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