Wind characteristics and wind energy potential in Morocco

Increasing knowledge on wind shear models to strengthen their reliability appears as a crucial issue, markedly for energy investors to accurately predict the average wind speed at different turbine hub heights and thus the expected wind energy output. This is particularly helpful during the feasibility study to abate the costs of a wind power project. The extrapolation laws were found to provide the finest representation of the wind speed according to heights, thus avoiding installation of tall towers, or even more expensive devices such as LIDAR or SODAR. The proposed models are based on theories that determine the vertical wind profile from implicit relationships. However, these empirical extrapolation formulas have been developed for specific meteorological conditions and appropriate sites for wind turbines; reason that several studies have been made by various authors to determine the best suited formula to their own conditions. This study is aimed at proceeding the research issue addressed within a previous study, where some extrapolation models were tested and compared by extrapolating the energy resources at different heights. However, comparable results are returned by the power law and the log law which indeed proved to be preferable. In this context, this study deals the assessment of several wind speed extrapolation laws (six laws), by comparing the analytical results obtained with real data for two different meteorological Sites, different roughness, different altitudes and different measurement periods. The first site studied is an extremely rough site with daily measurements of March 2007, wind speed measurements are available at four different heights of Gantour/Gao site, obtained by the water, energy and environment company Senegal. The second site studied is a feeble rough site with monthly measurements for 2005, wind speed measurements are available at three different heights of Kuujjuarapik Site obtained by Hydro-Quebec Energy Helimax Canada. The study aims to determine the effectiveness and concordance between the extrapolation laws and the real measured data. The results show that the adjusted law is efficiently adequate for an extremely rough site and the modified laws with two other laws are efficiently adequate for a feeble rough site. The experimental results and numerical calculations exploited for the evaluation of the Weibull parameters fall the shape factors k greater than 9. The increase in altitude often causes an increase in the Weibull parameters values, however, our results show that the shape factor k can take lower values to those established in the reference altitude.

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“…The empirical formula whose exponent is variable coefficient, depending on the roughness (Nfaoui et al, 1998), namely Equation (9) …”

Section: Variable Coefficient Lawmentioning

confidence: 99%

Evaluation of the Adequacy of the Wind Speed Extrapolation Laws for Two Different Roughness Meteorological Sites

Khalfa

Benretem

Herous

et al. 2014

American Journal of Applied Sciences

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“…The 2-parameter Weibull distribution (W2) and the Rayleigh distribution (RAY) are the pdfs that are the most commonly used in wind speed data analysis especially for studies related to wind energy estimation [35,27,42,51,45,7,16,23,36,3,2,1,25,40,10,31,43,46]. The W2 is by far the most widely used distribution to characterize wind speed.…”

Section: Introductionmentioning

confidence: 99%

Probability distributions of wind speed in the UAE

Ouarda

Charron²,

Shin³

et al. 2015

Energy Conversion and Management

197

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a b s t r a c tFor the evaluation of wind energy potential, probability density functions (pdfs) are usually used to describe wind speed distributions. The selection of the appropriate pdf reduces the wind power estimation error. The most widely used pdf for wind energy applications is the 2-parameter Weibull probability density function. In this study, a selection of pdfs are used to model hourly wind speed data recorded at 9 stations in the United Arab Emirates (UAE). Models used include parametric models, mixture models and one non-parametric model using the kernel density concept. A detailed comparison between these three approaches is carried out in the present work. The suitability of a distribution to fit the wind speed data is evaluated based on the log-likelihood, the coefficient of determination R 2 , the Chi-square statistic and the Kolmogorov-Smirnov statistic. Results indicate that, among the one-component parametric distributions, the Kappa and Generalized Gamma distributions provide generally the best fit to the wind speed data at all heights and for all stations. The Weibull was identified as the best 2-parameter distribution and performs better than some 3-parameter distributions such as the Generalized Extreme Value and 3-parameter Lognormal. For stations presenting a bimodal wind speed regime, mixture models or nonparametric models were found to be necessary to model adequately wind speeds. The two-component mixture distributions give a very good fit and are generally superior to non-parametric distributions.

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“…The monthly wind speed and solar radiation of Rabat and Essaouira sites are available at: http://eosweb.larc.nasa.gov (Surface meteorology and Solar Energy). The annual wind speed of Rabat and Essaouira are respectively equal to 3.7 and 4.47 m/s at a height of 10 m [32], further detailed descriptions of wind characteristics of the whole Moroccan territory are available in [32,33].…”

Section: Resultsmentioning

confidence: 99%