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A methodology for the synthetic generation of hourly wind speed time series based on some known aggregate input data

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  • Carapellucci, Roberto
  • Giordano, Lorena

Abstract

The availability of hourly wind speed data is becoming increasingly important for ensuring the proper design of wind energy conversion systems. For many sites, measured series of such high resolution are incomplete or entirely lacking; hence the need for a model for synthesizing wind speed data.

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  • Carapellucci, Roberto & Giordano, Lorena, 2013. "A methodology for the synthetic generation of hourly wind speed time series based on some known aggregate input data," Applied Energy, Elsevier, vol. 101(C), pages 541-550.
    • Handle: RePEc:eee:appene:v:101:y:2013:i:c:p:541-550
    DOI: 10.1016/j.apenergy.2012.06.044
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    3. Zhang, Hua & Yu, Yong-Jing & Liu, Zhi-Yuan, 2014. "Study on the Maximum Entropy Principle applied to the annual wind speed probability distribution: A case study for observations of intertidal zone anemometer towers of Rudong in East China Sea," Applied Energy, Elsevier, vol. 114(C), pages 931-938.
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    5. Lynch & John Curtis, 2016. "The effects of wind generation capacity on electricity prices and generation costs: a Monte Carlo analysis," Applied Economics, Taylor & Francis Journals, vol. 48(2), pages 133-151, January.
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    7. Xiu, Chunbo & Wang, Tiantian & Tian, Meng & Li, Yanqing & Cheng, Yi, 2014. "Short-term prediction method of wind speed series based on fractal interpolation," Chaos, Solitons & Fractals, Elsevier, vol. 68(C), pages 89-97.
    8. Burlibaşa, A. & Ceangă, E., 2013. "Rotationally sampled spectrum approach for simulation of wind speed turbulence in large wind turbines," Applied Energy, Elsevier, vol. 111(C), pages 624-635.
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