Assessment of Wind Energy Potential using Generic Models

被引:0
作者
Tenghiri, Lhoussaine [1 ]
Khalil, Yassine [1 ]
Abdi, Farid [1 ]
Bentamy, Anas [2 ]
机构
[1] Fac Sci & Tech, Elect Engn Dept, Fes, Morocco
[2] Al Akhawayn Univ, Sch Sci & Engn, Ifrane, Morocco
来源
PROCEEDINGS OF 2016 INTERNATIONAL RENEWABLE & SUSTAINABLE ENERGY CONFERENCE (IRSEC' 16) | 2016年
关键词
component; capacity factor; wind turbine; generic model; power curve; WEIBULL PARAMETERS; CONVERSION SYSTEM; TURBINES; CAPACITY; SPEED; SITES;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Power production of a wind turbine system is strongly dependent on both the wind regime at the site and the operating parameters of the wind turbine (design parameters). In order to evaluate the performance of a wind turbine in a given location, an accurate estimation of the turbine's Capacity Factor (CF) is required. This parameter shows the degree of match between the characteristics of the turbine andthe wind patterns on the site. In this paper, four widely used empirical models are presented and compared using the method of bins, which is based on the manufacturer-provided power curves. The generic models considered in this paper are Linear Model (LM), Quadratic Model (QM), Cubic Model (CM), and General Model (GM). The validity of these models was investigated using a case study of four locations across Morocco which are namely: Tetouan, Essaouira, Taza and Ouarzazate. Four small scale wind turbines presenting different ranges of characteristic speeds and rated powers (10 kW, 20 kW, and 50 kW) were used to conduct the comparative study. From the obtained results, the recommended models are the Quadratic and the Cubic models. These two models present a good description of the turbines' power curves.
引用
收藏
页码:1170 / 1175
页数:6
相关论文
共 34 条
[11]  
Dagdougui H., 2010, RENEW SUST ENERG REV, V14, P1959
[12]   Research on power coefficient of wind turbines based on SCADA data [J].
Dai, Juchuan ;
Liu, Deshun ;
Wen, Li ;
Long, Xin .
RENEWABLE ENERGY, 2016, 86 :206-215
[13]   Comparison of Three Methods for Wind Turbine Capacity Factor Estimation [J].
Ditkovich, Y. ;
Kuperman, A. .
SCIENTIFIC WORLD JOURNAL, 2014,
[14]   Estimating wind speed distribution [J].
Dorvlo, ASS .
ENERGY CONVERSION AND MANAGEMENT, 2002, 43 (17) :2311-2318
[15]   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
[16]  
Ghosh S. K., P 2014 3 INT C DEV R
[17]  
Hossieni A., P 2014 3 INT C REN E
[18]  
International Eloctrotechnical Commission, WIND TURB 2
[19]   Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrain [J].
Jowder, Fawzi A. L. .
APPLIED ENERGY, 2009, 86 (04) :538-545
[20]   Estimation of wind energy production in various sites in Australia for different wind turbine classes: A comparative technical and economic assessment [J].
Katsigiannis, Yiannis A. ;
Stavrakakis, George S. .
RENEWABLE ENERGY, 2014, 67 :230-236