DocumentCode :
1177650
Title :
Normalized Power Curves as a Tool for Identification of Optimum Wind Turbine Generator Parameters
Author :
Rau, V. G. ; Jangamshetti, S. H.
Author_Institution :
Indian Institute of Technology
Volume :
21
Issue :
8
fYear :
2001
Firstpage :
56
Lastpage :
56
Abstract :
This paper presents a novel method of matching wind turbine generators to a site using normalized power and capacity factor curves. The site matching is based on identifying optimum turbine speed parameters from the turbine performance index curve, which is obtained from the normalized curves, so as to yield higher energy production at a higher capacity factor. The wind speeds are parameterized using a cubic mean cuberoot and statistically modeled using the Weibull probability density function. An expression for a normalized power and capacity factor, expressed entirely in normalized rated speed, is derived. The wind turbine performance index, a new ranking parameter, is defined to optimally match turbines to a potential wind site. The plots of normalized power, capacity factor, and turbine performance index versus normalized rated wind speed are drawn for a known value of the Weibull shape parameter of a site. Usefulness of these normalized curves for identifying optimum wind turbine generator parameters for a site is presented by means of two illustrative case studies. The generalized curves, if used at the planning and development stages of wind power stations, will serve as a useful tool to make a judicious choice of a wind turbine generator that yields higher energy at a higher capacity factor.
Keywords :
Capacity planning; Performance analysis; Power generation; Probability density function; Production; Shape; Wind energy; Wind energy generation; Wind speed; Wind turbines; Capacity factors; Weibull probability density function; normalized power curves; normalized rated wind speed; turbine performance index; wind turbine generator;
fLanguage :
English
Journal_Title :
Power Engineering Review, IEEE
Publisher :
ieee
ISSN :
0272-1724
Type :
jour
DOI :
10.1109/MPER.2001.4311536
Filename :
4311536
Link To Document :
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