Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Wake‐effect aware optimal online control of wind farms : an explicit solution

Tools
- Tools
+ Tools

Chen, Kaixuan, Qiu, Yiwei, Lin, Jin, Liu, Feng, Zhao, Xiaowei and Song, Yonghua (2021) Wake‐effect aware optimal online control of wind farms : an explicit solution. IET Renewable Power Generation, 15 (4). pp. 877-888. doi:10.1049/rpg2.12078

[img]
Preview
PDF
WRAP-wake‐effect-aware-optimal-online-control-wind-farms-explicit-solution-Zhao-2020.pdf - Published Version - Requires a PDF viewer.
Available under License Creative Commons Attribution 4.0.

Download (1035Kb) | Preview
Official URL: http://dx.doi.org/10.1049/rpg2.12078

Request Changes to record.

Abstract

Wake effects impose significant aerodynamic interactions among wind turbines. To improve the wind farm operating performance, practical wind farm online control considering wake effects becomes very important. To achieve online optimal wind farm control while responding to grid demands, this paper proposes a novel optimal wind farm supervisory control (SC) model and its explicit solutions. From the controller modelling perspective, the two major wind farm operating modes, the maximum power point tracking mode and the set‐point tracking mode, are first analysed and unified in one optimisation model while considering wake effects. In this way, wind farm power production and rotor kinetic energy reserve can be simultaneously considered to conveniently modify the operation mode in response to different grid demands. Aside from controller modelling, the collocation method is first introduced to address the online application problem of such wake‐effect aware optimal WF control. Although a few optimisation algorithms have been proposed to find the optimum offline, online optimal control is still challenging because of the computational complexity brought by wake model non‐linearity and non‐convexity. The proposed collocation method explicitly approximates the optimal solutions to the proposed supervisory control model, through which only a direct algebraic operation is required for online optimal control instead of repeated optimisations. Case studies are carried out on different wind farms under various wind conditions, showing that the wind farm power production potential and releasable power reserve are improved compared to traditional greedy control in both modes. The accuracy of the collocation method is verified. A detailed analysis of the wind farm production capacity under different wind speeds and directions is also provided.

Item Type: Journal Article
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH): Wind turbines, Wind turbines -- Aerodynamics, Wind turbines -- Rotors, Wind power plants
Journal or Publication Title: IET Renewable Power Generation
Publisher: The Institution of Engineering and Technology
ISSN: 1752-1424
Official Date: 16 March 2021
Dates:
DateEvent
16 March 2021Published
20 January 2021Available
2 November 2020Accepted
Volume: 15
Number: 4
Page Range: pp. 877-888
DOI: 10.1049/rpg2.12078
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
Funder: EPSRC
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/R007470/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
51761135015[NSFC] National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us