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Investigation on the spatiotemporal complementarity of wind energy resources in China

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Abstract

Wind power resources are abundant in China, especially in northern China and eastern coastal areas of China. Nevertheless, wind energy has intermittent and unstable characteristics, which leads to random power output and limits the large-scale utilization of wind energy resources. It has been shown that geographically dispersed wind plants have obvious spatiotemporal offsetting effect. Power output from each individual site exhibits the power ups and downs. However, when we simulate power lines connecting sites over a certain region, the output from them changes slowly and rarely reaches either very low or full power. Hence using the spatiotemporal complementarity of wind resources effectively is highly beneficial to the smoothing of power supply. This paper investigates the spatiotemporal complementarity of wind resources in China based on the relevant data of wind energy resources, which are offered by China Meteorological Administration (CMA).

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References

  1. Xiao L Y, Lin L Z. Construction of unified new-energy based power grid and promotion of China’s smart grid. Adv Technol Elec Eng Energy, 2009, 4: 54–59

    Google Scholar 

  2. Li J F, Shi P F, Gao H. China Wind Power Outlook 2010 (in Chinese). Haikou: Haikou Publishing House, 2010. 2–3

    Google Scholar 

  3. Wan Z H. Seven wind power bases to be set up by 2020. China Daily. Website http://www.chinadaily.com.cn/bizchina/2009-06/30/content_8335789.htm

  4. Chi Y N, Liu Y H, Wang W S, et al. Study on impact of wind power integration on power system. Power Sys Technol, 2007, 31(3): 77–81

    Google Scholar 

  5. Horne J, Flynn D, Littler T. Frequency stability issues for islanded power systems. IEEE Trans Power System, 2004, 291: 299–306

    Google Scholar 

  6. Sun T, Wang W, Dai H, et al. Voltage fluctuation and flicker caused by wind power generation. Power Sys Technol, 2003, 27(12): 62–66

    Google Scholar 

  7. Holttinen H. The impact of large scale wind power production on the Nordic electricity system. Doctoral Dissertation. Espoo: Helsinki University of Technology, 2004

    Google Scholar 

  8. Sensarma P, Padiyar K, Ramanarayanan V. Analysis and performance evaluation of a distribution STATCOM for compensating voltage fluctuations. IEEE Trans Power Delivery, 2001, 16(2): 259–264

    Article  Google Scholar 

  9. Han C, Huang A Q, Baran M E, et al. STATCOM impact study on the integration of a large wind farm into a weak loop power system. IEEE Trans Energy Conversion, 2008, 23(1): 226–233

    Article  Google Scholar 

  10. Saad-Saoud Z, Lisboa M, Ekanayake J, et al. Application of STATCOMs to wind farms. IET, 1998. 511–516.

  11. Khan M, Iqbal M. Analysis of a small wind-hydrogen stand-alone hybrid energy system. Appl Energy, 2009, 86(11): 2429–2442

    Article  Google Scholar 

  12. Ibrahim H, Ilinca A, Perron J. Energy storage systems-Characteristics and comparisons. Renewable and Sustainable Energy Rev, 2008, 12(5): 1221–1250

    Article  Google Scholar 

  13. Bullough C, Gatzen C, Jakiel C, et al. Advanced adiabatic compressed air energy storage for the integration of wind energy. European Wind Energy Conference, EWEC 2004, 2004, 22–25

    Google Scholar 

  14. Nomura S, Ohata Y, Hagita T, et al. Wind farms linked by SMES systems. IEEE Trans Appl Supercond, 2005, 15(2): 1951–1954

    Article  Google Scholar 

  15. Kahn E. The reliability of distributed wind generators. Elec Power Sys Res, 1979, 2(1): 1–14

    Article  MathSciNet  Google Scholar 

  16. Simonsen T K, Stevens B G. Regional wind energy analysis for the Central United States. Proceedings of the Global Wind Power Conference 2004. American Wind Energy Association, Washington DC, 2004. 1–16

    Google Scholar 

  17. Czisch G, Ernst B. High wind power penetration by the systematic use of smoothing effects within huge catchment areas shown in a European example. Proceedings of Windpower 2001. American Wind Energy Association, ISET, Universitat Gesamthochschule Kassel, Germany, 2001

  18. Ernst B, Wan Y, Kirby B. Short-term fluctuation of wind-turbines looking at data from the German 250 MW measurement program from the ancillary point services viewpoint. American Wind Energy Association Windpower’ 99 Conference, Washington DC, 1999

  19. Milligan M R, Factor T. Optimizing the geographic distribution of wind plants in Iowa for maximum economic benefit and reliability. Wind Eng, 2000, 24(4): 271–290

    Article  Google Scholar 

  20. Holttinen H, Hirvonen R. Power system requirements for wind power. In: Ackermann T, ed. Wind Power in Power Systems. New York: Wiley, 2005. 143–167

    Chapter  Google Scholar 

  21. DeCarolis J F, Keith D W. The economics of large-scale wind power in a carbon constrained world. Energy Policy, 2006, 34(4): 395–410

    Article  Google Scholar 

  22. Oswald J, Raine M, Ashraf-Ball H. Will British weather provide reliable electricity? Energy Policy, 2008, 36(8): 3212–3225

    Article  Google Scholar 

  23. Burton T. Wind Energy Handbook. New York: Wiley, 2001

    Book  Google Scholar 

  24. Li H Q, Wang L M. Cost estimate of carbon emission reduction of China’s wind energy and its spatiotemporal diversity (in Chinese). Geogr Sci, 2010, 30(5):651–659

    Google Scholar 

  25. Gipe P. Wind Power: Renewable Energy for Home, Farm, and Business. Chelsea: Chelsea Green Pub Co, 2003

    Google Scholar 

  26. Yu D, Liang J, Han X, et al. Profiling the regional wind power fluctuation in China. Energy Policy, 2011, 39(1): 299–306

    Article  Google Scholar 

  27. Manwell J F, McGowan J G, Rogers A L. Wind Energy Explained. Wiley Online Library, 2002

  28. Yang X, Xiao Y, Chen S. Wind speed and generated power forecasting in wind farm. Proceedings-Chin Soc Elec Eng, 2005, 25(11): 1–5

    Google Scholar 

  29. Sinden G. Characteristics of the UK wind resource: long-term patterns and relationship to electricity demand. Energy Policy, 2007, 35(1): 112–127

    Article  Google Scholar 

  30. Kempton W, Archer C L, Dhanju A, et al. Large CO2 reductions via offshore wind power matched to inherent storage in energy end-uses. Geophys Res Lett, 2007, 34(2): LO2817

    Article  Google Scholar 

  31. Hoicka C E, Rowlands I H. Solar and wind resource complementarity: Advancing options for renewable electricity integration in Ontario, Canada. Renewable Energy, 2011, 36(1): 97–107

    Article  Google Scholar 

  32. Rowlands I H, Jernigan C. Wind power in Ontario. Bull Sci, Technol & Soc, 2008, 28(6): 436–436

    Article  Google Scholar 

  33. Alexiadis M, Dokopoulos P, Sahsamanoglou H, et al. Short-term forecasting of wind speed and related electrical power. Solar Energy, 1998, 63(1): 61–68

    Article  Google Scholar 

  34. Barbounis T G, Theocharis J B, Alexiadis M C, et al. Long-term wind speed and power forecasting using local recurrent neural network models. IEEE Trans Energy Conversion, 2006, 21(1): 273–284

    Article  Google Scholar 

  35. Holttinen H. Impact of hourly wind power variations on the system operation in the Nordic countries. Wind Energy, 2005, 8(2): 197–218

    Article  Google Scholar 

  36. Ummels B C, Gibescu M, Pelgrum E, et al. Impacts of wind power on thermal generation unit commitment and dispatch. IEEE Trans Energy Conversion, 2007, 22(1): 44–51

    Article  Google Scholar 

  37. Pan Z Q. Impact of Large wind farms on peak load regulating (in Chinese). Wind Power, 1996, (1): 26–30

  38. Exell R. The wind energy potential of Thailand. Solar Energy, 1985, 35(1): 3–13

    Article  Google Scholar 

  39. Lemonsu A, Masson V. Simulation of a summer urban breeze over Paris. Boundary-Layer Meteorol, 2002, 104(3): 463–490

    Article  Google Scholar 

  40. Chen W, Zhou F, Han X Y, et al. Study of the characteristic of power load in China (in Chinese). Eco Technol Power, 2008, 20(4): 25–29

    Google Scholar 

  41. M G, Cui Y, Gan G Y. A static optimization method to determine integrated power transmission capacity of clustering wind farms. J Chinese Elec Eng Sci, 2011, 31(1): 15–18

    Google Scholar 

  42. Xiao L Y, Lin L Z. Investigations on future power drid. Adv Technol Elec Eng Energy, 2011, 30(1): 56–63

    MathSciNet  Google Scholar 

  43. Xiao L Y, Lin L Z, Liu Y. Discussions on the architecture and operation mode of future power grids. Energies, 2011, 4(7): 1025–1035

    Article  Google Scholar 

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Authors and Affiliations

  1. Key Laboratory of Applied Superconductivity, Chinese Academy of Sciences, Beijing, 100190, China

    Yi Liu, LiYe Xiao, LiangZhen Lin & ShaoTao Dai

  2. Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China

    Yi Liu, LiYe Xiao, HaiFeng Wang, LiangZhen Lin & ShaoTao Dai

  3. The Queen’s University of Belfast, Belfast, BT9 5AH, UK

    HaiFeng Wang

Authors
  1. Yi Liu
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  2. LiYe Xiao
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  3. HaiFeng Wang
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  4. LiangZhen Lin
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  5. ShaoTao Dai
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Correspondence to Yi Liu.

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Liu, Y., Xiao, L., Wang, H. et al. Investigation on the spatiotemporal complementarity of wind energy resources in China. Sci. China Technol. Sci. 55, 725–734 (2012). https://doi.org/10.1007/s11431-011-4678-4

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  • DOI: https://doi.org/10.1007/s11431-011-4678-4

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