Day one, 8 September - WindEurope Technology Workshop 2021
Resource Assessment & Analysis of Operating Wind Farms 2021
8-10 September • Online

Day one, 8 September

Opening speeches



The electricity system will double in size compared to today and wind will be half of that by 2050. So resource and operational assessment are more important than ever. Where can we still improve operational and resource assessment to ensure the cost-effective management of a climate neutral energy system? Digitalisation is a big driver to improve the performance of wind assets and optimise system integration. How do artificial intelligence and machine learning contribute to improving resource and operational assessment? All our models are historical. But Climate Change is testing our modelling. While we help address Climate Change we also need to be mindful of its impacts on our resources and operations. How can we deal with this? Join us for a conversation with Salvatore Bernabei, CEO of ENEL green power to explore these questions and get ready for 3 days of in-depth presentations and discussions.

Giles Dickson

CEO, WindEurope

Welcoming address

Salvatore Bernabei

CEO, Enel Green Power

Opening remarks

Artificial Intelligence: from design to operation


Artificial Intelligence (AI) provides powerful solutions that support all steps of the value chain of wind energy. In this session participants will learn about contributions of machine learning in the ressource assessment phase for obtaining more accurate annual energy production estimates, but also in the operational phase, for detecting underperformance of wind turbines.

The session will address the scalability of AI tools for predictive maintenance of wind turbines, where massive data are considered. Finally, the participants will hear about AI-based state-of-the-art forecasting methods for wind generation and extreme wind situations and also for optimising the use of forecasts in applications like trading to electricity markets.


Georges Kariniotakis

Professor, Head of Renewables & SmartGrids Group, MINES ParisTech


Jordan Perr-Sauer

Staff Researcher – Data Science, National Renewable Energy Laboratory (NREL)

Lowering long-term energy estimate uncertainty through better wind plant power curves

Henrique Diogenes

Performance & Reliability Coordinator, Casa dos Ventos

A machine learning approach for underperformance detection in wind turbines

Gianmarco Pizza

CEO, Nispera

A scalable solution for predictive maintenance of operating wind farms based on deep learning

Miguel Ángel Prosper Fernández

Meteorologist, Siemens Gamesa Renewable Energy

Detection system for extreme wind events based on WRF high-resolution simulations and Deep Learning image recognition

Simon Camal

Senior Researcher, Project Manager, MINES ParisTech – Centre PERSEE

A holistic approach to improve the model & value chain of renewable energy forecasting – the smart4RES project

Sponsored session by EMD – windPRO Product News


Tools – Presentation of the new windPRO 3.5 features: Hybrid, Solar, Life-time extension, Eddy Viscosity etc.

Data – Introduction to new Global Atlas of Siting Parameters (GASP)

Automation – Using the new EMD-API to automate data retrieval in e.g. Python and R


Per Møller Nielsen

Product Owner, EMD International A/S

Lasse Svenningsen

R&D Manager, EMD International A/S

Morten L. Thøgersen

Senior Technical Expert, EMD International A/S

Mobile fieldwork: How to reduce costs, errors and carbon footprint with Real-time Data

Sponsored session by Resco


Join to learn:

  • How an app facilitated the life of a manager at a larger wind energy company
  • 5 key features you should demand from a mobile field solution
  • Top innovations that will make the life of your field workers easier

    Peter Semancik

    International Business Development Manager

    Improving simulations to reduce uncertainty


    The maturity of the wind industry has led it to become a much more competitive market than in the past, requiring greater precision in studies by reducing its uncertainties. This session will show innovative techniques aimed at reducing uncertainty in different aspects relevant to wind farms, ranging from the optimal use of measurement systems, to the development and calibration of new models of wakes, plant losses or the performance of wind turbines.


    Jose Vidal

    Technical Director, Energy Advisory Services, UL


    Lee Cameron

    Data Science Manager, RES

    Designing scanning LiDAR campaigns to Reduce Yield Assessment Uncertainty

    Morten Lybech Thøgersen

    Senior Wind Energy Specialist, EMD International A/S

    Shorter measuring campaigns using geospatial predictors and machine learning

    Neil Atkinson

    Principal Specialist, K2 Management

    A multiple wind farm validation of turbine performance predictions from a 3D turbine performance matrix

    Camille Dubreuil-Boisclair

    Principal Researcher, Equinor ASA

    Ensemble methods for wake parameter calibration

    Marion Le Doeuff

    Analytics Manager, Natural Power

    Method to improve accuracy of production modelling and loss interaction in the time domain

    Resource Assessment: Measurements


    In this session we will learn about the latest within lidars. Not only the usual individual lidars, but also several lidars working in synchrony. We will get ideas of how to use and correct lidar measurements in complex terrain, and finally we will see how many elements can be integrated into an optimal measuring campaign.


    Lars Landberg

    Director, Group Leader, Renewables, Research and Development, DNV


    Scott Wylie

    Head of Customer Service, Data & Support, ZX Lidars

    Bankable standalone LiDAR measurements in complex terrain

    Annette Westerhellweg

    Senior Project Manager, UL

    RSD correction for complex terrain effects with the linear wind flow model WindMap

    Florian Jäger

    Research Associate, Fraunhofer IEE

    Multi-LiDAR measurements for site and resource assessments

    Gunhild Thorsen

    Developement engineer, DTU Wind Energy

    A user-friendly WindScanner system in action

    Doron Callies

    Senior Scientist, Fraunhofer IEE

    Holistic optimization of wind measurement campaigns for resource assessment

    Operations: Data-driven maintenance


    In the last 5 years, Operation & Maintenance in the Renewable Energy sector has shown one of the most fascinating industrial changes. Operations, technology and digitalization have mixed together creating a symbiotic growth that enabled a new maintenance approach based on data. Join this session to embrace this change as a continuous improvement process to progressively increase efficiency and optimize maintenance costs.


    Jose Alba Perez

    Head of Global O&M Wind and Storage, Enel Green Power


    Alex Byrne

    Principal Engineer, DNV

    IEA Wind Task 43: Enabling risk-based maintenance through digitalisation

    Franz Langmayr

    Managing Director, Uptime Engineering

    Information merging and analytics for maintenance process optimisation

    Mihail Ivanov

    Product Manager Digitalization, ZF Wind Power

    Improved powertrain prognostics by integrating domain knowledge in alert processing

    Kuljit Singh

    Business Development Manager, OptaSense Ltd

    Monitoring of export and inter-array cables using Distributed Rayleigh Sensing