Joint distribution of wind speed and direction over complex terrains based on nonparametric copula models

Wang, Hanyu; Xiao, Ting; Gou, Hongye; Pu, Qianhui; Bao, Yi

doi:10.1016/j.jweia.2023.105509

Cited by 7 publications

(1 citation statement)

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“…Carnicero et al illustrated the Bernstein Copula-based circular–linear and circular–circular modeling approaches using two cases, one of the relationship between wind direction and precipitation, and the other between the wind directions of two adjacent buoys [ 36 ]. In a recent study [ 37 ], the nonparametric Bernstein copula was used to construct a JPDF of wind speed and direction, where the order of the model was deter-mined by a stepwise search strategy combined with the cube root of the sample size recommended by Sancetta and Satchell. The model accurately describes the prevailing wind direction in complex wind environments and, in addition, the EBC method provides desired JPDF accuracy when the marginal distributions are poorly represented.…”

Section: Introductionmentioning

confidence: 99%

A Circular-Linear Probabilistic Model Based on Nonparametric Copula with Applications to Directional Wind Energy Assessment

Liu,

Yan

2024

Entropy

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The joint probability density function of wind speed and wind direction serves as the mathematical basis for directional wind energy assessment. In this study, a nonparametric joint probability estimation system for wind velocity and direction based on copulas is proposed and empirically investigated in Inner Mongolia, China. Optimal bandwidth algorithms and transformation techniques are used to determine the nonparametric copula method. Various parameter copula models and models without considering dependency relationships are introduced and compared with this approach. The results indicate a significant advantage of employing the nonparametric copula model for fitting joint probability distributions of both wind speed and wind direction, as well as conducting correlation analyses. By utilizing the proposed KDE-COP-CV model, it becomes possible to accurately and reliably analyze how wind power density fluctuates in relation to wind direction. This study reveals the researched region possesses abundant wind resources, with the highest wind power density being highly dependent on wind direction at maximum speeds. Wind resources in selected regions of Inner Mongolia are predominantly concentrated in the northwest and west directions. These findings can contribute to improving the accuracy of micro-siting for wind farms, as well as optimizing the design and capacity of wind turbine generators.

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Section: Introductionmentioning

confidence: 99%