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Trivariate maximum entropy distribution of significant wave height, wind speed and relative direction

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  • Dong, Sheng
  • Tao, Shanshan
  • Li, Xue
  • Soares, C. Guedes

Abstract

A trivariate maximum entropy distribution of significant wave height, wind speed and the relative direction is proposed here. In this joint distribution, all the marginal variables follow modified maximum entropy distributions, and they are combined by a correlation coefficient matrix based on the Nataf transformation. The methods of single extreme factors and of conditional probability are presented for the joint design of trivariate random variables. The corresponding sampling data about significant wave heights, wind speeds and the relative directions from a location in the North Atlantic is applied for statistical analysis, and the results show that the trivariate maximum entropy distribution is sufficiently good to fit the data, and method of conditional probability can reduce the design values efficiently.

Suggested Citation

  • Dong, Sheng & Tao, Shanshan & Li, Xue & Soares, C. Guedes, 2015. "Trivariate maximum entropy distribution of significant wave height, wind speed and relative direction," Renewable Energy, Elsevier, vol. 78(C), pages 538-549.
    • Handle: RePEc:eee:renene:v:78:y:2015:i:c:p:538-549
    DOI: 10.1016/j.renene.2015.01.027
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    References listed on IDEAS

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    1. Rusu, Liliana & Guedes Soares, C., 2012. "Wave energy assessments in the Azores islands," Renewable Energy, Elsevier, vol. 45(C), pages 183-196.
    2. Zhang, Jie & Chowdhury, Souma & Messac, Achille & Castillo, Luciano, 2013. "A Multivariate and Multimodal Wind Distribution model," Renewable Energy, Elsevier, vol. 51(C), pages 436-447.
    3. Rusu, Eugen & Guedes Soares, C., 2012. "Wave energy pattern around the Madeira Islands," Energy, Elsevier, vol. 45(1), pages 771-785.
    4. Portilla, Jesus & Sosa, Jeison & Cavaleri, Luigi, 2013. "Wave energy resources: Wave climate and exploitation," Renewable Energy, Elsevier, vol. 57(C), pages 594-605.
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    1. Seixas, M. & Melício, R. & Mendes, V.M.F. & Couto, C., 2016. "Blade pitch control malfunction simulation in a wind energy conversion system with MPC five-level converter," Renewable Energy, Elsevier, vol. 89(C), pages 339-350.
    2. Díaz, H. & Silva, D. & Bernardo, C. & Guedes Soares, C., 2023. "Micro sitting of floating wind turbines in a wind farm using a multi-criteria framework," Renewable Energy, Elsevier, vol. 204(C), pages 449-474.
    3. Sheng Dong & Chun-Shuo Jiao & Shan-Shan Tao, 2017. "Joint return probability analysis of wind speed and rainfall intensity in typhoon-affected sea area," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(3), pages 1193-1205, April.
    4. Ramezani, Mahyar & Choe, Do-Eun & Heydarpour, Khashayar & Koo, Bonjun, 2023. "Uncertainty models for the structural design of floating offshore wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).

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