Wind characteristics and energy potential assessment in Akure, South West Nigeria: econometrics and policy implications

被引:12
作者
Okeniyi, Joshua Olusegun [1 ]
Moses, Ime Friday [2 ,3 ]
Okeniyi, Elizabeth Toyin [4 ]
机构
[1] Covenant Univ, Dept Mech Engn, Ota, Nigeria
[2] Fed Univ Technol Akure, Dept Phys, Akure, Nigeria
[3] Nigeria Atom Energy Commiss, Abuja, Nigeria
[4] Covenant Univ, Dept Petr Engn, Ota, Nigeria
关键词
wind energy potential; Weibull probabilistic modelling; Rayleigh probabilistic modelling; Kolmogorov-Smirnov statistics; low wind-speed econometric analysis; Akure; -; Nigeria;
D O I
10.1080/01430750.2013.864586
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper analysed 11 years of daily mean wind-speed data, measured at Akure, Ondo State, Nigeria, using Weibull and Rayleigh distribution functions. While both distributions showed good agreements in extreme-value estimation patterns, investigation of their wind-speed characteristics modelling criteria, using goodness-of-fit statistics, revealed that the wind data followed the Weibull more than Rayleigh. Monthly wind-speed of Akure city ranged from 1.41 to 4.24m/s by the Weibull fittings and from 1.40 to 4.16m/s by the Rayleigh fittings. Overall results, of 2.71m/s (Weibull) or 2.70m/s (Rayleigh) mean wind-speed and 18.51W/m(2) (Weibull) or 22.26W/m(2) (Rayleigh) mean power density, indicated Akure a low wind-speed site, requiring low wind-speed turbine for generating wind energy. Econometric analyses of power output simulations using such turbine system resulted in affordable wind energy cost. These bear policy implications for sustainable wind energy usage in this and similar regions of the world.
引用
收藏
页码:282 / 300
页数:19
相关论文
共 43 条
[11]   Electricity generation using wind energy conversion systems in the area of Western Greece [J].
Bagiorgas, H. S. ;
Assimakopoulos, M. N. ;
Theoharopoulos, D. ;
Matthopoulos, D. ;
Mihalakakou, G. K. .
ENERGY CONVERSION AND MANAGEMENT, 2007, 48 (05) :1640-1655
[12]   On the distributional parameters used in assessment of the suitability of wind speed probability density functions [J].
Celik, AN .
ENERGY CONVERSION AND MANAGEMENT, 2004, 45 (11-12) :1735-1747
[13]   A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey [J].
Celik, AN .
RENEWABLE ENERGY, 2004, 29 (04) :593-604
[14]  
Central Bank of Nigeria (CBN), 2010, ANN REP STAT ACC YEA
[15]   UK onshore wind capacity factors 1998-2005 [J].
Dagnall, S. ;
Tipping, A. ;
Janes, M. .
INTERNATIONAL JOURNAL OF AMBIENT ENERGY, 2007, 28 (02) :83-88
[16]   Assessment of wind energy potential and optimal electricity generation in Borj-Cedria, Tunisia [J].
Dahmouni, A. W. ;
Ben Salah, M. ;
Askri, F. ;
Kerkeni, C. ;
Ben Nasrallah, S. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2011, 15 (01) :815-820
[17]   Wind resource assessment of eastern coastal region of Saudi Arabia [J].
Elhadidy, M. A. ;
Shaahid, S. M. .
DESALINATION, 2007, 209 (1-3) :199-208
[18]   The Statistical Evaluation of Wind Speed and Power Density in the Firouzkouh Region in Iran [J].
Emami, N. ;
Behbahani-Nia, A. .
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2012, 34 (12) :1076-1083
[19]   Wind energy potential of Gokceada Island in Turkey [J].
Eskin, N. ;
Artar, H. ;
Tolun, S. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2008, 12 (03) :839-851
[20]  
Fadare D.A., 2008, PAC J SCI TECHNOL, V9, P110