Sessions | WindEurope Electric City 2021


Resource assessment - Modelling & Measurements 2

Offshore wind Onshore wind Technical and Scientific Programme

When: Tuesday, 23 November 2021, 15:30 - 16:45
Where: Auditorium A15

Session description

The more accurate the assessment of the wind resource is when planning a wind farm, the more accurate the estimation of Annual Energy Production will be, and hence the stronger the business case and the lower the financing costs. Proper wind resource assessment is therefore a cornerstone of every wind project, especially as the environment for wind projects becomes increasingly merchant. The "Resource Assessment" sessions will focus on reducing uncertainty when estimating how much wind there is at a given site, through better models and validation tools. It is designed for wind energy professionals who conduct or commission wind resource assessment campaigns, researchers working on wind dynamics and modelling, data scientists and analysts, as well as anyone interested in staying up-to-date on new technology and research developments in this fast-moving and increasingly digital field.

Session chair

Marie-Anne Cowan

Lead Wind Engineer - Energy and Climate Analytics, Wood Thilsted

Lars Landberg

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


High-resolution estimation of wind resources at turbine hub height with SAR (Synthetic Aperture Radar) satellite measurement and Machine Learning

Mauricio Fragoso

Director, Energies & Infrastructures Monitoring, Group CLS

Measuring Wind Farm Blockage – Measurement Campaign design using long-range scanning lidar systems

Jens Riechert

Senior Consultant, OWC

Global Wind Atlas 1, 2 & 3 – validations and uncertainty assessment

Niels Gylling Mortensen

Senior Researcher (emeritus), DTU Wind Energy

Massive computing power to estimate Vref: Large Eddy Simulations for 30 years of extreme winds

Pep Moreno

CEO, Vortex

Simulation of diurnal cycles in flat and complex terrain using the WRF-LES model

Roberto Chávez-Arroyo

Research Scientist, UL

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