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Optimization of power coefficient on a horizontal axis wind turbine using bem theory

Journal

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Volume 26, Issue -, Pages 169-182

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2013.05.009

Keywords

Optimization; Horizontal axis wind turbine; Blade element momentum (BEM) theory

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Aerodynamic optimization has widely become a issue of considerable interest to determine the geometry of an aerodynamic configuration amidst certain design constraints. Aerodynamic performance is calculated from a prescribed geometric shape, which is often performed in trial and error method. Numerous design methods are available for the aerodynamic design of the rotor. The goal in optimizing is to maximize the aerodynamic efficiency at a single design wind speed. However, single-design point methods do not automatically lead to the optimum design, since they consider only one point in the total operational range. Moreover they do not implicitly involve considerations on loads which require an experienced designer. The aerodynamic optimization of a Horizontal Axis Wind Turbine is a complex method characterized by numerous trade-off decisions aimed at finding the optimum overall performance. However researcher design the wind turbine is an enormous ways and more often decision-making is very difficult. Commercial turbines have been derived from both theoretical and empirical methods, but there is no clear evidence on which of these is optimal. Turbine blades are optimized with the aim to achieve maximum power coefficient for the given blade with solidity, ratio of coefficient of drag to lift, angle of attack and tip speed ratio. In this article, the blade element theory is used to find the optimum value analytically. The effect of power coefficient for different blade angle, tip speed ratio, ratio of coefficient of drag and coefficient of lift and blade solidity is presented and the optimized set value is obtained. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

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