Capacity factor; Month-based Turbine Performance Index; Power coefficient; Weibull distribution; Capacity factors; Month-based turbine performance index; Performance indices; Power coefficients; Rated wind speed; Turbine parameters; Turbine performance; Weibull; Wind power density; Wind speed data; Renewable Energy, Sustainability and the Environment
Abstract :
[en] The capacity factor (CF) and power coefficient (Cp) are two important wind turbine characteristics. CF describes the power generation capacity during a given period, and Cp describes the efficiency of the wind turbine. Both quantities depend on the rated wind speed. Determining the optimal rated wind speed that maximizes a function of CF and Cp that is directly related to a wind turbine's output wind power density thus is of utmost importance as it leads to a maximum energy output. This paper proposes a novel Month-based Turbine Performance Index (MTPI) that considers the hourly mean wind speed data month-wise and enables the evaluation of this desired optimum rated turbine speed (Vr,opt) for a given site. Here, the 2-parameter Weibull distribution is employed as a single tool to parameterize the wind speed data and determine the wind speed probability density function, wind power density, vertical wind shear, CF, and Cp of the wind turbine. The examined stations taken for the analysis are from Trivandrum, Ahmedabad, and Calcutta in India. Our index is especially important in regions with intra annular variability, since it is the first to consider monthly instead of annual data.
Disciplines :
Mathematics Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Gugliani, Gaurav Kumar; Department of Mechanical Engineering, Mandsaur University, Mandsaur, India
Sarkar, Arnab; Department of Mechanical Engineering, Indian Institute of Technology (B.H.U.), Varanasi, India
LEY, Christophe ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH) ; Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Gent, Belgium
Matsagar, Vasant; Department of Civil Engineering, Indian Institute of Technology, HauzKhas, New Delhi, India
External co-authors :
yes
Language :
English
Title :
Identification of optimum wind turbine parameters for varying wind climates using a novel month-based turbine performance index
This research is supported by the funding agency Board of Research In Nuclear Sciences (BRNS) , project code number 2012/36/65-BRNS , from the Government of India. The authors are grateful to the Editor and two anonymous reviewers for helpful comments that led to an improvement of the paper.
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