Back to Search Start Over

Optimal characteristics of wind turbine to maximize capacity factor.

Authors :
Rasham, Ali M.
Hussain, Mohammed Khalil
Majeed, M.H.
Source :
AIP Conference Proceedings; 2023, Vol. 2651 Issue 1, p1-10, 10p
Publication Year :
2023

Abstract

The capacity factor is the main factor in assessing the efficiency of wind Turbine. This paper presents a procedure to find the optimal wind turbine for five different locations in Iraq based on finding the highest capacity factor of wind turbine for different locations. The wind data for twelve successive years (2009-2020) of five locations in Iraq are collected and analyzed. The longitudes and latitudes of the candidate sites are (44.3661o E, 33.3152o N), (47.7738o E, 30.5258o N), (45.8160o E, 32.5165o N), (44.33265o E, 32.0107o N) and (46.25691o E, 31.0510o N) for Baghdad, Basrah, Al-Kut, Al-Najaf, and Al-Nasiriyah respectively. The average wind velocity, standard deviation, Weibull shape and scale factors, and probability density function are calculated. According to quadratic model, the capacity factor for five wind turbines of different characteristics is calculated and compared with wind turbines in wind farm. The suitable wind turbine for the candidate sites is selected via matching between wind sites-wind turbines characteristics. The Gamesa G114-2.0MW model has highest capacity factor among other models for all selected sites whereas the Adwen AD 5-132 has lowest capacity factor. The Genetic algorithm is used to find the optimum cut-in and rated speeds of the wind turbine. The main objective of the algorithm to be maximized is the capacity factor of wind turbine. According to the practical ranges for cut-in and rated speeds of wind turbines, a proposed optimal value of cut-in and rated speeds are identified to ensure highest capacity factor for the studied wind sites in Iraq. MATLAB program is used to simulate the mathematical model of wind energy, wind turbine performance, and the capacity factor of wind turbines. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2651
Issue :
1
Database :
Complementary Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
162733034
Full Text :
https://doi.org/10.1063/5.0106773