Evaluation of wind energy potential: a case study

ABSTRACT

In this study, the wind energy potential of the Kırklareli University Kayalı Campus at a height of 100 meters has been evaluated by using statistical distribution methods. The parameters of the distributions were calculated by Moment and Maximum Likelihood (MLE) methods. As a result of the goodness of fit tests, the Rayleigh MLE method was estimated the most suitable model among the statistical distributions examined. According to the annual mean results estimated by applying the Rayleigh MLE method; the scale parameter, the wind speed, the standard deviation, and the power density were found as 7.15 m/s, 6.34 m/s, 3.31 m/s and 322 $\mathrm{W}/{\mathrm{m}}^2$, respectively. The annual dominant wind direction was determined as the Northeast, (NE) with 1407 hours of blowing. It is suggested that the most suitable turbine for the location is the GE103 model, estimated to generate 7.270 GWh of electrical energy annually.

KEYWORDS:

• Wind energy potential
• Weibull distribution
• parameter estimation
• annual wind energy production
• wind turbine micrositing

Nomenclature

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Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Notes on contributors

Bekir Adem Çakmakçı

Bekir Adem Çakmakçı is a research assistant in the Department of Energy Systems Engineering at the Kırklareli University (Turkey). His research areas focus on the analysis and applications of renewable energy systems and thermal systems.

Engin Hüner

Engin Hüner is an assistant professor in the Department of Energy Systems Engineering at the Kırklareli University (Turkey). He completed a bachelor’s, master and Ph.D. degree in Electrical Education of Abant İzzet Baysal University, Electronical Engineering of Gebze High Technology Institute, and Electrical Education of Marmara University, respectively. His research areas mainly focus on electrical machines and renewable energy systems.