Preprints
https://doi.org/10.5194/wes-2018-19
https://doi.org/10.5194/wes-2018-19
24 May 2018
 | 24 May 2018
Status: this preprint has been retracted.

Hybrid adaptive control for variable-speed variable-pitch wind energy systems using general regression neural network

Xiuxing Yin

Abstract. This paper presents a novel hybrid adaptive control approach for the VS-VP half-direct driven WECS by combining pitch control with variable generator torque regulation in different operating regions. A general regression neural network (GRNN) is employed to derive the reference commands of generator torque and pitch angle from the real-time signals of generator power and speed. Furthermore, a fast and effective nonlinear PID pitch controller is presented to track the reference command of pitch angle in the full load region. The proposed GRNN based hybrid adaptive control strategies have been developed and validated using simulations. This study shows that the proposed method is much faster, more accurate and effective than conventional linear control approach.

This preprint has been retracted.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Xiuxing Yin

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Xiuxing Yin
Xiuxing Yin

Viewed

Total article views: 2,670 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,119 475 76 2,670 90 91
  • HTML: 2,119
  • PDF: 475
  • XML: 76
  • Total: 2,670
  • BibTeX: 90
  • EndNote: 91
Views and downloads (calculated since 24 May 2018)
Cumulative views and downloads (calculated since 24 May 2018)

Viewed (geographical distribution)

Total article views: 2,043 (including HTML, PDF, and XML) Thereof 2,007 with geography defined and 36 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 May 2024
Download

This preprint has been retracted.

Altmetrics