Collective control of a cluster of stall regulated wind turbines

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

Abstract

Collective control of a small cluster of wind turbines using a single controller is investigated to enable simplification of the turbines. For simplicity, reduced cost, and possibly improved reliability, each turbine is constant speed stall regulated. In return, each turbine experiences reduced energy capture and increased loads, and these disadvantages become greater as the number of wind turbines in the cluster increases. In this paper, a cluster consisting of 5 turbines is assessed in comparison to the situation with each turbine having its own converter and controller. A new collective control strategy that acts in response to the poorest control is proposed as opposed to acting in response to the average control. The control strategy is applied to a cluster model, which is also developed in this paper by modifying a Matlab/SIMULINK® simulation model of the SUPERGEN 5MW exemplar wind turbine, and simulation results demonstrate that the control strategy could be more cost effective than each turbine having its own converter and controller, especially with optimal design of rotors.
Original languageEnglish
Title of host publicationInternational Conference on Sustainable Power Generation and Supply (SUPERGEN 2012)
Place of PublicationPiscataway, NJ, United States
PublisherIEEE
Pages1-8
Number of pages8
ISBN (Print)9781849196734
DOIs
Publication statusPublished - 9 Sep 2012
EventIET International Conference on Sustainable Power Generation and Supply - Hangzhou, China
Duration: 8 Sep 20129 Sep 2012
http://www.ukchinanet.com/UK-China%20Network_conference%20website%20HZ.html

Conference

ConferenceIET International Conference on Sustainable Power Generation and Supply
Abbreviated titleSUPERGEN 2012
Country/TerritoryChina
CityHangzhou
Period8/09/129/09/12
Internet address

Keywords

  • wind turbine control
  • collective control
  • wind turbine modelling
  • Model Predictive Control

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