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Quality of wind speed fitting distributions for the urban area of Palermo, Italy

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Cited by:

  1. Guedes, Kevin S. & de Andrade, Carla F. & Rocha, Paulo A.C. & Mangueira, Rivanilso dos S. & de Moura, Elineudo P., 2020. "Performance analysis of metaheuristic optimization algorithms in estimating the parameters of several wind speed distributions," Applied Energy, Elsevier, vol. 268(C).
  2. Ciulla, Giuseppina & Lo Brano, Valerio & Di Dio, Vincenzo & Cipriani, Giovanni, 2014. "A comparison of different one-diode models for the representation of I–V characteristic of a PV cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 684-696.
  3. Jia, Junmei & Yan, Zaizai & Peng, Xiuyun & An, Xiaoyan, 2020. "A new distribution for modeling the wind speed data in Inner Mongolia of China," Renewable Energy, Elsevier, vol. 162(C), pages 1979-1991.
  4. 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.
  5. Zárate-Miñano, Rafael & Anghel, Marian & Milano, Federico, 2013. "Continuous wind speed models based on stochastic differential equations," Applied Energy, Elsevier, vol. 104(C), pages 42-49.
  6. Valerio Lo Brano & Giuseppina Ciulla & Antonio Piacentino & Fabio Cardona, 2013. "On the Efficacy of PCM to Shave Peak Temperature of Crystalline Photovoltaic Panels: An FDM Model and Field Validation," Energies, MDPI, vol. 6(12), pages 1-23, November.
  7. Masseran, Nurulkamal, 2015. "Evaluating wind power density models and their statistical properties," Energy, Elsevier, vol. 84(C), pages 533-541.
  8. Lo Brano, Valerio & Ciulla, Giuseppina & Piacentino, Antonio & Cardona, Fabio, 2014. "Finite difference thermal model of a latent heat storage system coupled with a photovoltaic device: Description and experimental validation," Renewable Energy, Elsevier, vol. 68(C), pages 181-193.
  9. Qin, Zhilong & Li, Wenyuan & Xiong, Xiaofu, 2013. "Incorporating multiple correlations among wind speeds, photovoltaic powers and bus loads in composite system reliability evaluation," Applied Energy, Elsevier, vol. 110(C), pages 285-294.
  10. Muhammad Aslam, 2022. "Neutrosophic F-Test for Two Counts of Data from the Poisson Distribution with Application in Climatology," Stats, MDPI, vol. 5(3), pages 1-11, August.
  11. Ciulla, G. & D’Amico, A. & Di Dio, V. & Lo Brano, V., 2019. "Modelling and analysis of real-world wind turbine power curves: Assessing deviations from nominal curve by neural networks," Renewable Energy, Elsevier, vol. 140(C), pages 477-492.
  12. Ibrahim Mohamed Diaaeldin & Mahmoud A. Attia & Amr K. Khamees & Othman A. M. Omar & Ahmed O. Badr, 2023. "A Novel Multiobjective Formulation for Optimal Wind Speed Modeling via a Mixture Probability Density Function," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
  13. Ayman Al-Quraan & Bashar Al-Mhairat & Ahmad M. A. Malkawi & Ashraf Radaideh & Hussein M. K. Al-Masri, 2023. "Optimal Prediction of Wind Energy Resources Based on WOA—A Case Study in Jordan," Sustainability, MDPI, vol. 15(5), pages 1-23, February.
  14. Wang, Jianzhou & Hu, Jianming & Ma, Kailiang, 2016. "Wind speed probability distribution estimation and wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 881-899.
  15. Basir Khan, M. Reyasudin & Jidin, Razali & Pasupuleti, Jagadeesh & Shaaya, Sharifah Azwa, 2015. "Optimal combination of solar, wind, micro-hydro and diesel systems based on actual seasonal load profiles for a resort island in the South China Sea," Energy, Elsevier, vol. 82(C), pages 80-97.
  16. Mazzeo, Domenico & Oliveti, Giuseppe & Labonia, Ester, 2018. "Estimation of wind speed probability density function using a mixture of two truncated normal distributions," Renewable Energy, Elsevier, vol. 115(C), pages 1260-1280.
  17. Collados-Lara, Antonio-Juan & Baena-Ruiz, Leticia & Pulido-Velazquez, David & Pardo-Igúzquiza, Eulogio, 2022. "Data-driven mapping of hourly wind speed and its potential energy resources: A sensitivity analysis," Renewable Energy, Elsevier, vol. 199(C), pages 87-102.
  18. Xu, Jin & Kanyingi, Peter Kairu & Wang, Keyou & Li, Guojie & Han, Bei & Jiang, Xiuchen, 2017. "Probabilistic small signal stability analysis with large scale integration of wind power considering dependence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1258-1270.
  19. Wu, Jie & Wang, Jianzhou & Chi, Dezhong, 2013. "Wind energy potential assessment for the site of Inner Mongolia in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 215-228.
  20. Liu, Fa & Wang, Xunming & Sun, Fubao & Kleidon, Axel, 2023. "Potential impact of global stilling on wind energy production in China," Energy, Elsevier, vol. 263(PB).
  21. Alrashidi, Musaed & Rahman, Saifur & Pipattanasomporn, Manisa, 2020. "Metaheuristic optimization algorithms to estimate statistical distribution parameters for characterizing wind speeds," Renewable Energy, Elsevier, vol. 149(C), pages 664-681.
  22. Jiang, Haiyan & Wang, Jianzhou & Wu, Jie & Geng, Wei, 2017. "Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1199-1217.
  23. Kantar, Yeliz Mert & Usta, Ilhan & Arik, Ibrahim & Yenilmez, Ismail, 2018. "Wind speed analysis using the Extended Generalized Lindley Distribution," Renewable Energy, Elsevier, vol. 118(C), pages 1024-1030.
  24. Campisi-Pinto, Salvatore & Gianchandani, Kaushal & Ashkenazy, Yosef, 2020. "Statistical tests for the distribution of surface wind and current speeds across the globe," Renewable Energy, Elsevier, vol. 149(C), pages 861-876.
  25. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
  26. Zárate-Miñano, Rafael & Milano, Federico, 2016. "Construction of SDE-based wind speed models with exponentially decaying autocorrelation," Renewable Energy, Elsevier, vol. 94(C), pages 186-196.
  27. Allouhi, A. & Zamzoum, O. & Islam, M.R. & Saidur, R. & Kousksou, T. & Jamil, A. & Derouich, A., 2017. "Evaluation of wind energy potential in Morocco's coastal regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 311-324.
  28. 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.
  29. Katikas, Loukas & Dimitriadis, Panayiotis & Koutsoyiannis, Demetris & Kontos, Themistoklis & Kyriakidis, Phaedon, 2021. "A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series," Applied Energy, Elsevier, vol. 295(C).
  30. Niu, Tong & Wang, Jianzhou & Zhang, Kequan & Du, Pei, 2018. "Multi-step-ahead wind speed forecasting based on optimal feature selection and a modified bat algorithm with the cognition strategy," Renewable Energy, Elsevier, vol. 118(C), pages 213-229.
  31. Zheng, Hanbo & Huang, Wufeng & Zhao, Junhui & Liu, Jiefeng & Zhang, Yiyi & Shi, Zhen & Zhang, Chaohai, 2022. "A novel falling model for wind speed probability distribution of wind farms," Renewable Energy, Elsevier, vol. 184(C), pages 91-99.
  32. Jónsdóttir, Guðrún Margrét & Milano, Federico, 2019. "Data-based continuous wind speed models with arbitrary probability distribution and autocorrelation," Renewable Energy, Elsevier, vol. 143(C), pages 368-376.
  33. Soukissian, Takvor, 2013. "Use of multi-parameter distributions for offshore wind speed modeling: The Johnson SB distribution," Applied Energy, Elsevier, vol. 111(C), pages 982-1000.
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