IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v159y2020icp1188-1198.html
   My bibliography  Save this article

Analysis and efficient comparison of ten numerical methods in estimating Weibull parameters for wind energy potential: Application to the city of Bafoussam, Cameroon

Author

Listed:
  • Tiam Kapen, Pascalin
  • Jeutho Gouajio, Marinette
  • Yemélé, David

Abstract

The aim of this paper is to analyze and compare efficiently of 10 (ten) numerical methods namely, the empirical method of Justus (EMJ), the empirical method of Lysen (EML), the method of moments (MoM), the graphical method (GM), the Mabchour’s method (MMab), the energy pattern factor method (EPFM), the maximum likelihood method (MLM), the modified maximum likelihood method (MMLM), the equivalent energy method (EEM), and the alternative maximum likelihood method (AMLM) in order to estimate Weibull parameters for wind energy potential. They were performed by using wind speed data collected in the meteorological station of Bafoussam city, in the west region of Cameroon, in the period from 2007 to 2013. The results of this study obtained from statistical analysis show that the MLM presents relatively more excellent ability throughout the simulation tests, followed by EEM, EPFM and EMJ respectively. They also demonstrated that EEM presented minimum error in estimating the monthly wind power density and that the wind potential of Bafoussam city can be interesting for some applications such as rural electrification and water pumping in agriculture.

Suggested Citation

  • Tiam Kapen, Pascalin & Jeutho Gouajio, Marinette & Yemélé, David, 2020. "Analysis and efficient comparison of ten numerical methods in estimating Weibull parameters for wind energy potential: Application to the city of Bafoussam, Cameroon," Renewable Energy, Elsevier, vol. 159(C), pages 1188-1198.
    • Handle: RePEc:eee:renene:v:159:y:2020:i:c:p:1188-1198
    DOI: 10.1016/j.renene.2020.05.185
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120308909
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.05.185?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Njoh, Ambe J. & Etta, Simon & Ngyah-Etchutambe, Ijang B. & Enomah, Lucy E.D. & Tabrey, Hans T. & Essia, Uwem, 2019. "Opportunities and challenges to rural renewable energy projects in Africa: Lessons from the Esaghem Village, Cameroon solar electrification project," Renewable Energy, Elsevier, vol. 131(C), pages 1013-1021.
    2. Nasser Yimen & Oumarou Hamandjoda & Lucien Meva’a & Benoit Ndzana & Jean Nganhou, 2018. "Analyzing of a Photovoltaic/Wind/Biogas/Pumped-Hydro Off-Grid Hybrid System for Rural Electrification in Sub-Saharan Africa—Case Study of Djoundé in Northern Cameroon," Energies, MDPI, vol. 11(10), pages 1-30, October.
    3. Karthikeya, B.R. & Negi, Prabal S. & Srikanth, N., 2016. "Wind resource assessment for urban renewable energy application in Singapore," Renewable Energy, Elsevier, vol. 87(P1), pages 403-414.
    4. Muh, Erasmus & Tabet, Fouzi, 2019. "Comparative analysis of hybrid renewable energy systems for off-grid applications in Southern Cameroons," Renewable Energy, Elsevier, vol. 135(C), pages 41-54.
    5. Ahmed Shata, A.S. & Hanitsch, R., 2006. "The potential of electricity generation on the east coast of Red Sea in Egypt," Renewable Energy, Elsevier, vol. 31(10), pages 1597-1615.
    6. Feijóo, Andrés & Villanueva, Daniel, 2016. "Assessing wind speed simulation methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 473-483.
    7. Elsner, Paul, 2019. "Continental-scale assessment of the African offshore wind energy potential: Spatial analysis of an under-appreciated renewable energy resource," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 394-407.
    8. Morgan, Vincent T., 1995. "Statistical distributions of wind parameters at Sydney, Australia," Renewable Energy, Elsevier, vol. 6(1), pages 39-47.
    9. Abanda, F.H., 2012. "Renewable energy sources in Cameroon: Potentials, benefits and enabling environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4557-4562.
    10. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
    11. Mas’ud, Abdullahi Abubakar & Vernyuy Wirba, Asan & Muhammad-Sukki, Firdaus & Mas’ud, Ibrahim Abubakar & Munir, Abu Bakar & Md Yunus, Norhidayah, 2015. "An assessment of renewable energy readiness in Africa: Case study of Nigeria and Cameroon," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 775-784.
    12. Abdullahi Abubakar Mas’ud & Asan Vernyuy Wirba & Jorge Alfredo Ardila-Rey & Ricardo Albarracín & Firdaus Muhammad-Sukki & Álvaro Jaramillo Duque & Nurul Aini Bani & Abu Bakar Munir, 2017. "Wind Power Potentials in Cameroon and Nigeria: Lessons from South Africa," Energies, MDPI, vol. 10(4), pages 1-19, March.
    13. Safari, Bonfils & Gasore, Jimmy, 2010. "A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda," Renewable Energy, Elsevier, vol. 35(12), pages 2874-2880.
    14. Chaurasiya, Prem Kumar & Ahmed, Siraj & Warudkar, Vilas, 2018. "Comparative analysis of Weibull parameters for wind data measured from met-mast and remote sensing techniques," Renewable Energy, Elsevier, vol. 115(C), pages 1153-1165.
    15. Taner, Tolga, 2018. "Energy and exergy analyze of PEM fuel cell: A case study of modeling and simulations," Energy, Elsevier, vol. 143(C), pages 284-294.
    16. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    17. Wirba, Asan Vernyuy & Abubakar Mas'ud, Abdullahi & Muhammad-Sukki, Firdaus & Ahmad, Salman & Mat Tahar, Razman & Abdul Rahim, Ruzairi & Munir, Abu Bakar & Karim, Md Ershadul, 2015. "Renewable energy potentials in Cameroon: Prospects and challenges," Renewable Energy, Elsevier, vol. 76(C), pages 560-565.
    18. 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.
    19. Olaofe, Z.O., 2018. "Review of energy systems deployment and development of offshore wind energy resource map at the coastal regions of Africa," Energy, Elsevier, vol. 161(C), pages 1096-1114.
    20. Carneiro, Tatiane C. & Melo, Sofia P. & Carvalho, Paulo C.M. & Braga, Arthur Plínio de S., 2016. "Particle Swarm Optimization method for estimation of Weibull parameters: A case study for the Brazilian northeast region," Renewable Energy, Elsevier, vol. 86(C), pages 751-759.
    21. Muh, Erasmus & Amara, Sofiane & Tabet, Fouzi, 2018. "Sustainable energy policies in Cameroon: A holistic overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3420-3429.
    22. Mboumboue, Edouard & Njomo, Donatien, 2016. "Potential contribution of renewables to the improvement of living conditions of poor rural households in developing countries: Cameroon׳s case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 266-279.
    23. Kenfack, Joseph & Lewetchou K., J. & Bossou, Olivier Videme & Tchaptchet, E., 2017. "How can we promote renewable energy and energy efficiency in Central Africa? A Cameroon case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1217-1224.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chang, Ping-Chen, 2022. "MC-based simulation approach for two-terminal multi-state network reliability evaluation without knowing d-MCs," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    2. Ismail Kamdar & Shahid Ali & Juntakan Taweekun & Hafiz Muhammad Ali, 2021. "Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
    3. Chang, Ping-Chen & Huang, Ding-Hsiang & Lin, Yi-Kuei & Nguyen, Thi-Phuong, 2021. "Reliability and maintenance models for a time-related multi-state flow network via d-MC approach," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Chang, Ping-Chen, 2024. "A path-based simulation approach for multistate flow network reliability estimation without using boundary points," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    5. Škvorc, Petar & Kozmar, Hrvoje, 2021. "Wind energy harnessing on tall buildings in urban environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kenfack, Joseph & Nzotcha, Urbain & Voufo, Joseph & Ngohe-Ekam, Paul Salomon & Nsangou, Jean Calvin & Bignom, Blaise, 2021. "Cameroon's hydropower potential and development under the vision of Central Africa power pool (CAPP): A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    2. 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.
    3. Belabes, B. & Youcefi, A. & Guerri, O. & Djamai, M. & Kaabeche, A., 2015. "Evaluation of wind energy potential and estimation of cost using wind energy turbines for electricity generation in north of Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1245-1255.
    4. Muh, Erasmus & Tabet, Fouzi, 2019. "Comparative analysis of hybrid renewable energy systems for off-grid applications in Southern Cameroons," Renewable Energy, Elsevier, vol. 135(C), pages 41-54.
    5. Chaurasiya, Prem Kumar & Ahmed, Siraj & Warudkar, Vilas, 2018. "Comparative analysis of Weibull parameters for wind data measured from met-mast and remote sensing techniques," Renewable Energy, Elsevier, vol. 115(C), pages 1153-1165.
    6. Bahrami, Arian & Teimourian, Amir & Okoye, Chiemeka Onyeka & Khosravi, Nima, 2019. "Assessing the feasibility of wind energy as a power source in Turkmenistan; a major opportunity for Central Asia's energy market," Energy, Elsevier, vol. 183(C), pages 415-427.
    7. Katinas, Vladislovas & Marčiukaitis, Mantas & Gecevičius, Giedrius & Markevičius, Antanas, 2017. "Statistical analysis of wind characteristics based on Weibull methods for estimation of power generation in Lithuania," Renewable Energy, Elsevier, vol. 113(C), pages 190-201.
    8. Katinas, Vladislovas & Gecevicius, Giedrius & Marciukaitis, Mantas, 2018. "An investigation of wind power density distribution at location with low and high wind speeds using statistical model," Applied Energy, Elsevier, vol. 218(C), pages 442-451.
    9. Celik, Ali N. & Kolhe, Mohan, 2013. "Generalized feed-forward based method for wind energy prediction," Applied Energy, Elsevier, vol. 101(C), pages 582-588.
    10. 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.
    11. Bundhoo, Zumar M.A., 2018. "Renewable energy exploitation in the small island developing state of Mauritius: Current practice and future potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2029-2038.
    12. 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.
    13. Muh, Erasmus & Amara, Sofiane & Tabet, Fouzi, 2018. "Sustainable energy policies in Cameroon: A holistic overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3420-3429.
    14. 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.
    15. 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.
    16. 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.
    17. Usta, Ilhan, 2016. "An innovative estimation method regarding Weibull parameters for wind energy applications," Energy, Elsevier, vol. 106(C), pages 301-314.
    18. He, Junyi & Chan, P.W. & Li, Qiusheng & Lee, C.W., 2020. "Spatiotemporal analysis of offshore wind field characteristics and energy potential in Hong Kong," Energy, Elsevier, vol. 201(C).
    19. Saeed, Muhammad Abid & Ahmed, Zahoor & Zhang, Weidong, 2020. "Wind energy potential and economic analysis with a comparison of different methods for determining the optimal distribution parameters," Renewable Energy, Elsevier, vol. 161(C), pages 1092-1109.
    20. He, J.Y. & Chan, P.W. & Li, Q.S. & Huang, Tao & Yim, Steve Hung Lam, 2024. "Assessment of urban wind energy resource in Hong Kong based on multi-instrument observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:159:y:2020:i:c:p:1188-1198. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.