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Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm

For the future installation of a wind farm in Cameroon, the wind energy potentials of three of Cameroon’s coastal cities (Kribi, Douala and Limbe) are assessed using NASA average monthly wind data for 31 years (1983–2013) and compared through Weibull statistics. The Weibull parameters are estimated...

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Autores principales: Arreyndip, Nkongho Ayuketang, Joseph, Ebobenow, David, Afungchui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107688/
https://www.ncbi.nlm.nih.gov/pubmed/27872902
http://dx.doi.org/10.1016/j.heliyon.2016.e00187
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author Arreyndip, Nkongho Ayuketang
Joseph, Ebobenow
David, Afungchui
author_facet Arreyndip, Nkongho Ayuketang
Joseph, Ebobenow
David, Afungchui
author_sort Arreyndip, Nkongho Ayuketang
collection PubMed
description For the future installation of a wind farm in Cameroon, the wind energy potentials of three of Cameroon’s coastal cities (Kribi, Douala and Limbe) are assessed using NASA average monthly wind data for 31 years (1983–2013) and compared through Weibull statistics. The Weibull parameters are estimated by the method of maximum likelihood, the mean power densities, the maximum energy carrying wind speeds and the most probable wind speeds are also calculated and compared over these three cities. Finally, the cumulative wind speed distributions over the wet and dry seasons are also analyzed. The results show that the shape and scale parameters for Kribi, Douala and Limbe are 2.9 and 2.8, 3.9 and 1.8 and 3.08 and 2.58, respectively. The mean power densities through Weibull analysis for Kribi, Douala and Limbe are 33.7 W/m2, 8.0 W/m2 and 25.42 W/m2, respectively. Kribi’s most probable wind speed and maximum energy carrying wind speed was found to be 2.42 m/s and 3.35 m/s, 2.27 m/s and 3.03 m/s for Limbe and 1.67 m/s and 2.0 m/s for Douala, respectively. Analysis of the wind speed and hence power distribution over the wet and dry seasons shows that in the wet season, August is the windiest month for Douala and Limbe while September is the windiest month for Kribi while in the dry season, March is the windiest month for Douala and Limbe while February is the windiest month for Kribi. In terms of mean power density, most probable wind speed and wind speed carrying maximum energy, Kribi shows to be the best site for the installation of a wind farm. Generally, the wind speeds at all three locations seem quite low, average wind speeds of all the three studied locations fall below 4.0m/s which is far below the cut-in wind speed of many modern wind turbines. However we recommend the use of low cut-in speed wind turbines like the Savonius for stand alone low energy needs
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spelling pubmed-51076882016-11-21 Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm Arreyndip, Nkongho Ayuketang Joseph, Ebobenow David, Afungchui Heliyon Article For the future installation of a wind farm in Cameroon, the wind energy potentials of three of Cameroon’s coastal cities (Kribi, Douala and Limbe) are assessed using NASA average monthly wind data for 31 years (1983–2013) and compared through Weibull statistics. The Weibull parameters are estimated by the method of maximum likelihood, the mean power densities, the maximum energy carrying wind speeds and the most probable wind speeds are also calculated and compared over these three cities. Finally, the cumulative wind speed distributions over the wet and dry seasons are also analyzed. The results show that the shape and scale parameters for Kribi, Douala and Limbe are 2.9 and 2.8, 3.9 and 1.8 and 3.08 and 2.58, respectively. The mean power densities through Weibull analysis for Kribi, Douala and Limbe are 33.7 W/m2, 8.0 W/m2 and 25.42 W/m2, respectively. Kribi’s most probable wind speed and maximum energy carrying wind speed was found to be 2.42 m/s and 3.35 m/s, 2.27 m/s and 3.03 m/s for Limbe and 1.67 m/s and 2.0 m/s for Douala, respectively. Analysis of the wind speed and hence power distribution over the wet and dry seasons shows that in the wet season, August is the windiest month for Douala and Limbe while September is the windiest month for Kribi while in the dry season, March is the windiest month for Douala and Limbe while February is the windiest month for Kribi. In terms of mean power density, most probable wind speed and wind speed carrying maximum energy, Kribi shows to be the best site for the installation of a wind farm. Generally, the wind speeds at all three locations seem quite low, average wind speeds of all the three studied locations fall below 4.0m/s which is far below the cut-in wind speed of many modern wind turbines. However we recommend the use of low cut-in speed wind turbines like the Savonius for stand alone low energy needs Elsevier 2016-11-10 /pmc/articles/PMC5107688/ /pubmed/27872902 http://dx.doi.org/10.1016/j.heliyon.2016.e00187 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Arreyndip, Nkongho Ayuketang
Joseph, Ebobenow
David, Afungchui
Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm
title Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm
title_full Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm
title_fullStr Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm
title_full_unstemmed Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm
title_short Wind energy potential assessment of Cameroon’s coastal regions for the installation of an onshore wind farm
title_sort wind energy potential assessment of cameroon’s coastal regions for the installation of an onshore wind farm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107688/
https://www.ncbi.nlm.nih.gov/pubmed/27872902
http://dx.doi.org/10.1016/j.heliyon.2016.e00187
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