Browse by Author or creator

Pandit, Ravi and Astolfi, Davide and Hong, Jiarong and Infield, David and Santos, Matilde (2022) SCADA data for wind turbine data-driven condition/performance monitoring : a review on state-of-art, challenges and future trends. Wind Engineering, 47 (2). pp. 422-441. ISSN 0309-524X

Richmond, M. and Sobey, A. and Pandit, R. and Kolios, A. (2020) Stochastic assessment of aerodynamics within offshore wind farms based on machine-learning. Renewable Energy, 161. pp. 650-661. ISSN 0960-1481

Pandit, Ravi Kumar and Infield, David and Kolios, Athanasios (2020) Gaussian process power curve models incorporating wind turbine operational variables. Energy Reports, 6. pp. 1658-1669. ISSN 2352-4847

Pandit, Ravi and Kolios, Athanasios and Infield, David (2020) Data-driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance. IET Renewable Power Generation, 14 (13). pp. 2386-2394. ISSN 1752-1416

Pandit, Ravi Kumar and Infield, David (2019) Comparative analysis of Gaussian Process power curve models based on different stationary covariance functions for the purpose of improving model accuracy. Renewable Energy, 140. pp. 190-202. ISSN 0960-1481

Kolios, Athanasios and Walgern, Julia and Koukoura, Sofia and Pandit, Ravi and Chiachio-Ruano, Juan; (2019) openO&M : Robust O&M open access tool for improving operation and maintenance of offshore wind turbines. In: Proceedings of the 29th European Safety and Reliability Conference. Research Publishing, DEU, pp. 629-625. ISBN 978981112723

Pandit, Ravi Kumar and Infield, David and Kolios, Athanasios (2019) Comparison of advanced non-parametric models for wind turbine power curves. IET Renewable Power Generation, 13 (9). pp. 1503-1510. ISSN 1752-1416

Pandit, Ravi Kumar and Infield, David (2019) SCADA based nonparametric models for condition monitoring of a wind turbine. The Journal of Engineering. pp. 1-5. ISSN 2051-3305

Pandit, Ravi and Infield, David; (2018) Comparative analysis of binning and support vector regression for wind turbine rotor speed based power curve use in condition monitoring. In: 2018 53rd International Universities Power Engineering Conference (UPEC). IEEE, GBR. ISBN 9781538629109

Pandit, Ravi Kumar and Infield, David and Carroll, James (2018) Incorporating air density into a Gaussian process wind turbine power curve model for improving fitting accuracy. Wind Energy. pp. 1-14. ISSN 1095-4244

Pandit, Ravi Kumar and Infield, David (2018) Comparative assessments of binned and support vector regression-based blade pitch curve of a wind turbine for the purpose of condition monitoring. International Journal of Energy and Environmental Engineering. pp. 1-8. ISSN 2008-9163

Pandit, Ravi Kumar and Infield, David (2018) Comparative analysis of binning and Gaussian Process based blade pitch angle curve of a wind turbine for the purpose of condition monitoring. Journal of Physics: Conference Series, 1102 (1). 012037. ISSN 1742-6588

Pandit, Ravi Kumar and Infield, David (2018) Comparison of binned and Gaussian Process based wind turbine power curves for condition monitoring purposes. Journal of Maintenance Engineering, 2.

Pandit, Ravi Kumar and Infield, David (2018) Comparative study of binning and gaussian process based rotor curves of a wind turbine for the purpose of condition monitoring. In: 3rd International Conference on Offshore Renewable Energy, 2018-08-29 - 2018-08-30.

Pandit, Ravi and Infield, David (2018) Gaussian process operational curves for wind turbine condition monitoring. Energies, 11 (7). ISSN 1996-1073

Pandit, Ravi Kumar and Infield, David (2018) Performance assessment of a wind turbine using SCADA based Gaussian Process model. International Journal of Prognostics and Health Management, 9 (1). 023. ISSN 2153-2648

Pandit, Ravi Kumar and Infield, David (2018) SCADA-based wind turbine anomaly detection using Gaussian Process (GP) models for wind turbine condition monitoring purposes. IET Renewable Power Generation. ISSN 1752-1416

Pandit, Ravi and Infield, David; (2018) QQ plot for assessment of Gaussian Process wind turbine power curve error distribution function. In: 9th European Workshop on Structural Health Monitoring. British Institute of Non-Destructive Testing, GBR. (In Press)

Pandit, Ravi Kumar and Infield, David; (2017) Using Gaussian process theory for wind turbine power curve analysis with emphasis on the confidence intervals. In: 2017 6th International Conference on Clean Electrical Power (ICCEP). IEEE, ITA, pp. 744-749. ISBN 978-1-5090-4683-6