Evaluating wind power density models and their statistical properties

Masseran, Nurulkamal

doi:10.1016/j.energy.2015.03.018

Cited by 73 publications

(32 citation statements)

References 51 publications

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“…Wind power density is considered as another critical factor in determining how much wind power (W) is available at per unit area (m 2 ) area. This can be achieved by probability distribution function [14]. The wind map of Pakistan is provided in Figure 4, where several wind classes are classified by taking wind power generation into account [13].…”

Section: Wind Data Assessmentmentioning

confidence: 99%

Wind Power Integration: An Experimental Investigation for Powering Local Communities

et al. 2019

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The incorporation of wind energy as a non-conventional energy source has received a lot of attention. The selection of wind turbine (WT) prototypes and their installation based on assessment and analysis is considered as a major problem. This paper focuses on addressing the aforementioned issues through a Weibull distribution technique based on five different methods. The accurate results are obtained by considering the real-time data of a particular site located in the coastal zone of Pakistan. Based on the computations, it is observed that the proposed site has most suitable wind characteristics, low turbulence intensity, wind shear exponent located in a safe region, adequate generation with the most adequate capacity factor and wind potential. The wind potential of the proposed site is explicitly evaluated with the support of wind rose diagrams at different heights. The energy generated by ten different prototypes will suggest the most optimum and implausible WT models. Correspondingly, the most capricious as well as optimal methods are also classified among the five Weibull parameters. Moreover, this study provides a meaningful course of action for the selection of a suitable site, WT prototype and parameters evaluation based on the real-time data for powering local communities.

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Section: Wind Data Assessmentmentioning

confidence: 99%

Wind Power Integration: An Experimental Investigation for Powering Local Communities

et al. 2019

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“…Since the PDF of output power from renewable energies are more complicated compared with traditional uncertainties [5,6], the accurate modeling of these kinds of variables is the prerequisite of system analysis. According to literature of relevant researches, the probabilistic model of output power by wind turbines is commonly transformed from wind speed model, which is characterized by Weibull distribution [4,7,8]. Researches in [9] also show that a three-parameter Burr distribution and a two-parameter lognormal distribution could describe the wind speed characteristics.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic load flow considering correlations of input variables following arbitrary distributions

Liu

Gao

Cui

et al. 2016

Electric Power Systems Research

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“…The accuracy of these distributions, characterized by their ability to fit the observed data, has a significant impact on the efficiency and uncertainty of the estimated wind energy productions at a particular site. In the literature, some well-known PDFs and CDFs, including Weibull, Rayleigh, Generalized Extreme Value, Gamma, Normal, Log-normal, Logistic, Log-logistic, and Inverse Gaussian [7][8][9][10][11][12], have been used to model the wind speed and power density distributions. For instance, Ouarda et al [7] investigated the wind speed characteristics of nine stations in UAE using eleven distribution functions.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Wind Energy Potential as a Power Generation Source: A Case Study of Eight Selected Locations in Northern Cyprus

2018

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This paper presents a techno-economic assessment of the wind power potential for eight locations distributed over the Northern part of Cyprus. The wind speed data were collected from the meteorological department located in Lefkoşa, Northern Cyprus.Ten distribution models were used to analyze the wind speed characteristics and wind energy potential at the selected locations. The maximum-likelihood method was used for calculating the parameters of the distribution functions.The power law model is utilized to determine the mean wind speed at various heights. In addition, the wind power density for each location was estimated. Furthermore, the performances of different small-scale vertical axis 3–10 kW wind turbines were evaluated to find those that were suitable and efficient for power generation in the studied locations.The results showed that the annual mean wind speed in the regions is greater than 2 m/s at a height of 10 m. Moreover, it is indicated that Generalized Extreme Value distribution provided the best fit to the actual data for the regions of Lefkoşa, Ercan, Girne, Güzelyurt, and Dipkarpaz. However, the Log-Logistic, Weibull, and Gamma distributions gave a better fit to the actual data of Gazimağusa, YeniBoğaziçi, and Salamis, respectively. The Rayleigh distribution does not fit the actual data from all regions. Furthermore, the values of wind power densityat the areas studied ranged from 38.76 W/m2 to 134.29 W/m2 at a height of 50 m, which indicated that wind energy sources in these selected locations are classified as poor. Meanwhile, based on the wind analysis, small-scale wind turbine use can be suitable for generating electricity in the studied locations. Consequently, an Aeolos-V2 with a rating of 5 kW was found to be capable of producing the annual energy needs of an average household in Northern Cyprus.

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Evaluating wind power density models and their statistical properties

Cited by 73 publications

References 51 publications

Wind Power Integration: An Experimental Investigation for Powering Local Communities

Wind Power Integration: An Experimental Investigation for Powering Local Communities

Probabilistic load flow considering correlations of input variables following arbitrary distributions

Assessment of Wind Energy Potential as a Power Generation Source: A Case Study of Eight Selected Locations in Northern Cyprus

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