A Comparative Study on Wind Energy Assessment Distribution Models: A Case Study on Weibull Distribution

Hanifa Teimourian, Mahmoud Abubakar, Melih Yildiz and Amir Teimourian ()
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Hanifa Teimourian: Department of Electrical Engineering, Faculty of Engineering, University of Near East, Northern Cyprus, Via Mersin 10, Lefkosa 99138, Turkey
Mahmoud Abubakar: Department of Aeronautical Engineering, Faculty of Aviation and Space Sciences, University of Kyrenia, Northern Cyprus, Via Mersin 10, Girne 99320, Turkey
Melih Yildiz: Department of Aeronautical Engineering, Faculty of Aviation and Space Sciences, Erciyes University, Kayseri 38280, Turkey
Amir Teimourian: Department of Aeronautical Engineering, Faculty of Aviation and Space Sciences, University of Kyrenia, Northern Cyprus, Via Mersin 10, Girne 99320, Turkey

Energies, 2022, vol. 15, issue 15, 1-15

Abstract: Wind power generation highly depends on the determination of wind power potential, which drives the design and feasibility of the wind energy production investment. This gives an important role to wind power estimation, which creates the need for an accurate wind data analysis and wind energy potential assessments for a given location. Such assessments require the implementation of an accurate and suitable wind distribution model. Therefore, in the quest for a well-fitted model, eight methods for estimating the Weibull parameters are investigated in this paper. The methods were then investigated by employing statistical tools, and their performances have been discussed in terms of various error indicators such as root mean squared error (RMSE), regression error (R2), chi-square (X2), and mean absolute error (MAE). Meteorological data for diverse terrain from 14 provinces with 30 sites scattered across Iran were employed to examine the performance of the investigated methods. The results demonstrated that the empirical method has superiority over the investigated technique in terms of errors.

Keywords: Weibull distribution; parameter estimation; empirical method; maximum likelihood method; energy pattern factor (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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