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Modelling Technology Transfer in Green IT with Multi-agent System Read chapter Read first chapter

2017 | OriginalPaper | Chapter

12. Genetic Algorithm Systems for Wind Turbine Management

Authors : Sarah Odofin, Ayodeji Sowale

Published in: Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy

Publisher: Springer International Publishing

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Abstract

In this paper, the importance of wind turbine renewable energy management is important. Wind turbine is sophisticated, expensive and complicated in nature. Fault diagnosis is vital for wind turbine healthy operational state for reliability that is of high priority prognostic for effective management system. A novel algorithm is proposed to optimise the observer monitoring system performance to support practical operation. Reducing unplanned maintenance costs for uninterrupted healthy reliable operations will aid the online monitoring of the turbine behaviour.

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Literature
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Odofin, S., Gao, Z., & Sun, K. (2015). Robust fault diagnosis for wind turbine systems subjected to multi-faults. International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering WASET, 9(2).
Odofin, S. O., Ghassemlooy, Z., Kai, S., & Gao, Z. (2014). Simulation study of fault detection and diagnosis for wind turbine system. PGNet. In 15th Annual Postgraduate Symposium on the Convergence of Telecommunications, Network and Broadcasting, Liverpool, UK, June 2014.
Tchakoua, P., Wamkeue, R., Ouhrouche, M., Slaoui-Hasnaoui, F., Tameghe, T. A., & Ekemb, G. (2014). Wind turbine condition monitoring: State-of-the-art review, new trends, and future challenges. Energies, 7(4), 2595–2630.CrossRef
Zhu, Y., & Gao, Z. (2014). Robust observer-based fault detection via evolutionary Optimization with applications to wind turbine systems. In Proc. IEEE 9th Conference on Industrial Electronics and Applications, Hangzhou (pp. 1627–1632).
Metadata
Title
Genetic Algorithm Systems for Wind Turbine Management
Authors
Sarah Odofin
Ayodeji Sowale
Copyright Year
2017
Book
Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy

Print ISBN: 978-3-319-43433-9

Electronic ISBN: 978-3-319-43434-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-43434-6_12

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