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