DocumentCode :
551421
Title :
Neural networks for condition monitoring of wind turbines
Author :
Brandão, R. F Mesquita ; Carvalho, J. A Beleza ; Barbosa, F. P Maciel
Author_Institution :
Dept. of Electr. Eng., INESC Porto, Oporto, Portugal
fYear :
2010
fDate :
20-22 Sept. 2010
Firstpage :
1
Lastpage :
4
Abstract :
Wind energy is the renewable energy source considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or located offshore and these factors increase the referred operation and maintenance cost. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.
Keywords :
computerised monitoring; condition monitoring; maintenance engineering; neural nets; power engineering computing; power generation economics; power system management; power system measurement; renewable energy sources; sustainable development; wind power plants; wind turbines; condition monitoring; fossil power generation; neural network; renewable energy source; sustainable energy; wind farm; wind power; wind turbine; Circuit faults; Gears; Maintenance engineering; Mathematical model; Temperature measurement; Wind; Wind turbines; Condition Monitoring; maintenance; neural networks; wind energy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modern Electric Power Systems (MEPS), 2010 Proceedings of the International Symposium
Conference_Location :
Wroclaw
Print_ISBN :
978-83-921315-7-1
Type :
conf
Filename :
6007206
Link To Document :
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