A LiDAR-based pitch control strategy for ultra large wind turbines

  • Wael Farag
  • , Hussien Hassan
  • , Mohamed Saad
  • , Abdel Latif Elshafei

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

4 Scopus citations

Abstract

In this paper, a new adaptive predictive pitch control strategy is proposed. The proposed technique utilizes the future wind speed measurements provided by a light detection and ranging (LiDAR) apparatus. This apparatus supplies a feedforward controller with the incoming wind speed readings, which then generates an early control action that reduces generator speed variation and prevents suddenly generated power drop. The proposed feedforward controller is adaptive and got tuned online as well using the LiDAR wind measurements data. Moreover, a Robust Model Predictive feedback Controller (RMPC) is designed to augment the pitch control action with a component that reflects the fluctuation of the generator speed. The proposed control strategy is compared to that of a conventional gain-scheduled PI controller and tested on a 5-MW realistic wind turbine model against extreme turbulent wind profiles. Simulation results have proved the superiority of the proposed controller in improving both the power quality and the generator speed regulation as well as increasing the harvested power.

Original languageEnglish (US)
Title of host publication2017 19th International Middle-East Power Systems Conference, MEPCON 2017 - Proceedings
EditorsAbdallah M. Elsayed
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages451-458
Number of pages8
ISBN (Electronic)9781538609903
DOIs
StatePublished - Jul 2 2017
Event19th International Middle-East Power Systems Conference, MEPCON 2017 - Cairo, Egypt
Duration: Dec 19 2017Dec 21 2017

Publication series

Name2017 19th International Middle-East Power Systems Conference, MEPCON 2017 - Proceedings
Volume2018-February

Conference

Conference19th International Middle-East Power Systems Conference, MEPCON 2017
Country/TerritoryEgypt
CityCairo
Period12/19/1712/21/17

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Energy Engineering and Power Technology

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