the offshore wind infrastructure project (ewea)
DESCRIPTION
TRANSCRIPT
The Offshore Wind Infrastructure (OWI) Project
Hoebeke Patrick ; 3E ; Belgium
Pieter Jan Jordaens ; Sirris ; Belgium
Christof Devriendt ; VUB ; Belgium
www.owi-lab.be
1. Create testing and monitoring infrastructure for
offshore wind energy
Wind turbine component testing
Condition, health and performance monitoring
Wind measurements
2. Generate datasets
3. Develop advanced data interpretation and
modelling techniques
4. Implement O&M strategies for a better use of
infrastructure and resource for offshore wind farms
Abstract
Objectives
EWEA 2011, Brussels, Belgium: Europe’s Premier Wind Energy Event
Presentation of the “Offshore Wind Infrastructure”
research and development project (OWI-Lab),
co-funded by the Flanders Region of Belgium
The project is a framework for investment programs in
test and monitoring infrastructures for:
Offshore wind resource monitoring
Wind turbine systems and component testing
Wandelaar (offshore platform about 10 km from coast):
2. Development of a mobile platform for offshore
wind measurements based on a buoy and a
Lidar instrument (floating Lidar, Flidar)
This new infrastructure will be a versatile tool allowing:
Assessments of the wind resource at virtually any
location of offshore wind farm
Analysis of wake added turbulence inside wind
parks
The foreseen design (hardware and software)
compensates for wave movements.
NWP Model Adaptation to Offshore Conditions
New knowledge gained from the recorded wind
conditions will serve as input for the adaptation of a
specific weather prediction model (NWP) to offshore
conditions. In particular for:
Set up of a local weather prediction model (short
term and long term predictions of wind regime)
Statistical corrections
Hind-casting
Project Partners
3. Participation in the EU NORSEWInD project
The NORSEWInD project is one of the biggest
dedicated instrumentation networks to acquire wind
speed data offshore. Measurements performed in the
frame of this project will be included in the
NORSEWInD database.
O&M Optimization to Offshore Conditions
A new CFD model dedicated to offshore wind
conditions will be developed, including the modeling of
wake inside the wind parks.
Measurements using the stationary and floating lidar
structures will be used to calibrate and validate the
models.
4. Acquiring and testing state-of-the-art wind,
condition, and structural health monitoring
systems
Collecting:
Process and performance data
Structural health data of offshore structures
(vibrations, eigen frequencies, damping
values)
Dedicated drivetrain data
Corrosion rate data
Knowledge build-up of data-processing methods,
standards and software
Development of „health monitoring tools‟ based on
collected datasets and system insights.
Risk assessments and asset monitoring
CFD Model Adaptation to Offshore Conditions
Establishing optimal Operation and Maintenance
strategies to maximize profit by using a decision
support software based on:
The integration of wind data, process data,
performance data and monitoring data
Component lifetime
Offshore maintenance concepts with improved
planning and logistics
5. Start up of large climate test chamber
OWI-Lab test facility for wind turbine components
Extreme temperature testing from -60°C to +60°C
Design verification testing (DVT), component
validation, R&D tests, HALT
Max dimensions test specimen: 10m x 7m x 8m
(L x W x H), max weight 150 tons
Focus on cold start testing (low temperature tests)
Infrastructure for Offshore Wind Monitoring
1. Lidar wind measurement campaigns on the
Belgian continental plate from several fixed
locations.
Transformer platform of an operational wind farm:
Extrapolation over the long term using existing on
site wind measurement
Allows correlation of wind behavior with
environmental conditions (wave height, direction,
water and air temperature…)
Allows data
extrapolation over the
long term using existing
on-site wind
measurements
Allows correlation of
wind behavior with
environmental
conditions (wave height,
direction, water and air
temperature…)
The profitability of offshore wind farms depends
heavily on the ability to predict and deliver maximum
power output at competitive costs.
The testing and monitoring infrastructure within
this project combined with innovative data
modelling will contribute to improved O&M
strategies.
Provides a reference point for nearby offshore
wind farms