Smart composite wind turbine blades - a pilot study

Supeni, Eris Elianddy (2015) Smart composite wind turbine blades - a pilot study. [Thesis (PhD/Research)]

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Abstract

Wind energy is seen as a viable alternative energy option to meet future energy demands. The blades of wind turbines have been long recognised as the most critical component of the wind turbine system. The turbine blades interact with the wind flow to turn the wind turbine, in effect acting s a tool to extract the wind energy and turn it into electrical energy.

As the wind industry continues to explore new technologies, the turbine blade is a key aspect of better wind turbine designs. Harnessing greater wind power requires larger swept areas. Increasing the length of the turbine blades increases the swept area of a wind turbine, thereby improving the production of wind energy. However, longer turbine blades significantly add to the weight of the turbine, and they also suffer from larger bending deflections due to flapwise loads. The flapwise bending deflections not only result in a lower performance of electrical power generation but also increase in material degradation due to high fatigue loads and can significantly shorten the longevity for the turbine blade.

To overcome this excessive flapwise deflection, it is proposed that shape memory alloy (SMA) wires be used to return the turbine blade back to its optimal operational shape. The work presented here details the analytical and experimental work that was carried out to minimise blade flapping deflection using SMA.

This study proposes a way to overcome the wind blade deflection using shape memory alloy (SMA) wires. A �finite element model has been developed for the simulation of the deflection response of a horizontal axis wind turbine blade using an SMA wire arrangement. The model was developed on the commercial finite element ABAQUSR, and focused on design and analysis, to predict the structural response. Experimental work was carried out to investigate the feasibility of the model based on a plate-like structure. An Artificial Neural Network (ANN) was used to predict the performance of the smart wind turbine blades.

From this study, the model of a smart wind turbine, incorporating SMA wires, was determined to be capable of recovering from large deflections. The coefficient of performance of the smart wind turbine blade was also determined to be higher than the coefficient for a conventional turbine blade. The results showed that by increasing the number of SMA wires, the actuation provided is sufficient to recover from signifi�cant blade deflection resulting in a signifi�cant increase in the lift produced by the blade. It was determined that the coefficient of performance for turbine blades with SMA wires is 0.45 compared to 0.42 for turbine blades without SMA. These fi�ndings will be a signifi�cant achievement in the development of a smart wind turbine blade.
It is expected that the use of smart wind turbine blades, incorporating SMA in their design, will not only increase the power output of the wind turbine but also prolong the lifetime of the turbine blade itself through a reduction of the bending deflections.


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Item Type: Thesis (PhD/Research)
Item Status: Live Archive
Additional Information: Doctor of Philosophy (PhD) thesis.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - No Department
Supervisors: Epaarachchi, Jayantha A.
Date Deposited: 19 Feb 2016 02:03
Last Modified: 19 Feb 2016 02:26
Uncontrolled Keywords: SMA, wind, turbines, blades, flapwise deflection, SMA, shape memory alloy, ABAQUSR
Fields of Research : 09 Engineering > 0999 Other Engineering > 099999 Engineering not elsewhere classified
URI: http://eprints.usq.edu.au/id/eprint/27882

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