Performance Comparison of New Generation Parameter Estimation Methods for Weibull Distribution to Compute Wind Energy Density

Authors

  • Ahmet Emre Onay Department of Energy Systems Engineering, Bilecik S. E. University, Turkey
  • Emrah Dokur Department of Electrical Electronics Engineering, Bilecik S. E. University, Turkey
  • Mehmet Kurban Department of Electrical Electronics Engineering, Bilecik S. E. University, Turkey

DOI:

https://doi.org/10.5755/j02.eie.28919

Keywords:

Wind energy, Estimation methods, Weibull distribution, Wind energy intensification

Abstract

To install a wind energy conversion system to a region, the wind speed characteristics of that region must be identified. The two-parameter Weibull distribution is highly efficient in modeling wind speed characteristics. In this study, the wind speed data of 32 cities in three different regions of Turkey have been comparatively analysed to estimate Weibull distribution function parameters by the use of three well-known methods (Graphical Method (GM), Maximum Likelihood Method (MLM), Justus Moment Method (JMM)) and three new parameter estimation methods (Energy Pattern Factor Method (EPFM), Wind Energy Intensification Method (WEIM), Power Density Method (PD)) which have been proposed in recent years. Three years of hourly wind speed data of the specified regions have been used. The performance metrics of these analyses have been compared using Wind Energy Error (WEE), Root Mean Square Error (RMSE), and Coefficient of Determination (R2). The results have shown that while the PD method has high model performance, the JMM is closely competitive with the MLM. Besides, the wind energy densities that were estimated by using actual data have been compared with the resulting Weibull distribution. It has been clear that the method that has the closest estimation to the actual values is the PD method.

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Published

2021-09-08

How to Cite

Onay, A. E., Dokur, E., & Kurban, M. (2021). Performance Comparison of New Generation Parameter Estimation Methods for Weibull Distribution to Compute Wind Energy Density. Elektronika Ir Elektrotechnika, 1(1). https://doi.org/10.5755/j02.eie.28919

Issue

Section

RENEWABLE ENERGY