Fleet oriented pattern mining combined with time series signature extraction for understanding of wind farm response to storm conditions

Pieter-Jan Daems, Len Feremans, Timothy Verstraeten, Boris Cule, Bart Goethals, Jan Helsen

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

Offshore wind turbine installations are rapidly spreading around Europe and all over the world. These turbines are typically installed in large wind farms combining turbines of the same type. Farm owners target maximal performance of the farm in general and particularly predictability of behaviour. The latter is getting increasingly important since offshore wind farms are being managed more and more as conventional power plants driven by the electricity market supply and demand considerations. The context of zero subsidy farms exposes farm operators to fluctuations in electricity market prices. As such, deep understanding of farm behaviour is essential to come up with a good strategy to deal with these fluctuations.
Original languageEnglish
Title of host publication World conference for condition monitoring
EditorsLen Gelman, Nadine Martin, Andrew A. Malcolm, Chin Kian (Edmund) Liew
PublisherSpringer
Pages271-283
Number of pages13
Edition2
ISBN (Electronic)978-981-15-9199-0
ISBN (Print)978-981-15-9198-3
DOIs
Publication statusPublished - 2020
EventWorld Congress on Condition Monitoring - Singapore, Singapore
Duration: 1 Dec 20195 Dec 2019
https://wccm2019.org/

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

ConferenceWorld Congress on Condition Monitoring
Abbreviated titleWCCM
Country/TerritorySingapore
CitySingapore
Period1/12/195/12/19
Internet address

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Singapore Pte Ltd.

Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.

Keywords

  • Pattern mining
  • fleet analysis
  • Wind energy

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