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Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions

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  1. Zhang, Hua & Yu, Yong-Jing & Liu, Zhi-Yuan, 2014. "Study on the Maximum Entropy Principle applied to the annual wind speed probability distribution: A case study for observations of intertidal zone anemometer towers of Rudong in East China Sea," Applied Energy, Elsevier, vol. 114(C), pages 931-938.
  2. Macleod, Alasdair, 2008. "Using the microclimate to optimise renewable energy installations," Renewable Energy, Elsevier, vol. 33(8), pages 1804-1813.
  3. Carta, José A. & Velázquez, Sergio & Cabrera, Pedro, 2013. "A review of measure-correlate-predict (MCP) methods used to estimate long-term wind characteristics at a target site," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 362-400.
  4. Manuel Franco & Narayanaswamy Balakrishnan & Debasis Kundu & Juana-María Vivo, 2014. "Generalized mixtures of Weibull components," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 515-535, September.
  5. Phan, Duong & Bab-Hadiashar, Alireza & Lai, Chow Yin & Crawford, Bryn & Hoseinnezhad, Reza & Jazar, Reza N. & Khayyam, Hamid, 2020. "Intelligent energy management system for conventional autonomous vehicles," Energy, Elsevier, vol. 191(C).
  6. Estefania Artigao & Antonio Vigueras-Rodríguez & Andrés Honrubia-Escribano & Sergio Martín-Martínez & Emilio Gómez-Lázaro, 2021. "Wind Resource and Wind Power Generation Assessment for Education in Engineering," Sustainability, MDPI, vol. 13(5), pages 1-27, February.
  7. Mehr Gul & Nengling Tai & Wentao Huang & Muhammad Haroon Nadeem & Moduo Yu, 2019. "Assessment of Wind Power Potential and Economic Analysis at Hyderabad in Pakistan: Powering to Local Communities Using Wind Power," Sustainability, MDPI, vol. 11(5), pages 1-23, March.
  8. Antonio Bracale & Pasquale De Falco, 2015. "An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power," Energies, MDPI, vol. 8(9), pages 1-22, September.
  9. Calif, Rudy & Emilion, Richard & Soubdhan, Ted, 2011. "Classification of wind speed distributions using a mixture of Dirichlet distributions," Renewable Energy, Elsevier, vol. 36(11), pages 3091-3097.
  10. Schallenberg-Rodriguez, Julieta, 2013. "A methodological review to estimate techno-economical wind energy production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 272-287.
  11. 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.
  12. Franco, Manuel & Vivo, Juana-María, 2009. "Constraints for generalized mixtures of Weibull distributions with a common shape parameter," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1724-1730, August.
  13. Han, Qinkai & Wang, Tianyang & Chu, Fulei, 2022. "Nonparametric copula modeling of wind speed-wind shear for the assessment of height-dependent wind energy in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  14. Arslan, Talha & Bulut, Y. Murat & Altın Yavuz, Arzu, 2014. "Comparative study of numerical methods for determining Weibull parameters for wind energy potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 820-825.
  15. Kusiak, Andrew & Zheng, Haiyang & Song, Zhe, 2009. "On-line monitoring of power curves," Renewable Energy, Elsevier, vol. 34(6), pages 1487-1493.
  16. Sumair, Muhammad & Aized, Tauseef & Aslam Bhutta, Muhammad Mahmood & Siddiqui, Farrukh Arsalan & Tehreem, Layba & Chaudhry, Abduallah, 2022. "Method of Four Moments Mixture-A new approach for parametric estimation of Weibull Probability Distribution for wind potential estimation applications," Renewable Energy, Elsevier, vol. 191(C), pages 291-304.
  17. 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.
  18. Wais, Piotr, 2017. "Two and three-parameter Weibull distribution in available wind power analysis," Renewable Energy, Elsevier, vol. 103(C), pages 15-29.
  19. Lepore, Antonio & Palumbo, Biagio & Pievatolo, Antonio, 2020. "A Bayesian approach for site-specific wind rose prediction," Renewable Energy, Elsevier, vol. 150(C), pages 691-702.
  20. Liu, Feng Jiao & Chang, Tian Pau, 2011. "Validity analysis of maximum entropy distribution based on different moment constraints for wind energy assessment," Energy, Elsevier, vol. 36(3), pages 1820-1826.
  21. Simon Watson, 2014. "Quantifying the variability of wind energy," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(4), pages 330-342, July.
  22. 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.
  23. 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.
  24. Jin, Jingliang & Zhou, Dequn & Zhou, Peng & Miao, Zhuang, 2014. "Environmental/economic power dispatch with wind power," Renewable Energy, Elsevier, vol. 71(C), pages 234-242.
  25. Früh, Wolf-Gerrit, 2013. "Long-term wind resource and uncertainty estimation using wind records from Scotland as example," Renewable Energy, Elsevier, vol. 50(C), pages 1014-1026.
  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.
  27. Qing, Xiangyun, 2018. "Statistical analysis of wind energy characteristics in Santiago island, Cape Verde," Renewable Energy, Elsevier, vol. 115(C), pages 448-461.
  28. Makhloufi, Saida & Mekhaldi, Abdelouahab & Teguar, Madjid, 2016. "Three powerful nature-inspired algorithms to optimize power flow in Algeria's Adrar power system," Energy, Elsevier, vol. 116(P1), pages 1117-1130.
  29. Emilio Gómez-Lázaro & María C. Bueso & Mathieu Kessler & Sergio Martín-Martínez & Jie Zhang & Bri-Mathias Hodge & Angel Molina-García, 2016. "Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures," Energies, MDPI, vol. 9(2), pages 1-15, February.
  30. Hu, Qinghua & Wang, Yun & Xie, Zongxia & Zhu, Pengfei & Yu, Daren, 2016. "On estimating uncertainty of wind energy with mixture of distributions," Energy, Elsevier, vol. 112(C), pages 935-962.
  31. Santos, Fábio Sandro dos & Nascimento, Kerolly Kedma Felix do & Jale, Jader da Silva & Stosic, Tatijana & Marinho, Manoel H.N. & Ferreira, Tiago A.E., 2021. "Mixture distribution and multifractal analysis applied to wind speed in the Brazilian Northeast region," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
  32. Muhammad Fitra Zambak & Catra Indra Cahyadi & Jufri Helmi & Tengku Machdhalie Sofie & Suwarno Suwarno, 2023. "Evaluation and Analysis of Wind Speed with the Weibull and Rayleigh Distribution Models for Energy Potential Using Three Models," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 427-432, March.
  33. Muhammet Burak Kılıç & Yusuf Şahin & Melih Burak Koca, 2021. "Genetic algorithm approach with an adaptive search space based on EM algorithm in two-component mixture Weibull parameter estimation," Computational Statistics, Springer, vol. 36(2), pages 1219-1242, June.
  34. 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.
  35. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
  36. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
  37. Mingjin Zhang & Jinxiang Zhang & Fanying Jiang & Lianhuo Wu & Jingxi Qin & Yongle Li, 2023. "Combined wind profile characteristics based on wind parameters joint probability model in a mountainous gorge," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(1), pages 709-733, January.
  38. Wais, Piotr, 2017. "A review of Weibull functions in wind sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1099-1107.
  39. Carta, José A. & Velázquez, Sergio, 2011. "A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site," Energy, Elsevier, vol. 36(5), pages 2671-2685.
  40. Khahro, Shahnawaz Farhan & Tabbassum, Kavita & Mahmood Soomro, Amir & Liao, Xiaozhong & Alvi, Muhammad Bux & Dong, Lei & Manzoor, M. Farhan, 2014. "Techno-economical evaluation of wind energy potential and analysis of power generation from wind at Gharo, Sindh Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 460-474.
  41. Gugliani, Gaurav Kumar & Sarkar, Arnab & Ley, Christophe & Matsagar, Vasant, 2021. "Identification of optimum wind turbine parameters for varying wind climates using a novel month-based turbine performance index," Renewable Energy, Elsevier, vol. 171(C), pages 902-914.
  42. Akdag, S.A. & Bagiorgas, H.S. & Mihalakakou, G., 2010. "Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean," Applied Energy, Elsevier, vol. 87(8), pages 2566-2573, August.
  43. Goh, H.H. & Lee, S.W. & Chua, Q.S. & Goh, K.C. & Teo, K.T.K., 2016. "Wind energy assessment considering wind speed correlation in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1389-1400.
  44. Amr Khaled Khamees & Almoataz Y. Abdelaziz & Makram R. Eskaros & Mahmoud A. Attia & Mariam A. Sameh, 2022. "Optimal Power Flow with Stochastic Renewable Energy Using Three Mixture Component Distribution Functions," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
  45. Cabello, M. & Orza, J.A.G., 2010. "Wind speed analysis in the province of Alicante, Spain. Potential for small-scale wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3185-3191, December.
  46. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
  47. Shin, Ju-Young & Ouarda, Taha B.M.J. & Lee, Taesam, 2016. "Heterogeneous mixture distributions for modeling wind speed, application to the UAE," Renewable Energy, Elsevier, vol. 91(C), pages 40-52.
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