Feedback | Help | View MyArticles
jres nameplate
  • Volume/Page
  • Keyword
  • DOI
  • Citation
  • Advanced
   
 
 
 

Facebook Podcast Flickr Twitter iResearch App

Journal of Renewable and Sustainable Energy / Volume 4 / Issue 2 / REGULAR ARTICLES

J. Renewable Sustainable Energy 4, 023107 (2012); http://dx.doi.org/10.1063/1.3696072 (13 pages)

A bio-inspired approach to enhancing wind power conversion

YongDuan Song1,2, WenChuan Cai2, Peng Li2, and YongSheng Hu3

1School of Automation, Chongqing University, Chongqing 400044, China
2School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
3China Datang Corp. Renewable Power Co. Ltd., Beijing 100039, China

View MapView Map

(Received 2 September 2011; accepted 28 February 2012; published online 26 March 2012)

The primary objective of this investigation is to develop a new control method for wind turbines that can increase their wind energy capture efficiency. Since the resultant wind turbine system dynamics are profoundly nonlinear and coupled with significant uncertainties, traditional model-based control is found to be not only structurally complex but also computationally expensive. Here, we explore two sets of control algorithms to enhance wind to electrical energy conversion. The first accounts for system nonlinearities and external disturbances by integrating variable structure control with adaptive control. The second accommodates the nonlinearities arising from rotor aerodynamics and pitch (actuation) dynamics, as well as external disturbances, through a method inspired by a 1st order human memory/learning model. The second method allows direct maximum power coefficient tracking for winds under the rated speed and ensures rated power output for winds over the rated speed. Basically, it uses the system current and most recent memorized responses, together with past control experience, to generate new control actions. Both rotor dynamics and actuation (pitch) dynamics are reflected indirectly through the observed/measured system response at each instant, and are embedded within the control mechanism. Thus, there is no need for detailed information on the system model or system parameters in the control’s design and implementation. The efficacy of both proposed approaches is analyzed through numerical simulations.

© 2012 American Institute of Physics

Article Outline

  1. INTRODUCTION
  2. SYSTEM DESCRIPTION
    1. Power generation
    2. Wind turbine rotor dynamics
    3. Pitch dynamics
  3. CONTROL DESIGN FOR WIND TURBINES
    1. Adaptive variable structure control (A-VSC)
      1. Algorithm description
      2. Simulation results
    2. Memory-based control
      1. Inspiration for memory-based control
      2. Memory-based control for pitch angle and electromagnetic torque adjustment
      3. Simulation results
  4. CONCLUSION

RELATED DATABASES

To view database links for this article, you need to log in.

KEYWORDS, PACS, and IPC

Keywords

adaptive control, learning systems, maximum power point trackers, nonlinear control systems, numerical analysis, power generation control, variable structure systems, wind power plants, wind turbines

PACS

  • 88.50.Mp

    Electricity generation, grid integration from wind

International Patent Classification (IPC)

  • H02M3/00

    Conversion of dc power input into dc power output

  • H02M

    Apparatus for conversion between ac and ac, between ac and dc, or between dc and dc, and for use with mains or similar power supply systems; Conversion of dc or ac input power into surge output power; Control or regulation thereof

  • G05B13/00

    Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion

  • F03D

    Wind motors

ARTICLE DATA

Digital Object Identifier
http://dx.doi.org/10.1063/1.3696072

PUBLICATION DATA

ISSN

1941-7012 (online)

Publisher

$abstract.society.value is a Member of CrossRef American Institute of Physics

For access to fully linked references, you need to log in.

    References


Figures (13) Tables (1)

Access to article objects (figures, tables, multimedia) requires a subscription; log in to view available files.
(Access to supplementary files, where available, is free for this journal.)

Access to article objects (figures, tables, multimedia) requires a subscription; log in to view available files.
(Access to supplementary files, where available, is free for this journal.)



Close

Google Calendar

ADVERTISEMENT

Your Recent History Recent History Help

Recently Viewed

  1. A bio-inspired approach to enhancing wind power conversion
Go to AIP Home   © AIP Publishing LLC
Rights and Permissions  |   Disclaimer   |   Subscriptions and Pricing
close