A review of wind speed probability distributions used in wind energy analysis Case studies in the Canary Islands

被引:624
作者
Carta, J. A. [1 ]
Ramirez, P. [2 ]
Velazquez, S. [3 ]
机构
[1] Univ Las Palmas Gran Canaria, Dept Mech Engn, Gran Canaria 35017, Canary Islands, Spain
[2] Technol Inst Canary Isl, Dept Renewable Energies, Gran Canaria 35119, Canary Islands, Spain
[3] Univ Las Palmas Gran Canaria, Dept Elect & Automat Engn, Gran Canaria 35017, Canary Islands, Spain
关键词
Probability density distribution; Wind power density; Coefficient of determination; Moments method; Maximum likelihood method; Least squares method; MAXIMUM-ENTROPY PRINCIPLE; STATISTICAL-ANALYSIS; WEIBULL STATISTICS; ELECTRICITY-GENERATION; OUTPUT ESTIMATION; MARKOV-CHAIN; TURBINE CHARACTERISTICS; VERTICAL EXTRAPOLATION; STOCHASTIC SIMULATION; PARAMETER-ESTIMATION;
D O I
10.1016/j.rser.2008.05.005
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The probability density function (PDF) of wind speed is important innumerous wind energy applications. A large number of studies have been published in scientific literature related to renewable energies that propose the use of a variety of PDFs to describe wind speed frequency distributions. In this paper a review of these PDFs is carried out. The flexibility and usefulness of the PDFs in the description of different wind regimes (high frequencies of null winds, unimodal, bimodal, bitangential regimes, etc.) is analysed for a wide collection of models. Likewise, the methods that have been used to estimate the parameters on which these models depend are reviewed and the degree of complexity of the estimation is analysed in function of the model selected: these are the method of moments (MM), the maximum likelihood method (MLM) and the least squares method (LSM). In addition, a review is conducted of the statistical tests employed to see whether a sample of wind data comes from a population with a particular probability distribution. With the purpose of cataloguing the various PDFs, a comparison is made between them and the two parameter Weibull distribution (W.pdf), which has been the most widely used and accepted distribution in the specialised literature on wind energy and other renewable energy sources. This comparison is based on: (a) an analysis of the degree of fit of the continuous cumulative distribution functions (CDFs) for wind speed to the cumulative relative frequency histograms of hourly mean wind speeds recorded at weather stations located in the Canarian Archipelago; (b) an analysis of the degree of fit of the CDFs for wind power density to the cumulative relative frequency histograms of the cube of hourly mean wind speeds recorded at the aforementioned weather stations. The suitability of the distributions is judged from the coefficient of determination R-2. Amongst the various conclusions obtained, it can be stated that the W.pdf presents a series of advantages with respect to the other PDFs analysed. However, the W.pdf cannot represent all the wind regimes encountered in nature such as, for example, those with high percentages of null wind speeds, bimodal distributions, etc. Therefore, its generalised use is not justified and it will be necessary to select the appropriate PDF for each wind regime in order to minimise errors in the estimation of the energy produced by a WECS (wind energy conversion system). In this sense, the extensive collection of PDFs proposed in this paper comprises a valuable catalogue. (C) 2008 Elsevier Ltd. All rights reserved.
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页码:933 / 955
页数:23
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