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Intelligent optimized wind resource assessment and wind turbines selection in Huitengxile of Inner Mongolia, China

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  • Dong, Yao
  • Wang, Jianzhou
  • Jiang, He
  • Shi, Xiaomeng

Abstract

The exploration of wind energy has become one of the most significant aims for countries all around the world. This is due to its low impact on the environment and its sustainable development. Therefore, it is very important to develop an effective and scientific way to evaluate wind resource potential and so that suitable wind turbines can be chosen. In this study, the 4-times daily wind speed data for the past 63years in Huitengxile of Inner Mongolia in China was collected first to do mutation tests using Sliding T-test and Sliding F-test. The test results indicated that the wind speeds exhibited a significant change in the mean value and a big variation in variance. Secondly, in order to improve the assessment accuracy, three intelligent optimization algorithms were applied to estimate Weibull’s parameters, including Particle Swarm Optimization (PSO), Differential Evolution (DE) and Genetic Algorithm (GA). Finally, some new criteria, such as matching index, turbine cost index and the integrated matching index, were proposed in order to choose the most fitting wind turbine in accordance with the local environment and economic cost.

Suggested Citation

  • Dong, Yao & Wang, Jianzhou & Jiang, He & Shi, Xiaomeng, 2013. "Intelligent optimized wind resource assessment and wind turbines selection in Huitengxile of Inner Mongolia, China," Applied Energy, Elsevier, vol. 109(C), pages 239-253.
    • Handle: RePEc:eee:appene:v:109:y:2013:i:c:p:239-253
    DOI: 10.1016/j.apenergy.2013.04.028
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    1. Jowder, Fawzi A.L., 2009. "Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrain," Applied Energy, Elsevier, vol. 86(4), pages 538-545, April.
    2. AlRashidi, M.R. & EL-Naggar, K.M., 2010. "Long term electric load forecasting based on particle swarm optimization," Applied Energy, Elsevier, vol. 87(1), pages 320-326, January.
    3. Fyrippis, Ioannis & Axaopoulos, Petros J. & Panayiotou, Gregoris, 2010. "Wind energy potential assessment in Naxos Island, Greece," Applied Energy, Elsevier, vol. 87(2), pages 577-586, February.
    4. Islam, M.R. & Saidur, R. & Rahim, N.A., 2011. "Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function," Energy, Elsevier, vol. 36(2), pages 985-992.
    5. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
    6. Ucar, Aynur & Balo, Figen, 2009. "Evaluation of wind energy potential and electricity generation at six locations in Turkey," Applied Energy, Elsevier, vol. 86(10), pages 1864-1872, October.
    7. Dahmouni, A.W. & Salah, M. Ben & Askri, F. & Kerkeni, C. & Nasrallah, S. Ben, 2010. "Wind energy in the Gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(4), pages 1303-1311, May.
    8. Yu, James & Ji, Fuxing & Zhang, Ling & Chen, Yushou, 2009. "An over painted oriental arts: Evaluation of the development of the Chinese renewable energy market using the wind power market as a model," Energy Policy, Elsevier, vol. 37(12), pages 5221-5225, December.
    9. Wang, Jianjun & Li, Li & Niu, Dongxiao & Tan, Zhongfu, 2012. "An annual load forecasting model based on support vector regression with differential evolution algorithm," Applied Energy, Elsevier, vol. 94(C), pages 65-70.
    10. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    11. Varun & Siddhartha, 2010. "Thermal performance optimization of a flat plate solar air heater using genetic algorithm," Applied Energy, Elsevier, vol. 87(5), pages 1793-1799, May.
    12. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    13. Gökçek, Murat & Genç, Mustafa Serdar, 2009. "Evaluation of electricity generation and energy cost of wind energy conversion systems (WECSs) in Central Turkey," Applied Energy, Elsevier, vol. 86(12), pages 2731-2739, December.
    14. Bekele, Getachew & Palm, Björn, 2009. "Wind energy potential assessment at four typical locations in Ethiopia," Applied Energy, Elsevier, vol. 86(3), pages 388-396, March.
    15. Akdag, S.A. & Bagiorgas, H.S. & Mihalakakou, G., 2010. "Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean," Applied Energy, Elsevier, vol. 87(8), pages 2566-2573, August.
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