis, Lawrence M. & McQueston, Jacquelyn T., 2008. "Univariate Distribution Relationships," The American Statistician, American Statistical Association, vol. 62, pages 45-53, February.
    3. Global Energy Assessment Writing Team,, 2012. "Global Energy Assessment," Cambridge Books, Cambridge University Press, number 9781107005198.
    4. Global Energy Assessment Writing Team,, 2012. "Global Energy Assessment," Cambridge Books, Cambridge University Press, number 9780521182935.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Wind; Supply curve; Resource assessment; Technical potential; Integrated assessment model; Global;
    All these keywords.

    JEL classification:

    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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