Poster presentations - WindEurope Technology Workshop 2020

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Analysis of Operating Wind Farms General and Strategy Topics Resource Assessment

PO002	Impact of atmospheric conditions to the quality of day-ahead wind power forecast using Multi-Layer Perceptron neural network Minh-Thang Do, Data Scientist, Meteodyn
PO003	Long Range measurement with a nacelle mounted lidar Julien Tissot, Application Engineer Leosphere
PO004	Comparing Condition Monitoring Techniques in the Wind Industry Daryl Hickey, Reliability Engineer, Natural Power Consultants Ltd
PO006	Assessment of Lost Production using Empirical Remaining-Power-Generation in Turbine Main Bearing Failure Monitoring Jürgen Herp, Assistant Professor, University of Southern Denmark
PO010	An Overview of Wind Energy Production Prediction Bias, Losses, and Uncertainties Joseph Lee, Postdoctoral Researcher, NREL
PO011	Machine learning for improving the accuracy and consistency of operational wind farm analysis Jack Double, Specialist – Operational Wind, K2 Management
PO014	Statistical methods for innovative wind turbine performance control and monitoring Ludovio Terzi, O&M Manager, Renvico
PO015	Sensitivity of Romo Wind Spinner Anemometer iSpin to Environmental Variables: First Experimental Results Davide Trabucchi, Project Engeer, Deutshce Windguard
PO017	Application of a new machine learning method for site-dependent power curve prediction to field measurement data Sarah Barber, Programme Leader Wind Energy, University of Applied Sciences Rapperswil
PO018	Estimation of AEP variation between standard and site-specific power curve using 0 turbulence power curve approximation. Tristan Fleury, Operational Assessment Engineer, EDF Energies Renouvelables
PO019	The Comparison of annual energy production using simulated power curve at site conditions with logging data (Case Study: Kahak Wind Farm in Iran) Alireza Karbalaeimirza, Wind and Siting Engineer, Nordhausen University of Applied Science
PO020	292 Power Curve Test results: statistical analysis as a base for future Energy Yield Estimations Marta Juániz Zurbano, Wind Analyst, Enel Green Power
PO021	Effects of topography on turbine LiDAR measurements; a case study. Cyrille Huant, Asset Advisory Services Renewables, UL International
PO023	REWS Calculation with the Wind Iris 4–beam Julien Tissot, Application Engineer, Leosphere
PO024	Offshore Wind Farm Wake Effects Study with Nacelle Mounted Lidars Ye Feng, Wind Resource Engineer, Shanghai Electri

PO027	How should machine learning be successfully used for wind speed vertical extrapolation? Nicola Bodini, Postdoctoral Researcher, NREL
PO029	An AI-based Fault Detection Model using Alarms and Warnings from the SCADA system Antionio Notaristefano, Electrical Engineer, Nispera AG
PO031	Blade Defect Forecasting – Environmental conditions cause blade defects to develop and add downtime during the turbine lifetime. Icing, rain, lightning and wind and turbulence all add to the degradation of the blade surface and structure. Morten Handberg, Chief Blade Officer, Wind Power Lab
PO036	Estimating wind turbine loads and their uncertainties from SCADA data Wolfgang Moser, Principal Engineer, Innogy SE
PO037	Aerodynamic rotor imbalance detection: Pitch Health Indicator using SCADA data Nicolas Quiévy, Senior Wind Technology Manager, ENGIE
PO040	OpenOA – an open-source codebase for operational analysis of wind farms Eric Simley, Reseacher, NREL
PO045	International Energy Agency (IEA) Wind Task 43 on Wind Energy Digitalization. Opportunities and best practices for digitalization Jason Fields, Senior Research Engineer, NREL
PO046	De-risking assets transfers through transparency Henrik Pedersen, Senior Wind Energy Consultant, EMD International A/S
PO048	Reducing O&M costs of offshore wind farms through data-driven risk-based operations Alexios Koltsidopoulos Papatzimos, Renewables Consultant, Xodus Group

PO051	Uncertainty in offshore wind resources for the U.S.A Reshmi Ghosh, Ph.D. Student, Carnegie Mellon University
PO053	How Certain is Our Estimate of the Future Wind Conditions? – A look at Long-Term Trends Kai Moennich, Senior Engineering Lead, UL International
PO054	IEA Wind Task 31: Initial results of a new comparison metrics simulation challenge for wind resource assessment in complex terrain Sarah Barber, Programme Leader Wind Enery, University of Applied Sciences Rapperswil
PO055	How to Model Ambient Turbulence at Hub Height: A Better Turbulence Vertical Extrapolation is Possible Antonio Angulo, Senior Engineer – Customer Application Engineering, Onshore Wind, GE Renewable Energy
PO056	Improved methods for adjusting mesoscale model outputs to in-situ met mast data Matteo Ranaboldo, Energy Advisor Services Team – EMEA and Latin America, UL International
PO058	Analysis of pre- and post-construction EYAs (17 wind farms), analysis of uncertainty data base (250 pre-construction EYAs): Improving the methodology of pre-construction EYA and reducing uncertainty Nicolas Enrique Veneranda, Project Manager, Tractebel Engineering
PO061	Impact of underlaying boundary conditions databases: how available global topography and land use databases could impact AEP accuracy while increased model resolution is required? Alexis Dutrieux, Managing Director, ATM-PRO
PO062	Comparison of linear (WAsP) and CFD (Meteodyn WT) wind modelling on a complex south African site, with regards to levels of uncertainty. Paul Blondel, Senior Wind Resource Assessment Engineer, EDF Renouvelables
PO065	CFARS Site suitability subgroup: accelerating data-driven guidance for RSD TI corrections Alexandra St. Pé, Technology & Innovation Manager Wind, RWE Renewables
PO067	Assessment of agglomerated LiDAR calibration results as a function of environmental variables Edward Burin des Roziers, Wind Measurement Technical Expert, UL International
PO069	The use of CFD to increase the acceptance of wind data from lidars in complex terrain. Wulstan Nixon, Sales Manager, ZX Lidars
PO070	EOLOS FLS200 performance and uncertainties comparison over different types of pre-deployment verification campaigns Adrià Miquel, Reliability Engineer, Eolis Floating Lidar Solutions
PO072	A method to correct Windcube measurement in complex and forested terrain Paul Mazoyer, Application Engineer, Leosphere
PO073	Why high roughness and forest decrease lidar errors at complex terrain sites Tobias Klaas, Scientific Staff, Fraunhofer IEE
PO075	Assessment of the vector versus scalar averaging method when analyzing Lidar data. Melanie Konrad, Site Assessment, wpd Europe
PO076	Machine learning based approach for turbulence intensity measurement with pulsed DBS-Wind-LiDARs Zouhair Khadiri-Yazami, Research Associate, Fraunhofer IEE
PO077	Use of scanning lidars for advanced measurement applications such as global blockage studies Jens Riechert, DNV GL
PO079	Measuring effects of the Borkum Riffgrund 1 wind farm on FINO1 by means of long range lidar Juan José Trujillo, Research Engineer, UL International
PO081	An average operator for RSD wind data that is neither scalar nor vector Paul Mazoyer, Application Engineer, Leosphere
PO082	Do we need to calibrate Lidars against masts? Matthew Smith, Senior Sales Manager, ZX Lidars
PO083	Quantification of icing loss for wind resource assessments in the Netherlands, using five years of measurement data from an IEC compliant met mast and LiDAR validation. Anna Pulo, Senior Consultant, Navigant, a Guidehouse Company
PO084	TI: FLD vs Mast. Variations over different atmospheric and oceanographic conditions. Adrià Miquel, Reliability Engineer, Eolos Floating Lidar Solutions
PO085	Can I use my nacelle lidar for turbulence characterization? – A comparison study from DNV GL test site Jens Riechert, DNV GL
PO086	CTurbulence intensity comparison from lidar and spinner anemometer measurements in an offshore wind farm Katrin Ritter, Data Analyst, ROMO Wind
PO089	Wide implementation of time series post-processing in CFD site assessment Jonas Schmidt, Researcher, Fraunhofer IWES
PO092	A comparison of spectral and time series based methods for the synthesis of homogeneous and stationary stochastic velocity fields Cristobal Gallego-Castillo, Universidad Politécnica de Madrid
PO093	Synthetic wind speed generation for the simulation of realistic diurnal cycles Daniele D’Ambrioso, Vrije Universiteit Brussel
PO097	A tool to optimise lidar measurement campaigns: How many lidars, where and how long? Lukas Pauscher, Research Associate, Fraunhofer IEE
PO099	The influence of different wind speed measurements using a meteorological mast or LiDAR system on the power curve evaluation Jannes Vervoort, Research Associate, Fraunhofer IWES
PO100	Cost justification of floating lidars for wind resource and power performance John Slater, Senior Consultant, Fichtner
PO101	Reducing Uncertainty by Reconstructing Data Across Met Towers Tom Lambert, Windographer Product Manager, UL International
PO102	How long is long enough?The sensitivity of wind parameters to the duration of on-site measurement. Andrew Good, Senior Wind Analyst, BrightWind Analysis
PO103	Seasonal Effects in Long-Term Correction of Short-Term Wind Measurements Using Different Reanalysis Datasets Alexander Basse, Research Associate, University of Kassel
PO104	Shorter wind data for AEP calculation & risk analyses – Seasonality Impact Georgios Valsamakis, Project Lead, Enercon
PO108	End to end validation to accurately estimate the overall impact of turbine wakes Jonny Crease, Analyst – Pre-construction Wind, K2 Management
PO110	Assessing the effect of cluster wakes in different atmospheric stabilities Jörge Schneemann, ForWind – Carl von Ossietzky University Oldenberug
PO111	Wake modelling from mesoscale time series Bibiana García-Hevia, Wind Assessment Expert – Senior Researcher, CENER
PO112	Wake model comparison considering Nysted and Horns Rev offshore wind farms Cédric Dall’Ozzo, WRA Engineer, EDF Renouvelables
PO114	Cost-effective mesoscale simulations by downscaling ERA5 data David Schillebeeckx, Wind Analyst, 3E
PO115	New wind atlas generation for Europe and Germany based on ERA5 Martin Schneider, Meteorologist, anemos GmbH
PO116	Next-generation wind atlases: challenges and lessons learned from the New European Wind Atlas Bjarke Tobias Olsen, Postdoc, DTU Wind Energy