Resource assessment - part 2
When: Wednesday, 3 April 2019, 14:00 - 15:30
Where: Luxua 2
The Resource Assessment programme will span across 3 sessions. Each will take the audience through a range of topics. These will include: ice losses, turbulence intensity measurements, wake modelling improvements, seasonal forecasting, machine learning applications, and the impact of real world conditions on turbine performance. Each of these topics has the potential to have a profound impact upon the energy yield and therefore it is vital they are thoroughly understood.
Invited speakers from outside the Resource Assessment community will present: the potential impacts of climate change on the wind resource; insights on measurements from the data user perspective; and how to improve annual energy production using operational data.
Part 2 will take the audience through a range of topics ranging from ice losses, wake modelling improvements, seasonal forecasting through to the impact of real world conditions on turbine performance.
View the rest of the programme: Part 1 - Part 3
- Attendees will gain understanding of how climate predictions impact wind energy forecasts;
- Attendees will be able to analyse and extrapolate the effects of icing;
- Attendees will be able to apply a new implementation of a wake model;
- Attendees will be able to understand how nacelle LIDARS can be used to improve their understanding of real conditions.
Independent Expert, -
Director - Group Leader: Renewables, Strategic Research & Innovation, DNV GL
Transforming data into value
Technical Director, RES
Investigation of the impacts of real world flow conditions on wind turbine power performance through nacelle lidar combined with advanced CFD modelling
Senior Energy Analyst, Natural Power
Sub-seasonal to seasonal climate predictions for wind energy forecasting
Earth System Services Group Leader, Barcelona Supercomputing Center (BSC)
Effective validation for time series icing modelling using operational SCADA data
Wind Meteorologist , Vortex
Improvements to the Eddy Viscosity wind turbine wake model
Modelling and Analytics Expert, E.ON