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An Approach to Determine the Weibull Parameters for Wind Energy Analysis: The Case of Galicia (Spain)

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Cited by:

  1. Ewa Chomać-Pierzecka & Anna Sobczak & Dariusz Soboń, 2022. "Wind Energy Market in Poland in the Background of the Baltic Sea Bordering Countries in the Era of the COVID-19 Pandemic," Energies, MDPI, vol. 15(7), pages 1-21, March.
  2. Wang, Jianzhou & Huang, Xiaojia & Li, Qiwei & Ma, Xuejiao, 2018. "Comparison of seven methods for determining the optimal statistical distribution parameters: A case study of wind energy assessment in the large-scale wind farms of China," Energy, Elsevier, vol. 164(C), pages 432-448.
  3. Sunoh Kim & Jin Hur, 2020. "Probabilistic Approaches to the Security Analysis of Smart Grid with High Wind Penetration: The Case of Jeju Island’s Power Grids," Energies, MDPI, vol. 13(21), pages 1-13, November.
  4. Isabel Cristina Gil-García & María Socorro García-Cascales & Angel Molina-García, 2022. "Urban Wind: An Alternative for Sustainable Cities," Energies, MDPI, vol. 15(13), pages 1-20, June.
  5. Kim, SunOh & Hur, Jin, 2021. "Probabilistic power output model of wind generating resources for network congestion management," Renewable Energy, Elsevier, vol. 179(C), pages 1719-1726.
  6. Degiuli, Nastia & Runje, Biserka & Farkas, Andrea, 2017. "Statistical Analysis of Wind Speed for the Probability Evaluation of Cancelled Departure for Catamarans and Ferries," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2017), Dubrovnik, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Dubrovnik, Croatia, 7-9 September 2017, pages 340-350, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
  7. Mónica Borunda & Katya Rodríguez-Vázquez & Raul Garduno-Ramirez & Javier de la Cruz-Soto & Javier Antunez-Estrada & Oscar A. Jaramillo, 2020. "Long-Term Estimation of Wind Power by Probabilistic Forecast Using Genetic Programming," Energies, MDPI, vol. 13(8), pages 1-24, April.
  8. Manzoor Ellahi & Ghulam Abbas & Irfan Khan & Paul Mario Koola & Mashood Nasir & Ali Raza & Umar Farooq, 2019. "Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review," Energies, MDPI, vol. 12(22), pages 1-30, November.
  9. Dongbum Kang & Kyungnam Ko & Jongchul Huh, 2018. "Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea," Energies, MDPI, vol. 11(2), pages 1-19, February.
  10. Denis E.K. Dzebre & Muyiwa S. Adaramola, 2019. "Impact of Selected Options in the Weather Research and Forecasting Model on Surface Wind Hindcasts in Coastal Ghana," Energies, MDPI, vol. 12(19), pages 1-16, September.
  11. Steffen Betsch & Bruno Ebner, 2021. "Fixed point characterizations of continuous univariate probability distributions and their applications," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(1), pages 31-59, February.
  12. KC, Anup & Whale, Jonathan & Urmee, Tania, 2019. "Urban wind conditions and small wind turbines in the built environment: A review," Renewable Energy, Elsevier, vol. 131(C), pages 268-283.
  13. Zhang, Yagang & Yang, Jingyun & Wang, Kangcheng & Wang, Zengping & Wang, Yinding, 2015. "Improved wind prediction based on the Lorenz system," Renewable Energy, Elsevier, vol. 81(C), pages 219-226.
  14. Deockho Kim & Jin Hur, 2017. "Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea," Sustainability, MDPI, vol. 9(5), pages 1-12, May.
  15. Yun, Eunjeong & Hur, Jin, 2021. "Probabilistic estimation model of power curve to enhance power output forecasting of wind generating resources," Energy, Elsevier, vol. 223(C).
  16. Aris Alexopoulos, 2019. "One-Parameter Weibull-Type Distribution, Its Relative Entropy with Respect to Weibull and a Fractional Two-Parameter Exponential Distribution," Stats, MDPI, vol. 2(1), pages 1-21, January.
  17. Mekalathur B Hemanth Kumar & Saravanan Balasubramaniyan & Sanjeevikumar Padmanaban & Jens Bo Holm-Nielsen, 2019. "Wind Energy Potential Assessment by Weibull Parameter Estimation Using Multiverse Optimization Method: A Case Study of Tirumala Region in India," Energies, MDPI, vol. 12(11), pages 1-21, June.
  18. Marčiukaitis, Mantas & Žutautaitė, Inga & Martišauskas, Linas & Jokšas, Benas & Gecevičius, Giedrius & Sfetsos, Athanasios, 2017. "Non-linear regression model for wind turbine power curve," Renewable Energy, Elsevier, vol. 113(C), pages 732-741.
  19. Xu, Li & Ou, Yanxia & Cai, Jingjing & Wang, Jin & Fu, Yang & Bian, Xiaoyan, 2023. "Offshore wind speed assessment with statistical and attention-based neural network methods based on STL decomposition," Renewable Energy, Elsevier, vol. 216(C).
  20. Gunnar Bårdsen & Stan Hurn & Kenneth Lindsay, 2019. "Modelling and forecasting wind drought," Working Paper Series 18219, Department of Economics, Norwegian University of Science and Technology.
  21. Young-Been Cho & Yun-Sung Cho & Jae-Gul Lee & Seung-Chan Oh, 2021. "Design and Implementation of Probabilistic Transient Stability Approach to Assess the High Penetration of Renewable Energy in Korea," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
  22. Ke-Sheng Cheng & Cheng-Yu Ho & Jen-Hsin Teng, 2020. "Wind Characteristics in the Taiwan Strait: A Case Study of the First Offshore Wind Farm in Taiwan," Energies, MDPI, vol. 13(24), pages 1-21, December.
  23. Antonio Colmenar-Santos & Severo Campíez-Romero & Lorenzo Alfredo Enríquez-Garcia & Clara Pérez-Molina, 2014. "Simplified Analysis of the Electric Power Losses for On-Shore Wind Farms Considering Weibull Distribution Parameters," Energies, MDPI, vol. 7(11), pages 1-30, October.
  24. Usta, Ilhan, 2016. "An innovative estimation method regarding Weibull parameters for wind energy applications," Energy, Elsevier, vol. 106(C), pages 301-314.
  25. Hanifa Teimourian & Mahmoud Abubakar & Melih Yildiz & Amir Teimourian, 2022. "A Comparative Study on Wind Energy Assessment Distribution Models: A Case Study on Weibull Distribution," Energies, MDPI, vol. 15(15), pages 1-15, August.
  26. Soukissian, Takvor H. & Karathanasi, Flora E., 2017. "On the selection of bivariate parametric models for wind data," Applied Energy, Elsevier, vol. 188(C), pages 280-304.
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