Poster presentations - WindEurope Technology Workshop 2020
Resource Assessment & Analysis of Operating Wind Farms
8-11 June 2020 • Online

Poster presentations

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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, Technical Directory – Analysis Services, 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
Lindy Williams, Reseacher – Data Science, 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 power finances for the case of 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, Pre-construction Analysis Service Lead, 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