Comparison of Optimum Spline-Based Probability Density Functions to Parametric Distributions for the Wind Speed Data in Terms of Annual Energy Production
Munir Ali Elfarra and
Mustafa Kaya
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Munir Ali Elfarra: Department of Aeronautical Engineering, Ankara Yildirim Beyazit University, Ankara 06050, Turkey
Mustafa Kaya: Department of Aeronautical Engineering, Ankara Yildirim Beyazit University, Ankara 06050, Turkey
Energies, 2018, vol. 11, issue 11, 1-15
Abstract:
The common approach to wind energy feasibility studies is to use Weibull distribution for wind speed data to estimate the annual energy production (AEP). However, if the wind speed data has more than one mode in the probability density, the conventional distributions including Weibull fail to fit the wind speed data. This highly affects the technical and economic assessment of a wind energy project by causing crucial errors. This paper presents a novel way to define the probability density for wind speed data using splines. The splines are determined as a solution of constrained optimization problems. The constraints are the characteristics of probability density functions. The proposed method is implemented for different wind speed distributions including multimodal data and compared with Weibull, Weibull and Weibull and Beta Exponentiated Power Lindley (BEPL) distributions. It is also compared with two other nonparametric distributions. The results show that the spline-based probability density functions produce a minimum fitting error for all the analyzed cases. The AEP calculated based on this method is considered to have high fidelity, which will decrease the investment risk.
Keywords: nonparametric probability density function; Weibull distribution; Weibull and Weibull distribution; spline-based probability density function; annual energy production; multimodal wind speed data (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: 2018
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:11:p:3190-:d:183558
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