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Copula-based joint distribution analysis of wind speed and wind direction: wind energy development for Hong Kong
  • +1
  • Qiu Li,
  • Shiji Huang,
  • Zhenru Shu,
  • P.W. Chan
Qiu Li
City University of Hong Kong

Corresponding Author:[email protected]

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Shiji Huang
Central South University School of Civil Engineering
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Zhenru Shu
Central South University
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P.W. Chan
Hong Kong Observatory
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Abstract

Accurate assessment of wind energy potential can provide important implication regarding the optimalization of micro-siting of wind turbines and increase of wind power generation. It is, however, noteworthy that most previous studies on wind energy resource assessment focused solely on wind speed, whereas the dependence of wind energy on wind direction was much less considered and documented. In the current study, a copula-based method is proposed to better characterize the direction-related wind energy potential at six typical sites in Hong Kong. In the first step, several widely used statistical models are adopted to fit the marginal distributions of wind speed and direction. The joint probability density function (JPDF) of wind speed and wind direction is therewith constructed by various copula models. The goodness-of-fit evaluation indicates that Frank copula has the best performance to fit the JPDF at hilltop and offshore sites, while Gumbel copula outperforms other models at downtown sites. More importantly, the derived JPDFs are applied to estimate the direction-related wind power density at each of the considered sites, finding a maximum value of wind energy potential of 506.4 W/m2 at a hilltop site. In addition, site-to-site variability is also identified regarding the prevailing wind resource directions. The outcome of this study is expected to be useful for the site selection of wind turbines, as well as the strategic development of wind energy in Hong Kong. Notably, the proposed copula-based method can also be applied to characterize the direction-related wind energy potential somewhere other than Hong Kong.
09 Dec 2022Review(s) Completed, Editorial Evaluation Pending
10 Feb 2023Reviewer(s) Assigned
04 Mar 2023Editorial Decision: Revise Major
19 Mar 20231st Revision Received
20 Mar 2023Submission Checks Completed
20 Mar 2023Assigned to Editor
20 Mar 2023Review(s) Completed, Editorial Evaluation Pending
17 Apr 2023Reviewer(s) Assigned
02 Jun 2023Editorial Decision: Revise Minor
07 Jun 20232nd Revision Received
07 Jun 2023Submission Checks Completed
07 Jun 2023Assigned to Editor
07 Jun 2023Review(s) Completed, Editorial Evaluation Pending
09 Jun 2023Editorial Decision: Accept