Adaptive Data Processing Technique for Lidar-Assisted Control to Bridge the Gap between Lidar Systems and Wind Turbines: Preprint

Andrew Scholbrock, Paul Fleming, David Schlipf, Steffen Raach, Florian Haizmann, Raghu Krishnamurthy, Matthieu Boquet, Po Cheng

Research output: Contribution to conferencePaper

Abstract

This paper presents first steps toward an adaptive lidar data processing technique crucial for lidar-assisted control in wind turbines. The prediction time and the quality of the wind preview from lidar measurements depend on several factors and are not constant. If the data processing is not continually adjusted, the benefit of lidar-assisted control cannot be fully exploited, or can even result in harmful control action. An online analysis of the lidar and turbine data are necessary to continually reassess the prediction time and lidar data quality. In this work, a structured process to develop an analysis tool for the prediction time and a new hardware setup for lidar-assisted control are presented. The tool consists of an online estimation of the rotor effective wind speed from lidar and turbine data and the implementation of an online cross correlation to determine the time shift between both signals. Further, initial results from an ongoing campaign in which this system was employed for providing lidar preview for feed-forward pitch control are presented.
Original languageAmerican English
Number of pages9
StatePublished - 2015
EventEWEA 2015 Annual Event - Paris, France
Duration: 17 Nov 201520 Nov 2015

Conference

ConferenceEWEA 2015 Annual Event
CityParis, France
Period17/11/1520/11/15

NREL Publication Number

  • NREL/CP-5000-65273

Keywords

  • data processing
  • feedforward lidar
  • LIDAR-assisted
  • NREL
  • wind turbine controls

Fingerprint

Dive into the research topics of 'Adaptive Data Processing Technique for Lidar-Assisted Control to Bridge the Gap between Lidar Systems and Wind Turbines: Preprint'. Together they form a unique fingerprint.

Cite this