Genetic Algorithm Systems for Wind Turbine Management

Sarah Odofin () and Ayodeji Sowale ()
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Sarah Odofin: Northumbria University Newcastle
Ayodeji Sowale: Northumbria University Newcastle

Chapter Chapter 12 in Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy, 2017, pp 141-147 from Springer

Abstract: 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.

Keywords: Wind turbine; Genetic algorithm; Optimisation; Observation (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-319-43434-6_12

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DOI: 10.1007/978-3-319-43434-6_12

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