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Global riverine theoretical hydrokinetic resource assessment

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  • Ridgill, Michael
  • Neill, Simon P.
  • Lewis, Matt J.
  • Robins, Peter E.
  • Patil, Sopan D.

Abstract

Hydrokinetic energy conversion refers to the conversion of kinetic energy in moving water to electricity. It offers an alternative to conventional hydropower, with benefits of modularity and scalability, in addition to being environmentally and socially less impactful. This study aims to determine the theoretical global riverine hydrokinetic resource. We use a 35 year modelled daily discharge data set and vectorised representation of rivers, with near-global coverage and suitable spatiotemporal resolution, to determine the mean annual energy yield of 2.94 million river reaches. The mean global resource (excluding Greenland) is estimated to be 58 400±109 TWh yr−1 (6.660±0.012 TW). Consideration of global spatial distribution, by river reach, illustrates regional variation and shows a tendency for potential to be concentrated along major rivers and in areas of significant elevation change. China, Russia and Brazil are found to be the countries with the greatest potential. After normalisation by total river length, Bhutan, Nepal and Tajikistan also show great potential. Hydrokinetic energy conversion can benefit isolated communities currently without access to electricity. We consider how the specific advantages of this particular technology have the potential to be combined with and complement other established forms of renewable energy technology, providing the means to support the reduction of energy poverty.

Suggested Citation

  • Ridgill, Michael & Neill, Simon P. & Lewis, Matt J. & Robins, Peter E. & Patil, Sopan D., 2021. "Global riverine theoretical hydrokinetic resource assessment," Renewable Energy, Elsevier, vol. 174(C), pages 654-665.
    • Handle: RePEc:eee:renene:v:174:y:2021:i:c:p:654-665
    DOI: 10.1016/j.renene.2021.04.109
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    3. MacMillan, Andrew & Schell, Kristen R. & Roughley, Colter, 2023. "A predictive model of velocity for local hydrokinetic power assessment based on remote sensing data," Renewable Energy, Elsevier, vol. 211(C), pages 285-295.

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