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Optimal integration of offshore wind power for a steadier, environmentally friendlier, supply of electricity in China

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  • Lu, Xi
  • McElroy, Michael B.
  • Nielsen, Chris P.
  • Chen, Xinyu
  • Huang, Junling

Abstract

Demand for electricity in China is concentrated to a significant extent in its coastal provinces. Opportunities for production of electricity by on-shore wind facilities are greatest, however, in the north and west of the country. Using high resolution wind data derived from the GEOS-5 assimilation, this study shows that investments in off-shore wind facilities in these spatially separated regions (Bohai-Bay or BHB, Yangtze-River Delta or YRD, Pearl-River Delta or PRD) could make an important contribution to overall regional demand for electricity in coastal China. An optimization analysis indicates that hour-to-hour variability of outputs from a combined system can be minimized by investing 24% of the power capacity in BHB, 30% in YRD and 47% in PRD. The analysis suggests that about 28% of the overall off-shore wind potential could be deployed as base load power replacing coal-fired system with benefits not only in terms of reductions in CO2 emissions but also in terms of improvements in regional air quality. The interconnection of off-shore wind resources contemplated here could be facilitated by China's 12th-five-year plan to strengthen inter-connections between regional electric-power grids.

Suggested Citation

  • Lu, Xi & McElroy, Michael B. & Nielsen, Chris P. & Chen, Xinyu & Huang, Junling, 2013. "Optimal integration of offshore wind power for a steadier, environmentally friendlier, supply of electricity in China," Energy Policy, Elsevier, vol. 62(C), pages 131-138.
    • Handle: RePEc:eee:enepol:v:62:y:2013:i:c:p:131-138
    DOI: 10.1016/j.enpol.2013.05.106
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    References listed on IDEAS

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    1. Jiang, Dong & Zhuang, Dafang & Huang, Yaohuan & Wang, Jianhua & Fu, Jingying, 2013. "Evaluating the spatio-temporal variation of China's offshore wind resources based on remotely sensed wind field data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 142-148.
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    Cited by:

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    2. Zhang, Chongyu & Lu, Xi & Ren, Guo & Chen, Shi & Hu, Chengyu & Kong, Zhaoyang & Zhang, Ning & Foley, Aoife M., 2021. "Optimal allocation of onshore wind power in China based on cluster analysis," Applied Energy, Elsevier, vol. 285(C).
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    5. Zhang, Ning & Lu, Xi & McElroy, Michael B. & Nielsen, Chris P. & Chen, Xinyu & Deng, Yu & Kang, Chongqing, 2016. "Reducing curtailment of wind electricity in China by employing electric boilers for heat and pumped hydro for energy storage," Applied Energy, Elsevier, vol. 184(C), pages 987-994.
    6. Huber, Matthias & Weissbart, Christoph, 2015. "On the optimal mix of wind and solar generation in the future Chinese power system," Energy, Elsevier, vol. 90(P1), pages 235-243.
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    9. Bertrand Rioux, Philipp Galkin, Frederic Murphy, and Axel Pierru, 2017. "How do Price Caps in Chinas Electricity Sector Impact the Economics of Coal, Power and Wind? Potential Gains from Reforms," The Energy Journal, International Association for Energy Economics, vol. 0(KAPSARC S).
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    11. Zhao, Xin-gang & Ren, Ling-zhi, 2015. "Focus on the development of offshore wind power in China: Has the golden period come?," Renewable Energy, Elsevier, vol. 81(C), pages 644-657.
    12. Wei, Youzhou & Zou, Qing-Ping & Lin, Xianghong, 2021. "Evolution of price policy for offshore wind energy in China: Trilemma of capacity, price and subsidy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    13. Nie, Bingchuan & Li, Jiachun, 2018. "Technical potential assessment of offshore wind energy over shallow continent shelf along China coast," Renewable Energy, Elsevier, vol. 128(PA), pages 391-399.
    14. Browning, Morgan S. & Lenox, Carol S., 2020. "Contribution of offshore wind to the power grid: U.S. air quality implications," Applied Energy, Elsevier, vol. 276(C).
    15. Liao, Shiwu & Yao, Wei & Han, Xingning & Wen, Jinyu & Cheng, Shijie, 2017. "Chronological operation simulation framework for regional power system under high penetration of renewable energy using meteorological data," Applied Energy, Elsevier, vol. 203(C), pages 816-828.
    16. Lana V. L. Costa-Silva & Vinicio S. Almeida & Felipe M. Pimenta & Giovanna T. Segantini, 2017. "Time Span does Matter for Offshore Wind Plant Allocation with Modern Portfolio Theory," International Journal of Energy Economics and Policy, Econjournals, vol. 7(3), pages 188-193.

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