Preprints
https://doi.org/10.5194/wes-2021-55
https://doi.org/10.5194/wes-2021-55
15 Jun 2021
 | 15 Jun 2021
Status: this preprint has been withdrawn by the authors.

Wind Turbine Ice Detection Using AEP Loss Method – A Case Study

Jia Yi Jin, Timo Karlsson, and Muhammad S. Virk

Abstract. Ice detection of wind turbine and estimating the resultant production losses is challenging, but very important, as wind energy project decisions in cold regions are based on these estimated results. This paper describes the comparison of a statistical (T19IceLossMethod) and numerical (Computational Fluid Dynamics, CFD) case study of wind resource assessment and estimation of resultant Annual Energy Production (AEP) due to ice of a wind park in ice prone cold region. Three years Supervisory Control and Data Acquisition (SCADA) data from a wind park located in arctic region is used for this study. Statistical analysis shows that the relative power loss due to icing related stops is the main issue for this wind park. To better understand the wind flow physics and estimation of the wind turbine wake losses, Larsen wake model is used for the CFD simulations, where results show that it is important to use the wake loss model for CFD simulations of wind resource assessment and AEP estimation of a wind park. A preliminary case study about wind park layout optimization has also been carried out which shows that AEP can be improved by optimizing the wind park layout and CFD simulations can be a good tool.

This preprint has been withdrawn.

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.
Jia Yi Jin, Timo Karlsson, and Muhammad S. Virk

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2021-55', Anonymous Referee #1, 13 Jul 2021
  • RC2: 'Comment on wes-2021-55', Anonymous Referee #2, 04 Oct 2021

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2021-55', Anonymous Referee #1, 13 Jul 2021
  • RC2: 'Comment on wes-2021-55', Anonymous Referee #2, 04 Oct 2021
Jia Yi Jin, Timo Karlsson, and Muhammad S. Virk
Jia Yi Jin, Timo Karlsson, and Muhammad S. Virk

Viewed

Total article views: 897 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
525 341 31 897 28 26
  • HTML: 525
  • PDF: 341
  • XML: 31
  • Total: 897
  • BibTeX: 28
  • EndNote: 26
Views and downloads (calculated since 15 Jun 2021)
Cumulative views and downloads (calculated since 15 Jun 2021)

Viewed (geographical distribution)

Total article views: 889 (including HTML, PDF, and XML) Thereof 889 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 06 Oct 2024
Download

This preprint has been withdrawn.

Short summary
In this manuscript, a numerical case study has been presented regarding ice detection and wind resource assessment in ice prone cold regions. Three years SCADA data from a wind park in Arctic region is used for this study. T19IceLossMethod based statistical analysis and Computational Fluid Dynamics (CFD) based numerical simulations are carried out for icing events classification and wind resource assessment, as well as estimation of resultant Annual Energy Production (AEP).
Altmetrics