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Research and I nnovation at DTU W ind Energy Presentation at the Japanese-Danish Joint Workshop Future Green technology 10-12 December 2012, Hakata Japan Peter Hauge Madsen Head of Department, DTU Wind Energy, Technical University of Denmark

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Research and I nnovation at DTU W ind Energy

Presentation at the Japanese-Danish Joint Workshop Future Green technology 10-12 December 2012, Hakata Japan Peter Hauge Madsen Head of Department, DTU Wind Energy, Technical University of Denmark

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DTU W ind Energy, Technical University of Denm ark

Outline

  • DTU Wind Energy
  • Context
  • Research & research

infrastructure

  • Innovation and industry

cooperation

  • International cooperation

2 20 December 2012

Poul la Cour at Askov 1891-1903 The new 6 MW offshore wind turbine by Siemens, from http: / / www.siemens.com/ press/ en/ presspicture

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DTU W ind Energy, Technical University of Denm ark

W ind technology expertise

Wind Energy Division Materials Research Division Composites and Materials Mechanics Materials Science and Characterisation Fluid Mechanics Test and Measurements Wind Turbines Structures Aeroelastic Design Meteorology Wind Energy Systems Fluid Dynamics Composite Mechanics

> 2 4 0 staff m em bers Including 150 academic staff members and 50 PhD students

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DTU W ind Energy, Technical University of Denm ark

DTU W ind Energy - 2 0 1 2

4 20 December 2012

Quality Scientific excellence Relevance Strategic research programmes I m pact On society

Wind resources and siting Wind power integration and control Offshore wind energy Aero-elastic design Structural design and reliability Remote sensing and measurement tech. Aero and hydro dynamics Boundary layer meteorology and turbulence Light, strong materials Wind Energy Basics Wind Turbine Technology Wind Energy Systems

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DTU W ind Energy, Technical University of Denm ark

105m/ s, Test section 2.2 x 3.3m

Research and test facilities

Experim ents, Validation and Test

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DTU W ind Energy, Technical University of Denm ark

Wind Energy Education Programmes

6 20 December 2012

  • Int. M.Sc in Wind Energy:
  • Mechanics: 30 students per year
  • Electronics: 10 students per year
  • About 50 thesis work per year
  • Nordic Master’s programme in

Sustainable Energy

  • European Eramus Mundus Wind Master
  • PhD research school (DAWE):
  • about 50 PhD students at DTU
  • European Academy of Wind Energy
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DTU W ind Energy, Technical University of Denm ark 7

50 100 150 200 1994 '00 '05 '11 Kul Olie Naturgas Vindkraft Anden vedvarende energi m.m. PJ

Electricity production and used fuel

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DTU W ind Energy, Technical University of Denm ark 8

W ind Pow er in Denm ark

1000 2000 3000 4000 1990 '95 '00 '05 '11 MW 0% 5% 10% 15% 20% 25% 30% Kapacitet, havvindm øller [ MW] Kapacitet, landvindm øller [ MW] Vindkraft i pct. af indenlandsk elforsyning

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DTU W ind Energy, Technical University of Denm ark

Danish Energy Policy Goals & I ndustry

  • 100 pct. renewable energy in 2050
  • 100 pct. renewable energy in to

electricity and heat supply in 2035

  • No coal and oil from 2030
  • Wind power covers 9 pct. of gross

energy consumption in 2020.

  • Wind Power covers 49,5 pct. of

electricity consumption in 2020.

  • EU target for DK:
  • Renewable energy covers 30% in

2020, with 10 % i transport (DK expects 35% in 2020) 2 0 1 1 I ndustry statistics

  • Employment 25.550

– 45 % manufacturing – 13 % test and product development

  • Turnover in Denmark

51.8 billion DKK

  • Export 38.8 billion DKK
  • Global turnover 102.8

mia DKK

9 20.12.2012

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DTU W ind Energy, Technical University of Denm ark

W ind Pow er Meteorology tools and maps

W ind Atlas for Egypt ( 2 0 0 6 ) WAsP – the Wind Atlas Analysis and Application Program WAsP Engineering

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DTU W ind Energy, Technical University of Denm ark

Offshore W ind Conditions

  • Ocean winds
  • Lidar observations and

modelling

  • Wind resource

mapping using satellite data

  • Mesoscale modelling
  • Meteorological mast
  • bservations
  • Wind farms shadow

effect

  • Satellite observations

Lidar wind data and model from Horn’s Reef offshore Satellite winds showing the wake at Horn Reef wind farm. Mean wind speed map using satellite Envisat ASAR.

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DTU W ind Energy, Technical University of Denm ark

W ind Atlas update

Wind atlas for South Baltic 5 km WRF simulations Novel features:

  • Verification against high (100 m) offshore measurements
  • Comparison over large spatial extent against QuikScat winds
  • Climatologies can be calculated for arbitrary periods by

applying a wind classification weighting system Fino 3 at 100m Obs Model 10 m QuikSCAT comparsion

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DTU W ind Energy, Technical University of Denm ark

W ind conditions in com plex terrain

13 20 December 2012

Bolund experiment Mast Positions CFD were used to find the 10 positions

  • Well-defined inflow conditions
  • Roughness change
  • Steep escarpment / “complex”
  • Intercomparison study of

numerical micro scale flow models

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DTU W ind Energy, Technical University of Denm ark

Num erical results

14 20 December 2012

Speed-up along line A

2 m 5 m

Speed-up at M1 & M2 Mean Error: 2 6 % Linearized: 3 5 % LES: 2 6 % RANS 1 eqn.: 2 5 % RANS 2 eqn.: 2 0 %

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DTU W ind Energy, Technical University of Denm ark

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DTU W ind Energy, Technical University of Denm ark

LI DAR Scanning of Bolund

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DTU W ind Energy, Technical University of Denm ark

W ake effects – a com plex flow essential for perform ance and loads

CFD – Large eddy simulation

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DTU W ind Energy, Technical University of Denm ark

Fuga – a new w ake m odel

  • Linearised CFD
  • 106 times faster than

conventional CFD

  • Supported by Carbon Trust
  • It Works!

Farm Efficiency W ind Direction

Lillgrund

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DTU W ind Energy, Technical University of Denm ark

Validation: Horns Rev data. 8 m / s

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WT01 WT02 WT03 WT04 WT05 WT06 WT07 WT08 WT11 WT12 WT13 WT14 WT15 WT16 WT17 WT18 WT21 WT22 WT23 WT24 WT25 WT26 WT27 WT28 WT31 WT32 WT33 WT34 WT35 WT36 WT37 WT38 WT41 WT42 WT43 WT44 WT45 WT46 WT47 WT48 WT51 WT52 WT53 WT54 WT55 WT56 WT57 WT58 WT61 WT62 WT63 WT64 WT65 WT66 WT67 WT68 WT71 WT72 WT73 WT74 WT75 WT76 WT77 WT78 WT81 WT82 WT83 WT84 WT85 WT86 WT87 WT88 WT91 WT92 WT93 WT94 WT95 WT96 WT97 WT98

222 deg. 270 deg.

Simple closure: νt= κu* z No adjustable parameters!

GL Hassan - offshore workshop

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DTU W ind Energy, Technical University of Denm ark

  • Integrate existing atmospheric

and wake models from single wind farm to cluster scale.

  • Predict energy yield precisely

through simulation.

  • Interconnection optimization

for grid and offshore wind power plant system service.

  • Validation of the newly

integrated existing models based on wind farm

  • bservations.

EER EERA-DT DTOC I ntegrated design tool

Meteorological data / Cluster layout / Turbine data Grid data

Wake models

Optimised Cluster Design System services Energy yield

Yield models Grid models

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DTU W ind Energy, Technical University of Denm ark

The W alney Offshore W ind ( W OW ) Project

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  • Comprehensive loads validation on a state of the art 3.6MW wind turbine
  • Collaboration with Siemens Wind Energy and DONG energy

Key Measurements

  • Nacelle mounted LIDAR for wind

measurements

  • Wave sonar and Buoy at turbine
  • Accelerometers, strain gauges on
  • Blade root, drive train, tower

and foundation

  • Scientific Objectives
  • Validation of the dependencies
  • f design loads
  • Prediction of turbine net damping
  • Advanced wind/ wave correlation

studies

  • Wake effects on loads

Instrumented Turbine

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DTU W ind Energy, Technical University of Denm ark

HAW C2 – Risø DTU’s code for w ind turbine load and response

  • A tool for sim ulation of w ind turbine load &

response in tim e dom ain.

  • Normal onshore turbines; 3B, 2B, pitch control, (active)

stall

  • Offshore turbines (monopiles, tripods, jackets)
  • Floating turbines (HYWIND, Sway, Poseidon).
  • Based on a multibody formulation, which gives great

flexibility

  • I t is a know ledge platform !
  • New research/ models are continuously implemented

and updated.

  • Core is closed source. E.g. Structure, aerodynamics,

hydrodynamics, solver…

  • Submodels are open-source. E.g. water kinematics,

standard controllers, generator models.

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DTU W ind Energy, Technical University of Denm ark

Tower base flange, Mx 7.29 7.3 7.31 7.32 x 10

5

6.176 6.177 6.178 6.179 6.18 6.181 6.182 x 10

6

1.9 1.95 2 2.05 2.1 2.15 2.2 x 10

4

Topfarm w ind farm optim ization approach

  • loads and pow er
  • Optimum wind turbines position for the

lowest cost of energy

  • Wake modeling using DWM (Dynamic

Wake Meandering)

  • Quick lookup for power and fatigue loads

in a database based on HAWC2 aeroelastic simulations

  • Cost function including: Annual energy

production and costs of: Turbines, Grid, Foundation and O&M

0.005 0.01 0.015 0.02 0.025 30 210 60 240 90 270 120 300 150 330 180

Electrical power 7.29 7.3 7.31 7.32 x 10

5

6.176 6.177 6.178 6.179 6.18 6.181 6.182 x 10

6

1.655 1.66 1.665 1.67 1.675 1.68 x 10

7

Tower base lifetime fatigue loads in wind farm Annual energy yield for each turbine Wind rose

Example: A 20 WT wind farm

Turbines in wake have higher loads produce less energy!!

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DTU W ind Energy, Technical University of Denm ark

New concepts offshore

21-aug-2008 24

Combined wind and wave energy converters Floating turbines

Wind turbine Sub- structure Grid O&M Wind turbine Sub- structure Grid O&M

Life cycle costs

  • ffshore
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DTU W ind Energy, Technical University of Denm ark

Poseidon: Modeling Challenges

Risø Hawc2 Overview

  • Three rotors in one simulation

– Structural modeling already possible in the multi-body formulation – Aerodynamic model updated to handle this

  • Wake from upwind rotors

– Already possible with the dynamic wake meandering model in HAWC2

  • Large water surface area
  • Full coupled HAWC2-WAMSIM simulations
  • HAWC2 validated aeroelastic code
  • WAMSIM validated radiation/ diffraction

code for dynamic of floating structures from DHI

  • WAMSIM recode to HAWC2 dll-interface

format

  • Ordinary HAWC2 turbine model
  • Ordinary WAMSIM model
  • Full system solved by HAWC2
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DTU W ind Energy, Technical University of Denm ark

DTU offers

  • Research cooperation
  • Software with training
  • Standardization
  • Licenses / patents
  • Technology development services

– Applied R&D – Consulting: Analysis and studies – Testing & measurements

  • Education and training

– PhD programmes – Training courses

  • Dialogue & access to Danish wind

cluster and international network

I ndustry partners

  • Wind Turbine manufacturers

– Vestas – Siemens – Gamesa – Repower – GE – Envision – …

  • Energy companies

– Dong Energy – Vattenfall – EON – …

  • Component suppliers

– LM – …

26 20 December 2012

Collaboration w ith industry

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DTU W ind Energy, Technical University of Denm ark

Risø Test Stations – Prototype Testing

Risø 1979 Høvsøre 2007 Østerild 2011 5 test beds < 165 m < 8 MW Spacing 300 m 7 test beds < 250 m < 16 MW Spacing 600 m

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DTU W ind Energy, Technical University of Denm ark

Østerild Test Center

Inaugurated 6 Oct 2012 www.windturbinetest.dk

November 2012

Test bed 1. Total height 210 meter Nominal max power 16 MW Diameter less than 180 meter Test bed 4 Total height 250 meter Nominal max power 16 MW Diameter less than 230 meter Specifications for both test sites: Meteorology mast up to 250 meter Distance WT to met mast 500 meter Distance between WT’s 600 meter Average wind speed > 8 m/s

Siemens 6 MW – 154 m

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DTU W ind Energy, Technical University of Denm ark

R&D experiments and testing at DTU Commercial testing at Blade Test centre A/ S, a private limited company with the following shareholders: Det Norske Veritas AS Technical University of Denm ark FORCE Technology

W ind turbine blade testing

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DTU W ind Energy, Technical University of Denm ark

A large national w ind tunnel at Risø Park

Water tower The ducting Workshops Control room Campus Risø 105m/ s, Test section 2.2 x 3.3m

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DTU W ind Energy, Technical University of Denm ark

I nternational collaboration

I nternational:

  • IEA Wind R&D
  • EAWE – European

Academy for Wind Energy

  • EWEA
  • European Wind Energy

Technology Platform (EWI)

  • EERA – Joint programme
  • n wind energy
  • Clean Energy Ministry

Initiative (Global wind- and

solar atlas)

  • Bilateral cooperation

EERA Partners 2012 – 2014

www.eera-set.eu

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DTU W ind Energy, Technical University of Denm ark

Am bition

The EERA Joint Programme on Wind Energy aims at accelerating the realization of the SET-plan goals and to provide added value through:

  • Strategic leadership of the underpinning

research

  • Joint prioritisation of research tasks and

infrastructure

  • Alignment of European and national research

efforts

  • Coordination with industry, and
  • Sharing of knowledge and research

infrastructure.

.

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DTU W ind Energy, Technical University of Denm ark

Structure of the Joint Program m e

The joint programme comprises the following 5 sub-programmes:

  • W ind Conditions. Coordinated by

Risø DTU in Denmark.

  • Aerodynam ics. Coordinated by

ECN in the Netherlands.

  • Offshore W ind Energy.

Coordinated by SINTEF in Norway.

  • Grid I ntegration. Coordinated by

FhG IWES in Germany.

  • Research Facilities. Coordinated

by CENER in Spain.

  • Structures and Materials.

Coordinated by CRES, Greece

Structures and Materials Wind Conditions Aerodynamics Wind Integration Research Infrastructure Offshore Wind farms Application areas Enabling research areas

27 Research intitutes/ universities from 13 European nations

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DTU W ind Energy, Technical University of Denm ark

I ntegrated Research Program m e on W ind Energy – Proposal to EU FP7

SP1 Wind Conditions SP3 Structures & materials SP2 Aerodynamics SP4 Wind integration SP5 Offshore wind SP6 research infrastructure Mobility of researcher Infrastructure sharing Dissemination & outreach Managament & operation Strategy, DoW, reporting Workshops Component reliability Offshore design Wind integration Windscanner.eu DTOC INNWIND

Coordination & support actions Collaborative projects Ongoing CPs Up to €10M per technology area Duration of 4 years

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DTU W ind Energy, Technical University of Denm ark

Thank you for your attention