WIND FARM OPERATION AND MAINTENANCE OPTIMIZATION USING BIG DATA

Jan Helsen, Cédric Peeters, Peter Doro, Eline Ververs, pieter jan jordaens

Onderzoeksoutput: Other chapter contributionResearch

13 Citaten (Scopus)

Samenvatting

In the current electricity production mix wind energy is claiming a significant part. In order to guarantee stable electricity production predictability of the wind farm operational behaviour is essential. Big data approaches have the potential for a significant role in realizing this goal. In order to gain insights in turbine operational behaviour it is necessary to obtain a farm wide dataset, containing the operational sensor data of the different machines and context information such as maintenance data. Advanced analytics can use this data for understanding normal and deviating turbine operational behaviour. These insights will help in optimizing the operation and maintenance strategy of the farm. This paper gives an overview of our big data approach for data-storage and illustrates some of our data-analytics research tracks for gaining insights in the underlying failure mechanisms of turbines.

Originele taal-2English
TitelProceedings - 3rd IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2017
Plaats van productieIEEE
UitgeverijIEEE
Pagina's179-184
Aantal pagina's6
Volume10
ISBN van elektronische versie978-1-5090-6318-5
ISBN van geprinte versie978-1-5090-6319-2
DOI's
StatusPublished - 12 jun 2017
EvenementIEEE Big-data service - San Francisco Bay, San Francisco , United States
Duur: 6 apr 201710 apr 2017

Conference

ConferenceIEEE Big-data service
LandUnited States
StadSan Francisco
Periode6/04/1710/04/17

Vingerafdruk

Duik in de onderzoeksthema's van 'WIND FARM OPERATION AND MAINTENANCE OPTIMIZATION USING BIG DATA'. Samen vormen ze een unieke vingerafdruk.

Citeer dit