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Impact of turbine technology on wind energy potential and CO2 emission reduction under different wind resource conditions in China

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  • Liu, Fa
  • Sun, Fubao
  • Wang, Xunming

Abstract

Comprehensive knowledge about wind energy potential is critical for decision-making to achieve carbon neutrality and shape future energy pathways. Wind turbine technology advances (e.g., higher hub-heights, larger rotor diameters and rated power) can better support wind energy harvesting and alter wind energy potential. This study established an integrated model to evaluate the impact of wind turbine technology advances on onshore wind energy potentials under different wind resource conditions by using China as a case study. We found that technological advances of wind turbine can significantly impact wind energy potential. Compared with land-based 1.5-MW turbines, the onshore wind energy potential using newer generation turbines (land-based 2.5-MW turbines) would increase by 43% to 14.8 PWh (i.e., 2.0 times the electricity consumption of China in 2020). Importantly, advances in wind turbine technology can significantly increase capacity factor in poor wind resource regions, and thus enable economically viable generation in more areas. This can significantly increase wind energy potential in poor wind resource regions with large electrical load (e.g., Central, South and East China). Moreover, in contrast to the wind production of 0.46 PWh in 2020, China's wind energy potential is projected to hit 20.1 PWh by 2030 under the assumption of developed turbine technology in line with the trends of the past decade. The corresponding potential CO2 emission reduction would range from 12.6 Gt in 2020 to 21.7 Gt in 2030. These values are 1.3 and 2.2 times higher than China's CO2 emissions in 2020, respectively. To enhance wind energy contribution toward China's carbon neutrality goal, we recommend that the conversion of wind turbines to be accelerated, especially in poor wind resource regions with large electrical load.

Suggested Citation

  • Liu, Fa & Sun, Fubao & Wang, Xunming, 2023. "Impact of turbine technology on wind energy potential and CO2 emission reduction under different wind resource conditions in China," Applied Energy, Elsevier, vol. 348(C).
  • Handle: RePEc:eee:appene:v:348:y:2023:i:c:s0306261923009042
    DOI: 10.1016/j.apenergy.2023.121540
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    References listed on IDEAS

    as
    1. Vu Dinh, Quang & Doan, Quang-Van & Ngo-Duc, Thanh & Nguyen Dinh, Van & Dinh Duc, Nguyen, 2022. "Offshore wind resource in the context of global climate change over a tropical area," Applied Energy, Elsevier, vol. 308(C).
    2. Mentis, Dimitrios & Hermann, Sebastian & Howells, Mark & Welsch, Manuel & Siyal, Shahid Hussain, 2015. "Assessing the technical wind energy potential in Africa a GIS-based approach," Renewable Energy, Elsevier, vol. 83(C), pages 110-125.
    3. Cuevas-Figueroa, Gabriel & Stansby, Peter K. & Stallard, Timothy, 2022. "Accuracy of WRF for prediction of operational wind farm data and assessment of influence of upwind farms on power production," Energy, Elsevier, vol. 254(PB).
    4. Sheridan, Blaise & Baker, Scott D. & Pearre, Nathaniel S. & Firestone, Jeremy & Kempton, Willett, 2012. "Calculating the offshore wind power resource: Robust assessment methods applied to the U.S. Atlantic Coast," Renewable Energy, Elsevier, vol. 43(C), pages 224-233.
    5. Siyal, Shahid Hussain & Mörtberg, Ulla & Mentis, Dimitris & Welsch, Manuel & Babelon, Ian & Howells, Mark, 2015. "Wind energy assessment considering geographic and environmental restrictions in Sweden: A GIS-based approach," Energy, Elsevier, vol. 83(C), pages 447-461.
    6. Martin, Sean & Jung, Sungmoon & Vanli, Arda, 2020. "Impact of near-future turbine technology on the wind power potential of low wind regions," Applied Energy, Elsevier, vol. 272(C).
    7. Liu, Fa & Sun, Fubao & Liu, Wenbin & Wang, Tingting & Wang, Hong & Wang, Xunming & Lim, Wee Ho, 2019. "On wind speed pattern and energy potential in China," Applied Energy, Elsevier, vol. 236(C), pages 867-876.
    8. Leite, Gustavo de Novaes Pires & Weschenfelder, Franciele & Farias, João Gabriel de & Kamal Ahmad, Muhammad, 2022. "Economic and sensitivity analysis on wind farm end-of-life strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    9. Liu, Fa & Wang, Xunming & Sun, Fubao & Kleidon, Axel, 2023. "Potential impact of global stilling on wind energy production in China," Energy, Elsevier, vol. 263(PB).
    10. Christopher Jung & Dirk Schindler, 2022. "Development of onshore wind turbine fleet counteracts climate change-induced reduction in global capacity factor," Nature Energy, Nature, vol. 7(7), pages 608-619, July.
    11. Hong, Lixuan & Möller, Bernd, 2011. "Offshore wind energy potential in China: Under technical, spatial and economic constraints," Energy, Elsevier, vol. 36(7), pages 4482-4491.
    12. Katinas, Vladislovas & Gecevicius, Giedrius & Marciukaitis, Mantas, 2018. "An investigation of wind power density distribution at location with low and high wind speeds using statistical model," Applied Energy, Elsevier, vol. 218(C), pages 442-451.
    13. Erkka Rinne & Hannele Holttinen & Juha Kiviluoma & Simo Rissanen, 2018. "Effects of turbine technology and land use on wind power resource potential," Nature Energy, Nature, vol. 3(6), pages 494-500, June.
    14. Wais, Piotr, 2017. "A review of Weibull functions in wind sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1099-1107.
    15. Gass, Viktoria & Schmidt, Johannes & Strauss, Franziska & Schmid, Erwin, 2013. "Assessing the economic wind power potential in Austria," Energy Policy, Elsevier, vol. 53(C), pages 323-330.
    16. Michael R. Davidson & Da Zhang & Weiming Xiong & Xiliang Zhang & Valerie J. Karplus, 2016. "Modelling the potential for wind energy integration on China’s coal-heavy electricity grid," Nature Energy, Nature, vol. 1(7), pages 1-7, July.
    17. Obane, Hideaki & Nagai, Yu & Asano, Kenji, 2020. "Assessing land use and potential conflict in solar and onshore wind energy in Japan," Renewable Energy, Elsevier, vol. 160(C), pages 842-851.
    18. Tu, Qiang & Betz, Regina & Mo, Jianlei & Fan, Ying, 2019. "The profitability of onshore wind and solar PV power projects in China - A comparative study," Energy Policy, Elsevier, vol. 132(C), pages 404-417.
    19. Lopez, Anthony & Mai, Trieu & Lantz, Eric & Harrison-Atlas, Dylan & Williams, Travis & Maclaurin, Galen, 2021. "Land use and turbine technology influences on wind potential in the United States," Energy, Elsevier, vol. 223(C).
    20. Franke, Katja & Sensfuß, Frank & Deac, Gerda & Kleinschmitt, Christoph & Ragwitz, Mario, 2021. "Factors affecting the calculation of wind power potentials: A case study of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    21. McKenna, R. & Hollnaicher, S. & Ostman v. d. Leye, P. & Fichtner, W., 2015. "Cost-potentials for large onshore wind turbines in Europe," Energy, Elsevier, vol. 83(C), pages 217-229.
    22. Wang, Qiang & Luo, Kun & Yuan, Renyu & Zhang, Sanxia & Fan, Jianren, 2019. "Wake and performance interference between adjacent wind farms: Case study of Xinjiang in China by means of mesoscale simulations," Energy, Elsevier, vol. 166(C), pages 1168-1180.
    23. Mentis, Dimitrios & Siyal, Shahid Hussain & Korkovelos, Alexandros & Howells, Mark, 2016. "A geospatial assessment of the techno-economic wind power potential in India using geographical restrictions," Renewable Energy, Elsevier, vol. 97(C), pages 77-88.
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