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三种风力涡轮机容量系数估算方法的比较。

Comparison of three methods for wind turbine capacity factor estimation.

作者信息

Ditkovich Y, Kuperman A

机构信息

Hybrid Energy Sources Laboratory, Department of Electrical Engineering and Electronics, Ariel University Center of Samaria, 40700 Ariel, Israel.

出版信息

ScientificWorldJournal. 2014 Jan 22;2014:805238. doi: 10.1155/2014/805238. eCollection 2014.

Abstract

Three approaches to calculating capacity factor of fixed speed wind turbines are reviewed and compared using a case study. The first "quasiexact" approach utilizes discrete wind raw data (in the histogram form) and manufacturer-provided turbine power curve (also in discrete form) to numerically calculate the capacity factor. On the other hand, the second "analytic" approach employs a continuous probability distribution function, fitted to the wind data as well as continuous turbine power curve, resulting from double polynomial fitting of manufacturer-provided power curve data. The latter approach, while being an approximation, can be solved analytically thus providing a valuable insight into aspects, affecting the capacity factor. Moreover, several other merits of wind turbine performance may be derived based on the analytical approach. The third "approximate" approach, valid in case of Rayleigh winds only, employs a nonlinear approximation of the capacity factor versus average wind speed curve, only requiring rated power and rotor diameter of the turbine. It is shown that the results obtained by employing the three approaches are very close, enforcing the validity of the analytically derived approximations, which may be used for wind turbine performance evaluation.

摘要

通过一个案例研究,对计算定速风力涡轮机容量系数的三种方法进行了综述和比较。第一种“准精确”方法利用离散的风原始数据(以直方图形式)和制造商提供的涡轮机功率曲线(也是离散形式)来数值计算容量系数。另一方面,第二种“解析”方法采用连续概率分布函数,该函数拟合到风数据以及连续的涡轮机功率曲线,后者是通过对制造商提供的功率曲线数据进行双多项式拟合得到的。后一种方法虽然是一种近似方法,但可以通过解析求解,从而深入了解影响容量系数的各个方面。此外,基于该解析方法还可以得出风力涡轮机性能的其他几个优点。第三种“近似”方法仅在瑞利风情况下有效,它采用容量系数与平均风速曲线的非线性近似,只需要涡轮机的额定功率和转子直径。结果表明,采用这三种方法得到的结果非常接近,这证实了通过解析得出的近似方法的有效性,该方法可用于风力涡轮机性能评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc8/3920894/9f235fb16e30/TSWJ2014-805238.001.jpg

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