Ravi Pandit

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David InfieldProfessor of Renewable Energy Technologies, University of StrathclydeAdresse e-mail validée de eee.strath.ac.uk
Davide AstolfiUniversità di BresciaAdresse e-mail validée de unibs.it
Matilde Santos PeñasFull Professor of Computer Science and Physics, Complutense University of MadridAdresse e-mail validée de ucm.es
Athanasios KoliosProfessor in Risk and Asset ManagementAdresse e-mail validée de dtu.dk
Jiarong HongUniversity of MinnesotaAdresse e-mail validée de umn.edu
Jesús Enrique Sierra GarciaUniversidad de BurgosAdresse e-mail validée de ubu.es
Linyue GaoAssistant Professor, University of Colorado DenverAdresse e-mail validée de ucdenver.edu
James CarrollUniversity of StrathclydeAdresse e-mail validée de strath.ac.uk
Isidro Durazo-CardenasCranfield UniversityAdresse e-mail validée de cranfield.ac.uk
Tim DodwellCo founder & CTO at digiLab, Professor at University ExeterAdresse e-mail validée de digilab.co.uk
Adam SobeyProgramme Director, Data-Centric Engineering, The Alan Turing Institute/Professor of Data-CentricAdresse e-mail validée de soton.ac.uk
Rafael López MartínezUniversidad Complutense de MadridAdresse e-mail validée de ucm.es
JUAN CHIACHIO RUANOUniversity of GranadaAdresse e-mail validée de ugr.es
Sofia KoukouraResearch Associate, University of StrathclydeAdresse e-mail validée de strath.ac.uk
Francesco CastellaniUniversity of PerugiaAdresse e-mail validée de unipg.it
Alfredo VaccaroUniversità degli studi del SannioAdresse e-mail validée de unisannio.it
Marco PasettiUniversità degli Studi di BresciaAdresse e-mail validée de unibs.it
Fabrizio De CaroUniversità degli Studi del SannioAdresse e-mail validée de unisannio.it
Pablo Andres Buestán-AndradePhD Student, Complutense University of MadridAdresse e-mail validée de ucm.es
Dr. Anh Minh TANGEcole nationale des ponts et chaussées - Institut Polytechnique de ParisAdresse e-mail validée de enpc.fr

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Ravi Pandit

Lecturer (Assistant Professor) in Instrumentation and AI, Cranfield University

Adresse e-mail validée de cranfield.ac.uk - Page d'accueil

Wind Energy Applied data science & ML Uncertainity Quantification predictive maintenance


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
SCADA - based wind turbine anomaly detection using Gaussian Process models for wind turbine condition monitoring purposes R Pandit, D Infield IET Renewable Power Generation, 2018	126	2018
SCADA data for wind turbine data-driven condition/performance monitoring: A review on state-of-art, challenges and future trends SM Pandit R, Astolfi D, Hong J, Infield D Wind Engineering, 2022	98*	2022
Gaussian process power curve models incorporating wind turbine operational variables RK Pandit, D Infield, A Kolios Energy Reports 6, 1658-1669, 2020	72	2020
Incorporating air density into a Gaussian process wind turbine power curve model for improving fitting accuracy RK Pandit, D Infield, J Carroll Wind Energy 22 (2), 302-315, 2019	61	2019
Comparison of advanced non-parametric models for Wind Turbine Power Curves R Pandit, D Infield, A Kolios IET Renewable Power Generation, 2019	56	2019
Wind turbine pitch reinforcement learning control improved by PID regulator and learning observer JE Sierra-Garcia, M Santos, R Pandit Engineering Applications of Artificial Intelligence 111, 104769, 2022	53	2022
Operational Variables for improving industrial wind turbine Yaw Misalignment early fault detection capabilities using data-driven techniques R Pandit, D Infield, T Dodwell IEEE Transactions on Instrumentation and Measurement, 2021	50	2021
Comparative assessments of binned and support vector regression-based blade pitch curve of a wind turbine for the purpose of condition monitoring RK Pandit, D Infield International Journal of Energy and Environmental Engineering 10 (2), 181-188, 2019	48	2019
Gaussian process operational curves for wind turbine condition monitoring R Pandit, D Infield Energies 11 (7), 1631, 2018	47	2018
SCADA Data-Based Support Vector Machine Wind Turbine Power Curve Uncertainty Estimation and Its Comparative Studies R Pandit, A Kolios Applied Sciences 10 (23), 8685, 2020	45	2020
Comparative analysis of Gaussian Process power curve models based on different stationary covariance functions for the purpose of improving model accuracy RK Pandit, D Infield Renewable Energy, 2019	41	2019
Data‐driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance RK Pandit, A Kolios, D Infield IET Renewable Power Generation 14 (13), 2386-2394, 2020	40	2020
Stochastic assessment of aerodynamics within offshore wind farms based on machine-learning M Richmond, A Sobey, R Pandit, A Kolios Renewable Energy 161, 650-661, 2020	38	2020
Accounting for environmental conditions in data-driven wind turbine power models R Pandit, D Infield, M Santos IEEE Transactions on Sustainable Energy 14 (1), 168-177, 2022	37	2022
A review of predictive techniques used to support decision making for maintenance operations of wind turbines RK Pandit, D Astolfi, I Durazo Cardenas Energies 16 (4), 1654, 2023	25	2023
Discussion of wind turbine performance based on SCADA data and multiple test case analysis D Astolfi, R Pandit, L Terzi, A Lombardi Energies 15 (15), 5343, 2022	25	2022
Use of state-of-art machine learning technologies for forecasting offshore wind speed, wave and misalignment to improve wind turbine performance M Sacie, M Santos, R López, R Pandit Journal of Marine Science and Engineering 10 (7), 938, 2022	24	2022
Open O&M: Robust O&M Open Access Tool for Improving Operation and Maintenance of Offshore wind Turbines JCR Athanasios Kolios, Julia Walgern, Sofia Koukoura,Ravi Pandit Proceedings of the 29th European Safety and Reliability Conference (ESREL), 7, 2019	21*	2019
Data-Driven assessment of wind turbine performance decline with age and interpretation based on comparative test case analysis D Astolfi, R Pandit, L Celesti, M Vedovelli, A Lombardi, L Terzi Sensors 22 (9), 3180, 2022	20	2022
Multivariate wind turbine power curve model based on data clustering and polynomial LASSO regression D Astolfi, R Pandit Applied Sciences 12 (1), 72, 2021	20	2021

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