Incorporating air density into a Gaussian process wind turbine power curve model for improving fitting accuracy

Research output

Research output per year 2018 2019

• 17 Citations
• 8 Article
• 1 Conference contribution book
• 1 Proceeding
• 1 Conference Contribution

Research output per year

Research output per year

Search results

• 2019

  Comparative analysis of Gaussian Process power curve models based on different stationary covariance functions for the purpose of improving model accuracy

  Pandit, R. K. & Infield, D., 30 Sep 2019, In: Renewable Energy. 140, p. 190-202 13 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Condition monitoring
  • Wind turbines
  • Exponential functions
  • Fault detection
  • Chemical analysis
  10 Citations (Scopus)

  7 Downloads (Pure)

• Comparison of advanced non-parametric models for wind turbine power curves

  Pandit, R. K., Infield, D. & Kolios, A., 8 Jul 2019, In: IET Renewable Power Generation. 13, 9, p. 1503-1510 8 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Wind turbines
  • Support vector machines
  • Curve fitting
  • Fault detection
  • Statistical methods
  13 Citations (Scopus)

  44 Downloads (Pure)
• 2018

  Comparative analysis of binning and Gaussian Process based blade pitch angle curve of a wind turbine for the purpose of condition monitoring

  Pandit, R. K. & Infield, D., 10 Oct 2018, In: Journal of Physics: Conference Series. 1102, 1, 10 p., 012037 .

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Condition monitoring
  • Turbomachine blades
  • Wind turbines
  • Monitoring
  5 Citations (Scopus)

  16 Downloads (Pure)

• Comparative assessments of binned and support vector regression-based blade pitch curve of a wind turbine for the purpose of condition monitoring

  Pandit, R. K. & Infield, D., 12 Oct 2018, In: International Journal of Energy and Environmental Engineering. p. 1-8 8 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Condition monitoring
  • Turbomachine blades
  • Wind turbines
  • Turbine components
  • Anomaly detection
  12 Citations (Scopus)

  11 Downloads (Pure)

• Comparison of binned and Gaussian Process based wind turbine power curves for condition monitoring purposes

  Pandit, R. K. & Infield, D., 1 Sep 2018, In: Journal of Maintenance Engineering. 2, 12 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Condition monitoring
  • Wind turbines
  • Curve fitting
  • Bins
  • Anomaly detection
  33 Downloads (Pure)

• Gaussian process operational curves for wind turbine condition monitoring

  Pandit, R. & Infield, D., 22 Jun 2018, In: Energies. 11, 7, 20 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Condition monitoring
  • Wind turbines
  • Data acquisition
  • Turbines
  • Costs
  15 Citations (Scopus)

  25 Downloads (Pure)

• Performance assessment of a wind turbine using SCADA based Gaussian Process model

  Pandit, R. K. & Infield, D., 20 Jun 2018, In: International Journal of Prognostics and Health Management. 9, 1, 8 p., 023.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Wind turbines
  • Turbines
  • Condition monitoring
  • Power generation
  40 Downloads (Pure)

• SCADA-based wind turbine anomaly detection using Gaussian Process (GP) models for wind turbine condition monitoring purposes

  Pandit, R. K. & Infield, D., 31 May 2018, In: IET Renewable Power Generation. 9 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Anomaly detection
  • Condition monitoring
  • Wind turbines
  • Bins
  • Probability distributions
  28 Citations (Scopus)

  42 Downloads (Pure)