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

被引:24
作者
Arreyndip, Nkongho Ayuketang [1 ,2 ,4 ]
Joseph, Ebobenow [1 ]
David, Afungchui [1 ,3 ]
机构
[1] Univ Buea, Dept Phys, Buea 65, Cameroon
[2] African Inst Math Sci, Limbe 608, Cameroon
[3] Univ Bamenda, Dept Phys, Bamenda, Cameroon
[4] St Jerome Catholic Univ, Inst Douala, Polytech, Douala 5949, Cameroon
关键词
Mathematics; Applied mathematics; Computational mathematics;
D O I
10.1016/j.heliyon.2016.e00187
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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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页数:19
相关论文
共 10 条
[1]  
Afungchui D., 2014, REV DES ENERGIES REN, V17, P137
[2]   A review of wind speed probability distributions used in wind energy analysis Case studies in the Canary Islands [J].
Carta, J. A. ;
Ramirez, P. ;
Velazquez, S. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2009, 13 (05) :933-955
[3]   Assessment of wind energy potential of two sites in North-East, Nigeria [J].
Fagbenle, R. O. ;
Katende, J. ;
Ajayi, O. O. ;
Okeniyi, J. O. .
RENEWABLE ENERGY, 2011, 36 (04) :1277-1283
[4]  
Kaoga D., 2014, ASIAN J NATURAL APPL, V3, P72
[5]   Mixture probability distribution functions to model wind speed distributions [J].
Kollu R. ;
Rayapudi S.R. ;
Narasimham S.V.L. ;
Pakkurthi K.M. .
International Journal of Energy and Environmental Engineering, 2012, 3 (01) :1-10
[6]  
Montgomery D.C., 2003, APPL STAT PROBABILIT
[7]  
Mortensen G. Niels, 2013, REPORT145 DTU
[8]   Analysis of wind speed data and wind energy potential in three selected locations in South-East Nigeria [J].
Oyedepo, Sunday O. ;
Adaramola, Muyiwa S. ;
Paul, Samuel S. .
International Journal of Energy and Environmental Engineering, 2012, 3 (01) :1-11
[9]   An investigation of wind characteristics on the campus of Izmir Institute of Technology, Turkey [J].
Ozerdem, B ;
Turkeli, M .
RENEWABLE ENERGY, 2003, 28 (07) :1013-1027
[10]   Wind energy in Adamaoua and North Cameroon provinces [J].
Tchinda, R ;
Kaptouom, E .
ENERGY CONVERSION AND MANAGEMENT, 2003, 44 (06) :845-857