Parameter estimation of weibull probability distribution by seven methods – a wind regime of the city of nitra, Slovakia

• Autorzy: Pobočíková Ivana , Sedliačková Zuzana , Michalková Mária , Jurášová Daniela

Identyfikatory

DOI

10.17512/jamcm.2024.3.06

• Języki publikacji: EN

Abstrakty

EN

Slovakia currently has a relatively large unused potential in the area of electricity production from solar radiation and wind as renewable sources. The conversion of the wind’s mechanical energy into electrical energy depends, among other things, on the wind speed and its turbulence. Perhaps the most widely used probability distribution for a wind speed model is the Weibull distribution. In the article, we deal with the comparison of seven methods for estimating the parameters of this distribution – maximum likelihood method, method of moments, empirical method, empirical method of Lysen, power density method, least squares method and weighted least squares method – on wind speed records from the city of Nitra for the period of 2005-2021. The vicinity of this city is one of the places identified as a suitable location for the installation of wind turbines. The performance of individual estimation methods is evaluated based on the indicators – the coefficient of determination R 2 and the root mean square error RMSE. Based on these values, the most accurate method is the weighted least squares method, although all other methods achieved similarly good results.

Słowa kluczowe

EN

maximum likelihood method; moment method; empirical method; power density method; least square method

PL

metoda największej wiarygodności; metoda momentów; metoda gęstości mocy; metoda najmniejszych kwadratów; metody empiryczne

• Wydawca: Wydawnictwo Politechniki Częstochowskiej
• Czasopismo: Journal of Applied Mathematics and Computational Mechanics
• Rocznik: 2024
• Tom: Vol. 23, nr 3
• Strony: 63--73
• Opis fizyczny: Bibliogr. 11 poz., tab.

Twórcy

autor

Pobočíková Ivana

• Department of Applied Mathematics, University of Žilina Žilina, Slovakia

autor

Sedliačková Zuzana

• Department of Applied Mathematics, University of Žilina Žilina, Slovakia

autor

Michalková Mária

• Department of Applied Mathematics, University of Žilina Žilina, Slovakia

autor

Jurášová Daniela

• Departmant of Building Engineering and Urban Planning, University of Žilina Žilina, Slovakia

Bibliografia

• 1. European Commision (2023). European Wind Power Action Plan, 22.
• 2. WindEurope (2024). Wind energy in Europe. 2023 Statistics and the outlook for 2024-2030, 56.
• 3. Akdag, S.A., & Dinler, A. (2009). A new method to estimate Weibull parameters for wind energy application. Energy Conversion and Management, 50, 1761-1766.
• 4. Azad, A.K., Rasul, M.G., & Yusaf, T. (2014). Statistical diagnosis of the best Weibull methods for wind power assessment for agricultural applications. Energies, 2014(7), 3056-3084.
• 5. Gungor, A., Gokcek, M., Uçar, H., Arabaci, E., & Akyüz, A. (2020). Analysis of wind energy potential and Weibull parameter estimation methods: a case study from Turkey. International Journal of Environmental Science and Technology, 17, 1011-1020.
• 6. Mohammadi, K., Alavi, O., Mostafaeipour, A., Goudarzi, N., & Jalilvand, M. (2016). Assessing different parameters estimation methods of Weibull distribution to compute wind power density. Energy Conversion and Management, 108, 322-335.
• 7. Abou El-Ela, A.A., El-Sehiemy, R.A., Shaheen, A.M., & Shalaby, A.S. (2023). Assessment of wind energy based on optimal Weibull parameters estimation using bald eagle search algorithm: case studies from Egypt. Journal of Electrical Engineering and Technology, 18(6), 4061-4078.
• 8. Akpinar, E.K., & Akpinar, S. (2004). Determination of the wind energy potential for Maden. Energy Conversion and Management, 1, 2901-2914.
• 9. Lysen, E.H. (1983). Introduction to wind energy: Basic and advanced introduction to wind energy with emphasis on water pumping mills. CWD – Consultancy Services Wind Energy Developing Countries, 310.
• 10. Pobočíková, I., & Sedliačková, Z. (2012). The least square and the weighted least square methods for estimating the Weibull distribution parameters – A comparative study. Communications – Scientific Letters of the University of Zilina, 14(4), 88-93.
• 11. Bergman, B. (1986). Estimation of Weibull parameters using a weight function. Journal of Materials Science Letters, 5, 611-614.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).