EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 6 (2021) Renew. Energy Environ. Sustain., 6 (2021) 6 References
Open Access
Issue
Renew. Energy Environ. Sustain.
Volume 6, 2021
Article Number 6
Number of page(s) 15
DOI https://doi.org/10.1051/rees/2021006
Published online 07 April 2021
  1. K.O. Odeku, An analysis of renewable energy policy and law promoting socio-economic and sustainable development in rural South Africa, J. Hum. Ecol. 40 , 53–62 (2012) [Google Scholar]
  2. U. Lehr, A. Mönnig, R. Missaoui, S. Marrouki, G. Ben Salem, Employment from renewable energy and energy efficiency in Tunisia − new insights, new results, Energy Procedia 93 , 223–228 (2016) [Google Scholar]
  3. M.S. Salehudin, D.K. Prasad, P. Osmond, Renewable energy potential for energy efficient resort development in Malaysia, Solar 2011, the 49th AuSES Annual Conference , 2011, no. December, pp. 1– 10 [Google Scholar]
  4. M.O. Oseni, An analysis of the power sector performance in Nigeria, Renew. Sustain. Energy Rev. 15 , 4765–4774 (2011) [Google Scholar]
  5. D.K. Kidmo, K. Deli, B. Bogno, Status of renewable energy in Cameroon, Renew. Energy Environ. Sustain. 6 , 1–11 (2021) [Google Scholar]
  6. O.S. Ohunakin, Assessment of wind energy resources for electricity generation using WECS in North-Central region, Nigeria, Renew. Sustain. Energy Rev. 15 , 1968–1976 (2011) [Google Scholar]
  7. P.K. Halder, N. Paul, M.U.H. Joardder, M. Sarker, Energy scarcity and potential of renewable energy in Bangladesh, Renew. Sustain. Energy Rev. 51 , 1636–1649 (2015) [Google Scholar]
  8. K.S. Elie Bertrand, K. Abraham, M. Lucien, Sustainable energy through wind speed and power density analysis in Ambam, South Region of Cameroon, Front. Energy Res. 8 , 1–9 (2020) [Google Scholar]
  9. A. Fashina, M. Mundu, O. Akiyode, L. Abdullah, D. Sanni, L. Ounyesiga, The drivers and barriers of renewable energy applications and development in Uganda: a review, Clean Technol. 1 , 9–39 (2018) [Google Scholar]
  10. D.A. Salam, A. Riadh, Wind energy state of the art: present and future technology advancements, Renew. Energy Environ. Sustain. 5 , 1–8 (2020) [Google Scholar]
  11. D.K. Kidmo, B. Bogno, K. Deli, D. Goron, Seasonal wind characteristics and prospects of wind energy conversion systems for water production in the far North Region of Cameroon, Smart Grid Renew. Energy 11 , 127–164 (2020) [Google Scholar]
  12. IRENA, Global renewables outlook: energy transformation 2050 (Abu Dhabi, 2020). www.irena.org/publications [Google Scholar]
  13. M. Harries, Disseminating wind pumps in rural Kenya − meeting rural water needs using locally manufactured wind pumps, Energy Policy 30 , 1087–1094 (2002) [Google Scholar]
  14. C. Fant, B. Gunturu, A. Schlosser, Characterizing wind power resource reliability in southern Africa, Appl. Energy 161 , 565–573 (2016) [Google Scholar]
  15. J. Kenfack, J. Voufo, P.S. Ngohe Ekam, J.K. Lewetchou, U. Nzotcha, Overcoming local constraints when developing renewable energy systems for the electrification of remote areas in Africa, Renew. Energy Environ. Sustain. 5 , 1–10 (2020) [Google Scholar]
  16. NASA, POWER Single Point Data Access (2021). https://power.larc.nasa.gov/data-access-viewer/ (accessed March 14, 2021) [Google Scholar]
  17. J.W. White, G. Hoogenboom, P.W. Wilkens, P.W. Stackhouse Jr., J.M. Hoel, Evaluation of satellite-based, modeled-derived daily solar radiation data for the continental United States, Cimatol. Water Manag. 103 , 1242–1251 (2011) [Google Scholar]
  18. J. Bai, X. Chen, A. Dobermann, H. Yang, K.G. Cassman, F. Zhang, Evaluation of nasa satellite-and model-derived weather data for simulation of maize yield potential in China, Agron. J. 102 , 9–16 (2010) [Google Scholar]
  19. J.W. White, G. Hoogenboom, P.W. Stackhouse, J.M. Hoell, Evaluation of NASA satellite- and assimilation model-derived long-term daily temperature data over the continental US, Agric. For. Meteorol. 148 , 1574–1584 (2008) [Google Scholar]
  20. C.B. Hasager et al., Remote sensing of environment offshore wind climatology based on synergetic use of Envisat ASAR, ASCAT and QuikSCAT, Remote Sens. Environ. 156 , 247–263 (2015) [Google Scholar]
  21. R.J. Barthelmie, S.C. Pryor, Can satellite sampling of offshore wind speeds realistically represent wind speed distributions? J. Appl. Meteorol. 42 , 83–94 (2003) [Google Scholar]
  22. T. Remmers, F. Cawkwell, C. Desmond, J. Murphy, E. Politi, The potential of advanced scatterometer (ASCAT) 12.5 km coastal observations for offshore wind farm site selection in Irish waters, 1–16 (2019) [Google Scholar]
  23. K.M. Schmidt, S. Swaart, C. Reason, S.-A. Nicholson, Evaluation of satellite and reanalysis wind products with in situ wave glider wind observations in the Southern Ocean, J. Atmos. Ocean. Technol. 34 , 2551–2568 (2017) [Google Scholar]
  24. NASA, NASA Surface meteorology and Solar Energy: RETScreen Data (2020). https://eosweb.larc.nasa.gov/cgi-bin/sse/sse (accessed Dec. 07, 2020) [Google Scholar]
  25. D.K. Kidmo, R. Danwe, Y.S. Doka, N. Djongyang, Statistical analysis of wind speed distribution based on six Weibull Methods for wind power evaluation in Garoua, Cameroon, J. Renew. Energies 18 , 105–125 (2015) [Google Scholar]
  26. D.K. Kidmo, N. Djongyang, S.Y. Doka, D. Raidandi, Assessment of wind energy potential for small scale water pumping systems in the north region of Cameroon, Int. J. Basic Appl. Sci. 3 , 38–46 (2014) [Google Scholar]
  27. S.a. Akdaǧ, A. Dinler, A new method to estimate Weibull parameters for wind energy applications, Energy Convers. Manag. 50 , 1761–1766 (2009) [Google Scholar]
  28. N. Izadyar, H. Chyuan, W.T. Chong, K.Y. Leong, Resource assessment of the renewable energy potential for a remote area: a review, Renew. Sustain. Energy Rev. 62 , 908–923 (2016) [Google Scholar]
  29. North Region (Cameroon), From Wikipedia, Free Encycl., 2020. https://en.wikipedia.org/wiki/North%7B_%7DRegion%7B_%7D(Cameroon)%7B#%7DClimate (accessed Oct. 10, 2020) [Google Scholar]
  30. K. Mohammadi et al., Assessing different parameters estimation methods of Weibull distribution to compute wind power density, Energy Convers. Manag. 108 , 322–335 (2016) [Google Scholar]
  31. K. Mohammadi, O. Alavi, A. Mostafaeipour, N. Goudarzi, M. Jalilvand, Assessing different parameters estimation methods of Weibull distribution to compute wind power density, Energy Convers. Manag. 108 , 322–335 (2016) [Google Scholar]
  32. P.A. Costa Rocha, R.C. de Sousa, C.F. de Andrade, M.E.V. da Silva, Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil, Appl. Energy 89 , 395–400 (2012) [Google Scholar]
  33. B. Safari, J. Gasore, A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda, Renew. Energy 35 , 2874–2880 (2010) [Google Scholar]
  34. P.A. Costa Rocha, R.C. de Sousa, C.F. de Andrade, M.E.V. da Silva, Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil, Appl. Energy 89 , 395–400 (2012) [Google Scholar]
  35. S.F. Khahro, K. Tabbassum, A.M. Soomro, L. Dong, X. Liao, Evaluation of wind power production prospective and Weibull parameter estimation methods for Babaurband, Sindh Pakistan, Energy Convers. Manag. 78 , 956–967 (2014) [Google Scholar]
  36. B. Bailey, S. McDonald, D. Bernadett, M. Markus, K. Elsholz, Wind resource assessment handbook: fundamentals for conducting a successful monitoring program, Music Educ. J. 41 , 65 (1997) [Google Scholar]
  37. A. Azad, M. Rasul, T. Yusaf, Statistical diagnosis of the best Weibull methods for wind power assessment for agricultural applications, Energies 7, 3056–3085 (2014) [Google Scholar]
  38. L. Bilir, M. İmir, Y. Devrim, A. Albostan, Seasonal and yearly wind speed distribution and wind power density analysis based on Weibull distribution function Science Direct Seasonal and yearly wind speed distribution and distribution function, Int. J. Hydrogen Energy 40 , 15301–15310 (2016) [Google Scholar]
  39. I. Fyrippis, P.J. Axaopoulos, G. Panayiotou, Wind energy potential assessment in Naxos Island, Greece, Appl. Energy 87 , 577–586 (2010) [Google Scholar]
  40. L. Olatomiwa, S. Mekhilef, O.S. Ohunakin, Hybrid renewable power supply for rural health clinics (RHC) in six geo-political zones of Nigeria, Sustain. Energy Technol. Assess. 13 , 1–12 (2016) [Google Scholar]
  41. J.F. Manwell, J.G. McGowan, A.L. Rogers, Wind energy explained, Theory, Design and Application (BAffins Lane, Chichester, 2002) [Google Scholar]
  42. A. De Meij et al., Wind energy resource mapping of Palestine, Renew. Sustain. Energy Rev. 56 , 551–562 (2016) [Google Scholar]
  43. C. Stathopoulos, A. Kaperoni, G. Galanis, G. Kallos, Wind power prediction based on numerical and statistical models, J. Wind Eng. Ind. Aerodyn. 112 , 25–38 (2013) [Google Scholar]
  44. T.P. Chang, Wind speed and power density analyses based on mixture Weibull and maximum entropy distributions, Int. J. Appl. Sci. Eng. 8 , 39–46 (2010) [Google Scholar]
  45. D.K. Kidmo, R. Danwe, N. Djongyang, S.Y. Doka, Comparison of five numerical methods for estimating Weibull parameters for wind energy applications in the district of Kousseri, Cameroon, Asian J. Nat. Appl. Sci. 3 , 72–87 (2014) [Google Scholar]
  46. C. Neme, Statistical analysis of wind speed profile: a case study from Iasi Region, Romania, Int. J. Energy Eng. 3 , 261–268 (2013) [Google Scholar]
  47. K. Mohammadi, A. Mostafaeipour, O. Alavi, N. Goudarzi, M. Jalilvand, Assessing different parameters estimation methods of Weibull distribution to compute wind power density, Energy Convers. Manag. 108, 322–335 (2016) [Google Scholar]
  48. T.R.R. Ayodele, A.A.a. Jimoh, J.L.L. Munda, J.T.T. Agee, Wind distribution and capacity factor estimation for wind turbines in the coastal region of South Africa, Energy Convers. Manag. 64 , 614–625 (2012) [Google Scholar]
  49. G. Gualtieri, S. Secci, Methods to extrapolate wind resource to the turbine hub height based on power law: a 1-h wind speed vs. Weibull distribution extrapolation comparison, Renew. Energy 43 , 183–200 (2012) [Google Scholar]
  50. A. Mostafaeipour, M. Jadidi, K. Mohammadi, A. Sedaghat, An analysis of wind energy potential and economic evaluation in Zahedan, Iran, Renew. Sustain. Energy Rev. 30 , 641–650 (2014) [Google Scholar]
  51. O.S.S. Ohunakin, M.S.S. Adaramola, O.M.M. Oyewola, Wind energy evaluation for electricity generation using WECS in seven selected locations in Nigeria, Appl. Energy 88 , 3197–3206 (2011) [Google Scholar]
  52. A.N. Celik, A. Albani, M.Z. Ibrahim, A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey, Renew. Energy 29 , 593–604 (2004) [Google Scholar]
  53. S. Diaf, G. Notton, D. Diaf, Technical and economic assessment of wind farm power generation at Adrar in Southern Algeria, Energy Procedia 42 , 53–62 (2013) [Google Scholar]
  54. M.S. Adaramola, O.M. Oyewola, O.S. Ohunakin, O.O. Akinnawonu, Performance evaluation of wind turbines for energy generation in Niger Delta, Nigeria, Sustain. Energy Technol. Assess. 6 , 75–85 (2014) [Google Scholar]
  55. E.K. Akpinar, S. Akpinar, An assessment on seasonal analysis of wind energy characteristics and wind turbine characteristics, Energy Convers. Manag. 46 , 1848–1867 (2005) [Google Scholar]
  56. S.S. Paul, S.O. Oyedepo, M.S. Adaramola, Economic assessment of water pumping systems using wind energy conversions in the southern part of Nigeria, ENERGY Explor. Exploit. 30 , 1–18 (2012) [Google Scholar]
  57. S. Rehman, T.O. Halawani, M. Mohandes, Wind power cost assessment at twenty locations in the kingdom of Saudi Arabia, Renew. Energy 28 , 573–583 (2003) [Google Scholar]
  58. S. Mathew, Wind energy: fundamentals, resource analysis and economics, Berlin Heidelberg: Springer-Verlag, 2007 [Google Scholar]
  59. L.M. Ayompe, A. Duffy, An assessment of the energy generation potential of photovoltaic systems in Cameroon using satellite-derived solar radiation datasets, Sustain. Energy Technol. Assess. 7, 257–264 (2013) [Google Scholar]
  60. A. Ilinca, E. McCarthy, J.-L. Chaumel, J.-L. Rétiveau, Wind potential assessment of Quebec Province, Renew. Energy 28 , 1881–1897 (2003) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.