Sparse-Sensor Placement for Wind Farm Control

Kathryn Johnson, Paul Fleming, Christopher Bay, Timothy Taylor, Lucy Pao, Katherine Dykes

Research output: Contribution to journalArticlepeer-review

15 Scopus Citations


The objective of this paper is to incorporate sparse sensor data to improve flow-field estimates in a wind farm, which can then be used to perform better online wind farm optimization and control. A sparse-sensing algorithm is used to determine the optimal locations of sensors to improve the overall estimation precision of the flow field within the wind farm. This algorithm takes advantage of the dominant atmospheric structures in a wind farm to reconstruct the flow field from point measurements in the field. These measurements, in their optimal locations, have the ability to improve the observability of a wind farm and thus provide faster, more accurate, state estimation.

Original languageAmerican English
Article numberArticle No. 032019
Number of pages10
JournalJournal of Physics: Conference Series
Issue number3
StatePublished - 19 Jun 2018
Event7th Science of Making Torque from Wind, TORQUE 2018 - Milan, Italy
Duration: 20 Jun 201822 Jun 2018

Bibliographical note

Publisher Copyright:
© Published under licence by IOP Publishing Ltd.

NREL Publication Number

  • NREL/JA-5000-71428


  • sensors
  • sparse sensing
  • wind energy
  • wind farm
  • wind plant controls


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