Tuhfe Gocmen
Tuhfe Gocmen
Researcher DTU Wind Energy
Verified email at dtu.dk
Title
Cited by
Cited by
Year
Wind turbine wake models developed at the technical university of Denmark: A review
T Göçmen, P Van der Laan, PE Réthoré, AP Diaz, GC Larsen, S Ott
Renewable and Sustainable Energy Reviews 60, 752-769, 2016
1992016
Airfoil optimization for noise emission problem and aerodynamic performance criterion on small scale wind turbines
T Göçmen, B Özerdem
Energy 46 (1), 62-71, 2012
1012012
Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms
T Göçmen, G Giebel
Renewable energy 99, 524-532, 2016
442016
Turbine control strategies for wind farm power optimization
M Mirzaei, T Göçmen, G Giebel, PE Sĝrensen, NK Poulsen
2015 American Control Conference (ACC), 1709-1714, 2015
322015
Wind speed estimation and parametrization of wake models for downregulated offshore wind farms within the scope of PossPOW project
TG Bozkurt, G Giebel, NK Poulsen, M Mirzaei
Journal of Physics: Conference Series 524 (1), 012156, 2014
252014
Possible Power Estimation of Down-Regulated Offshore Wind Power Plants.
T Gögmen
Education 2015, 14, 2012
212012
Expert elicitation on wind farm control
JW van Wingerden, PA Fleming, T Göçmen, I Eguinoa, BM Doekemeijer, ...
Journal of Physics: Conference Series 1618 (2), 022025, 2020
162020
Data-driven wake modelling for reduced uncertainties in short-term possible power estimation
T Göçmen, G Giebel
Journal of Physics: Conference Series 1037 (7), 072002, 2018
132018
Optimizing wind farm control through wake steering using surrogate models based on high-fidelity simulations
P Hulsman, SJ Andersen, T Göçmen
Wind Energy Science 5 (1), 309-329, 2020
112020
Possible power of down‐regulated offshore wind power plants: The PossPOW algorithm
T Göçmen, G Giebel, NK Poulsen, PE Sĝrensen
Wind Energy 22 (2), 205-218, 2019
112019
Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm
T Duc, O Coupiac, N Girard, G Giebel, T Göçmen
Wind Energy Science 4 (2), 287-302, 2019
102019
Possible improvements for present wind farm models used in optimal wind farm controllers
J Kazda, T Göçmen, G Giebel, N Cutululis
Wind Integration Workshop, 2016
72016
Framework of multi-objective wind farm controller applicable to real wind farms
J Kazda, T Göçmen, G Giebel, M Courtney, N Cutululis
WindEurope Summit 2016, 2016
72016
Uncertainty quantification of the real-time reserves for offshore wind power plants
T Göçmen, G Giebel, PE Réthoré, JP Murcia Leon
15th Wind Integration Workshop, 15-17, 2016
52016
Estimation of the possible power of a wind farm
M Mirzaei, T Göçmen, G Giebel, PE Sĝrensen, NK Poulsen
IFAC Proceedings Volumes 47 (3), 6782-6787, 2014
52014
Model-free estimation of available power using deep learning
T Göçmen, A Meseguer Urbán, J Liew, AWH Lio
Wind Energy Science 6 (1), 111-129, 2021
22021
Launch of the FarmConners Wind Farm Control benchmark for code comparison
T Göçmen, K Kölle, SJ Andersen, I Eguinoa, T Duc, F Campagnolo, ...
Journal of Physics: Conference Series 1618 (2), 022040, 2020
22020
Optimization of wind farm power production using innovative control strategies
T Duc, G Giebel, T Göçmen, M Korpċs, O Coupiac
DTU Wind Energy, 2017
22017
Posspow: Possible power of offshore wind power plants
G Giebel, T Göçmen, PE Sĝrensen, NK Poulsen, JR Kristoffersen
European Wind Energy Conference & Exhibition 2013, 2013
22013
Applied Machine Learning Techniques for Performance Analysis in Large Wind Farms
JT Lyons, T Göçmen
Energies 14 (13), 3756, 2021
12021
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Articles 1–20