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Title: Grand challenges in the science of wind energy

Journal Article · · Science
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  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Technical Univ. of Denmark, Lyngby (Denmark)
  3. ForWind - Center for Wind Energy Research, Oldenburg (Germany)
  4. Technical Univ. of Munich (Germany)
  5. Chalmers Univ. of Technology, Gothenburg (Sweden)
  6. WindForS - Wind Energy Research Cluster, Stuttgart (Germany)
  7. Recognis Oy, Espoo (Finland)
  8. Kjeller Vindteknikk Oy, Espoo (Finland)
  9. National Renewable Energy Lab. (NREL), Golden, CO (United States); Univ. of Colorado, Boulder, CO (United States)
  10. Univ. of Massachusetts, Amherst, MA (United States)
  11. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
  12. Johns Hopkins Univ., Baltimore, MD (United States)
  13. National Renewable Energy Center of Spain, Navarre (Spain)
  14. Norwegian Univ. of Science and Technology, Trondheim (Norway)
  15. Univ. of Wyoming, Laramie, WY (United States)
  16. Univ. of Colorado, Boulder, CO (United States)
  17. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  18. ForWind - Center for Wind Energy Research, Oldenburg (Germany); Univ. of Oldenburg (Germany)
  19. Energy Systems Integration Group, Reston, VA (United States)
  20. Electric Power Research Inst. (EPRI), Palo Alto, CA (United States)
  21. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Harvested by advanced technical systems honed over decades of research and development, wind energy has become a mainstream energy resource. However, continued innovation is needed to realize the potential of wind to serve the global demand for clean energy. Here, we outline three interdependent, cross-disciplinary grand challenges underpinning this research endeavor. The first is the need for a deeper understanding of the physics of atmospheric flow in the critical zone of plant operation. The second involves science and engineering of the largest dynamic, rotating machines in the world. The third encompasses optimization and control of fleets of wind plants working synergistically within the electricity grid. Addressing these challenges could enable wind power to provide as much as half of our global electricity needs and perhaps beyond.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
Grant/Contract Number:
AC36-08GO28308; AC02-05CH11231
OSTI ID:
1571388
Alternate ID(s):
OSTI ID: 1887191
Report Number(s):
NREL/JA-5000-70493; MainId:13160; UUID:1f2b65e9-c5c4-e711-9c11-2c44fd93e385; MainAdminID:1640
Journal Information:
Science, Vol. 366, Issue 6464; ISSN 0036-8075
Publisher:
AAASCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (4)

Full-scale deformation measurements of a wind turbine rotor in comparison with aeroelastic simulations text January 2020
Deep Learning-Aided Model Predictive Control of Wind Farms for AGC Considering the Dynamic Wake Effect preprint January 2020
Analytical models for the asymmetric wake of vertical axis wind turbines text January 2020
Surrogate-based aeroelastic design optimization of tip extensions on a modern 10 MW wind turbine journal January 2021

Figures / Tables (6)