The Sixth IASTED Asian Conference on
Power and Energy Systems
April 10 – 12, 2013
Wind Turbine Performance Index as tool for Site Matching of Wind Turbine Generators
Rising fuel prices driven by growing demand, decline in the fossil fuel reserves, and incontrovertible evidences of global warming are causing serious concerns on energy and environment security around the globe. Unfortunately for a world that is so used to cheap fossil fuels, the reality is too difficult to accept to initiate serious effort at finding alternatives. However the time is running out and experts have been urging for quick and paradigm shift in the way we generate and utilize energy. Under this scenario, Wind Energy holds great promise and needs to be harnessed in a far greater scale than it is now. Industry/Academic institutions have a very great role to play in this. This tutorial is aimed at providing a basic as well as in depth understanding of Wind Energy from wind data analysis and extraction of maximum energy from the wind point of view.
Generation of electrical power by a wind turbine generator system at a specific site depends upon many factors. Significant among them being the mean wind speed of the site and more significantly the speed characteristics of the wind turbine itself, namely cut-in velocity (Vc), rated velocity (Vr) and cut-out velocity (Vf) including the hub height. This tutorial speaks about novel methods of (a) wind data analysis, and (b) site matching of wind turbine generators using normalized power and capacity factor curves. Wind data analysis is parameterized using cubic mean cuberoot of wind velocities. The site matching is based on identifying optimum turbine speed parameters from turbine performance index curve, which is obtained from the normalized power and capacity factor curves, so as to yield higher energy production at higher capacity factor. Wind Turbine Performance Index (TPI) is a newly introduced concept. It is shown that there exists a unique TPI curve for every site from which speed parameters of a turbine that will optimally match the site can be obtained. TPI curve is obtained from normalized power and capacity factor curves and is drawn on the common axis of normalized rated speed.
Main objective of the tutorial are to provide:
(i) basic knowledge about wind data analysis,
(ii) exposure to working of wind turbines,
(iii) basic tools of conducting performance analysis of wind turbine generators,
(iv) clear methods of selecting wind turbines for a site
(v) information about site matching of wind turbines
Background Knowledge Expected of the Participants
(i) Technical graduate with electrical or mechanical engineering background, (ii) Working Professional in Renewable Industry.
Qualifications of the Instructor(s)
Professor Dr. Suresh. H. Jangamshetti obtained Ph.D in Wind Energy from Indian Institute of Technology, Kharagpur, India. He is currently working as Professor in Basaveshwar Engineering College, Bagalkot, India. His research interest include wind and solar energy systems. He is a senior member of IEEE and Fulbright Alumni.