12th Irish Wind Energy Research Network Meeting

www.seai.ie
Irish Wind Energy Research Network
12th Meeting
John Mc Cann 28/6/2022

This event is being recorded
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2 www.seai.ie
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Questions submitted by clicking Q&A bubble
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A recording and slides will be distributed after the event

Overview
3 www.seai.ie
Wind Energy Trends
SEAI Wind Energy Research Updates
International Wind Energy Research Collaboration

Key Statistics and Key Targets
Peak Electricity Demand to Date: 5,357 MW
Installed Wind Capacity @ 31st March 2021: 4,320 MW
Maximum Wind Output to Date: 3,604 MW
Wind’s Contribution to Electricity in 2021: 29.4%* (32.4%**)
Renewable Contribution to Electricity in 2020: 35%* (37.8%**)
Wind TWh 2020: 9.72 TWh
2030 Targets
RES-E 80%
Wind 8.2GW Onshore Wind & 5GW Offshore Wind
* Preliminary Estimate Actual gross contribution (non-normalised)
** Estimated normalised contribution according to EC methodology
Sources: EirGrid & SEAI

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SEAI Wind Energy
Research Updates

SEAI Supports for Wind Energy R,D&D
7 www.seai.ie
SEAI RD&D Scheme
• SEAI 2022 RD&D Call for Proposals
• Call closed May 16th, applications under review
• Next call 2023
IEA Wind R,D&D Technology Collaboration Programme:
• Annual call for participants
• Funding of Task fees and travel costs for participants
• 36 Irish Researchers Participating in 17 IEA Wind Tasks
• Next call autumn 2022
SEAI Supported Offshore Renewable Energy Test Facilities & Sites
• Lir National Ocean Test Facility (NOTF) ORE Industry Access Programme (June 17th)
• SEA/AA screening statement & public consultation for AFLOWT floating offshore wind
demonstration project at the Atlantic Marine Energy Test Site (AMETS)

8
International Wind Energy
Research Collaboration

EU Horizon Europe
9 www.seai.ie
• 20 projects under Energy awarded during 2021, 1 was directly linked with wind
with Irish partners:
– EU-SCORES https://cordis.europa.eu/project/id/101036457 mixing variable
renewables sources offshore
– Irish partners Exceedence and Simplyblue.
• Hiperwind started on Dec 1 2020
https://cordis.europa.eu/project/id/101006689
– Irish Partner EPRI

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IEA Wind TCP Legacy and Active Research Tasks

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Task 11 WindScout Topical Expert Meetings
Upcoming Topical Expert Meetings:
• Implementing an Asset Management Standard in the Wind
Industry
• Grand Challenges for Wind Energy Research
• Hydrogen for 100% Renewable Energy Systems
• Wind Energy Research Needs for Emerging Wind Energy Markets
• Wind Energy Technology Transfer

12
IEA Wind Annual Report
• Global Overview and Statistics
• Deployment, R,D&D
• IEA Wind Research Tasks
• Objectives, Progress, Outputs
• Country Reports
• Wind Power deployment - Production and share of
electricity
• Policy Updates – Highlights
• Environmental and socio economic highlights
• R,D&D Highlights
• Available on new IEA Wind Website
• www.iea-wind.org

Results from a National Survey on Innovative Approaches to
Achieving a Social License
(Co-Wind Project)
Dr. Bernadette Power
Cork University Business School
12th Irish Wind Energy Research Network (IWERN) Meeting
Tuesday June 28th 2022
Co-Wind Research Team: Dr. Bernadette Power (PI), Dr.
Geraldine Ryan, Dr. John Eakins, Dr. Ellen O’ Connor, Julia
Le Maitre, Cork University Business School

Social acceptance is one of the key
barriers to scaling up on-shore wind
energy installations – in Ireland
(Hyland and Bertsch, 2018) as well as
in other countries such as Denmark
(Johansen, 2021), Switzerland
(Vuichard et al., 2019) and Germany
(Lienhoop, 2018).
Social Acceptance
15

Co-wind Project – Innovative Approaches to
Achieving a Social License
Community
Engagement
Community
Benefit Funds
Co-ownership /Co-
investment

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Online National Survey (N=2023)
It conducted two choice experiments with dual response focusing on engagement, community
benefit funds and co-investment.
Representative by age, gender but oversampled regions outside Dublin
Individual Environmental Attitude Wind Farm Externalities Wind Energy Attitude
Age Climate change very important Positive Positive statements
Sex Global warming first Community Benefit Fund Clean Energy Source
Education Buy 100% electricity Annual direct Payment CO2 Reduction
Employment status SEC in the area 20 construction jobs Potential to create Jobs
Landowner/Farmer Place Opportunity to buy shares Room for both onshore and offshore
Household Community is part of my identity 3 operational jobs Negative statements
Household size Everyone knows each other Reduced CO2 emissions Wind energy should be moved offshore
Household income Strong community spirit Negative Wind energy brings discord into communities
Home ownership Financial Shadow Flicker Tourism Impact
Location Previous investment experience Visual impact Unreliable
Region Local wind energy project Noise More environmental harm than good
Rural/Urban Non local wind energy project Anti-wind farm neighbours Choice experiments attributes
County Portfolio of wind projects Potential impact on wildlife
Proximity Amount to invest Potential health impact
Distance to nearest turbine
Cohorts (proximity*rural)

Scenario 1: Imagine a typical modern
wind farm with 15 turbines of 185m
height is proposed for development
and one of the turbines would be
within 1km of your home. How likely is
it that you would accept such a wind
farm in your community?
The impact of public participation measures on willingness to accept.
National Survey –Willingness to accept
25%
38%
21%
16%
32%
39%
16% 13%
0%
10%
20%
30%
40%
50%
Very likely Somewhat likely Somewhat unlikely Very unlikely
Scenario 1 Scenario 2
Scenario 2: Imagine a typical modern wind farm with 15 turbines of 185m height is
proposed for development and one of the turbines would be within 1km of your
home. The developer has provided a community liaison officer that is readily
available to visit or phone you to discuss any concerns you might have. There is an
annual community benefit fund of €180,000. You will receive an annual payment of
€1,000 for 15 years. You have an opportunity to invest in the wind farm. The
minimum investment is €500. The government will ensure your investment so that
the initial investment is always safe. How likely is it that you would accept such a
wind farm in your community?

Community benefits|
Attitudes
-4%
-6%
-6%
-5%
-5%
-9%
-12%
-24%
-27%
-29%
-39%
-33%
-5%
-6%
-4%
-7%
-5%
-6%
-8%
-17%
-19%
-27%
-21%
-30%
35%
41%
41%
37%
30%
32%
11%
12%
10%
11%
12%
9%
25%
19%
17%
18%
16%
11%
7%
6%
5%
7%
5%
5%
-70% -50% -30% -10% 10% 30% 50% 70%
An annual payment is provided directly to you
Related reduction in carbon dioxide emissions
Construction of the wind farm provides 20 jobs locally
Community benefit fund for the local community
Opportunity buy shares in the wind farm project
Operation of wind farm supports 3 jobs in the region
My neighbours are anti-wind energy
Visual impact of wind turbines in the landscape
Potential for shadow flicker from blades
Potential impact on health of residents
Potential impact on wildlife
Potential for noise from turbines
Acceptance
Factors that affect willingness to accept

Preference for initial engagement – Proximity to existing wind farm.
67% 65%
54% 52%
39% 39% 38%
33% 35%
46% 48%
61% 61% 62%
0%
10%
20%
30%
40%
50%
60%
70%
80%
<500m 500m-1km 2-3km 4-5km 6-10km 11-50km Over 50km
Very early engagement with scant information Early engagement with some information
National Survey - Engagement
Respondents who have experience of living near a wind farm prefer early engagement even with scant information
whereas respondents who have little or no experience of living near a wind farm prefer early engagement when
some information is available.

17%
17%
18%
16%
22%
22%
26%
35%
42%
47%
46%
51%
46%
51%
40%
40%
41%
36%
36%
33%
32%
27%
34%
25%
Long-term jobs for 2 people living in the community
Non-cash permanent benefits for the community e.g.
development of local amenities such as walking trails
Contracts for local businesses during construction
A community benefit fund which would target support towards
local projects within the area of benefit (10 km radius) for 15…
clubs, societies and other non-profits in the community
green and sustainability initiatives within the area of benefit (10…
Once-off lump sum direct payments to me and other near
residents within 1km of €5,000
On-going direct payments to me and other near neighbours
within 1km of €1000 per year for 15 years
In-kind
benefits
Public
benefits
Private
benefits
Strongly increase Increase No influence
National Survey – Benefit sharing

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National Survey – Fair Distribution of the Benefit Fund
The preference for community projects was slightly higher in the group that said there
was a strong community spirit in their community.
Those living closer to an existing wind farm have a higher preference for green and
sustainable community projects.
Overall support for a model of benefit sharing whereby priority is given to near-
neighbour payments.
Community Benefit Fund
€180,000 p.a.

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Governance of the fund, engagement and developer/electricity production
cost are more important than sharing of the community benefit fund.

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Community benefits are important but
household benefits are generally preferred
All supporters value local investment

Strong Supporters versus Conditional Supporters
Strong Supporters
Local benefits
Local investment
Local ownership
Conditional Supporters
Representative meetings
Semi-state projects
Greater setback distances
26

National Survey – Investment in wind energy
If you were provided with the opportunity to invest in the following projects over a
5 year time horizon at an approximate return of between 2% and 6% per annum
which of the following projects you would consider investing in?
33%
34%
45%
53%
59%
62%
67%
66%
55%
47%
41%
38%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
A non-local wind energy project
A non-local solar energy project
A portfolio of wind energy projects
A general green fund
A local solar energy project
A local wind energy project
Yes No
Strong appetite for citizen investment in local projects.

28
10%
31%
27%
16%
7%
5%
3%
13%
29%
26%
14%
8%
6%
5%
9%
28%
25%
16%
11%
5% 5%
0%
5%
10%
15%
20%
25%
30%
35%
No money to
invest
<=€500 €501–€1,000 €1,001–€2,000 €2,001–€5,000 €5,001–€10,000 >€10,000
Proportion
of
respondents
who
would
consider
investing
in
the
project
type
Proportion of respondents who would consider investing in each type of project by
the amount of money they would be willing to invest
A local project (n=1,260) A non-local project (n=676) A portfolio of projects (n=916)
Citizens generally prefer to invest low sums of money.

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Common factors to all projects that increase
citizens’ willingness to invest
Male
Landowner
Financial investment experience
High income
Living in a city
Living within 10km of a large wind turbine
More concerned about climate change
Agree with “There is a role for both on-shore and
off-shore wind energy”
Additional factors that increase
citizens’ willingness to invest
Local projects
SEC in area, Middle income, Strong community spirit,
Disagree with “Wind energy in Ireland does more
environmental harm than good”, Disagree with “Wind
farms bring discord into communities”, Disagree with
“Wind farm developments can negatively impact tourism”
Non-local projects
Living in Dublin, Disagree with “Wind energy in Ireland
does more environmental harm than good”
Portfolios of projects
Currently investing in wind energy, SEC in area, Living in
Dublin, Middle income, Agree with “Wind energy is key to
achieving Ireland's carbon reduction commitments”
Citizens willingness to Invest
The current expansion of the SEC network
should help to promote citizen investment in
local projects.

Thank You
?
Contact Details:
Bernadette Power:
b.power@ucc.ie

by: Behzad Keyvani
Supervisor: Prof. Damian Flynn
Increasing Network Utilisation
using Active Measures within
Transmission System Planning Studies
June. 2022

Introduction
✓ Congestion in the Irish transmission system
✓ Dynamic line rating (DLR) and power flow control concepts
✓ Scenario definition and regional clustering
✓ Network planning studies for DLR, power flow control, reconductoring and
battery storage system (BESS)
✓ Conclusions

Congestion In Irish Transmission System
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✓ Load centres mainly on east coast
✓ Wind farms mainly on west coast
✓ Congestion and overload particularly on 110 kV
network and north west region
✓ Offshore wind on east cost and new
interconnectors will cause congestion.
✓ New line construction to relieve congestion
✓ Utilisation of technological-based assets, e.g.
DLR, power flow control and battery storage to
harvest existing transmission capacity

Dynamic Line Rating Systems (DLR)
✓ Conventional engineering practice for line
thermal design (static rating)
✓ Dynamic line rating: reveals actual capacity of
overhead line
✓ Measurable in real time
✓ Quick installation
✓ Identification of critical spans for sensor
installation
✓ Control and protection aspects

Power Flow Control Devices
✓ Multiple deployment options:
− SSSC, TCSC, DSSC, DSR
✓ Re-deployable technology
✓ Controllable in real time
✓ Modes of operation: Inductive or capacitive
SSSC – Static synchronous series compensation
TCSC – Thyristor controlled series compensation
DSSC – Distributed static series compensation
DSR – Distributed series reactor

Scenario Definition and Regional Clustering
Dynamic line rating
sub-regions
Wind power
sub-regions
Solar power
sub-regions
✓ 10 sub-regions for DLR, 14 sub-regions for wind power and 6 sub-regions
for solar power based on MÉRA reanalysis data (2000-2018)

Planning studies
✓ Investment for power flow control (DSSC), dynamic line rating systems (DLR),
reconductoring and battery storage systems (BESS)
✓ Benders decomposition applied with a distributed computational framework
developed with Python and Gurobi
✓ Network under study: EirGrid PSS/E model 2028
✓ Objective to minimise fuel + emission + capital costs, unit commitment
applied
✓ Emergency line security constraints applied
✓ Concurrent investment of DLR and DSSC permitted
✓ RoCoF, minimum inertia, must-run units, and POR applied

Methodology
✓ Scenario definition, candidate selection, and concurrent investment
FFS – Fast forward selection algorithm

Network Aggregation
✓ Network aggregation, performed with Python script in PowerFactory

Base Case Study
✓ Maximum potential cost reduction:
⁻ Network focussed schemes (without BESS): 9.45%
⁻ BESS-included schemes: 9.93%
✓ Relief potential (RP):
RPsh =
Cost savings associated with sheme 𝑠ℎ
Maximum existing potential
UC – Unit commitment
UC+SC-LL– Unit commitment+ Network limits and security

✓ Average annual system marginal price
for UC case (without network
constraints) is 68.6 €/MWh
✓ In far west indicates the lowest value
(39.6 €/MWh)
✓ Around major load centres LMP values
exceed 80 €/MWh
Base Case Study - Local Marginal Price (LMP)

Base Case Study - Candidate Selection
✓ DLR candidates: critical lines shown
✓ DSSC candidates: critical lines and
their neighbouring lines
✓ BESS candidates: buses with highest
day to night variations in LMP values

Single Asset Cost Comparison
✓ Single asset treatment

Single Asset Cost Comparison
✓ Single asset treatment
─ DSSC scheme is most
economic option with
24.1% relief potential
Cost reduction %
Relief potential %
1.07%
11.3%
1.83%
19.4%
2.27%
24.1%
0.56%
5.66%

Dual Asset Cost Comparison
✓ Dual asset treatment

Dual Asset Cost Comparison
✓ Dual asset treatment
─ DLR+DSSC scheme most
economic, with relief
potential of 54.6%
Cost reduction %
Relief potential %
5.16%
54.6%
3.49%
36.6%
2.66%
26.5%
2.86%
28.5%
1.07%
11.3%

Cost Comparison For Optimal Scheme
✓ Multi-asset treatment

Cost Comparison For Optimal Scheme
✓ Multi-asset treatment
─ Operational cost falls by
2.77%, more capital
investment, 700+%
relative to DLR+DSCC
scheme
Cost reduction %
Relief potential %
5.16%
54.6%
5.81%
58.1%

Optimal Scheme
✓ Coordinated scheme with
⁻ 53 DSSC compensated lines
⁻ 33 DLR equipped lines
⁻ 93 buses host 4-hour BESS with total
capacity of 548 MW
⁻ 20 lines invest in both DLR and DSSC

Dispatch-down Values
✓ 5.63% Dispatch-down
increase due to network
constraints for Base case
(UC) reaching 10.4%
✓ BESS+DLR+DSSC relieves
60.3% of the dispatch-
down related to network
constraints, reducing it to
6.8%

Conclusions
✓ Scenario definition based on 10 DLR sub-regions, 14 wind power
sub-regions, and 6 solar power sub-regions
✓ Co-planning DLR and DSSC best reduces (capital + operational)
costs and relieves network constraints
✓ Additional benefits for BESS-based schemes to support generation-
demand balancing and provide various reserve services
✓ Up to 58.1% saving for costs associated with network constraints
with BESS+DLR+DSSC scheme, and 60.3% reduction in the
renewable dispatch-down related to network constraints

Behzad Keyvani behzad.keyvanieydi@ucdconnect.ie
Prof. Damian Flynn damian.flynn@ucd.ie
Increasing Network Utilisation
using Active Measures within
Transmission System Planning Studies
June 2022

Scenario Definition and Regional Clustering
✓ Methodology for wind power clustering

Implementation
✓ Benders decomposition and
parallelisation
✓ Dynamic contingency screening
✓ Distributed computational framework
developed with Python and Gurobi

Assumptions
✓ SNSP = 0.95
✓ Must-run units 2 in ROI (Dublin area) and 2 in NI
✓ RoCoF limit = 1 Hz/s
✓ Minimum Inertia = 15000 MWs
✓ min POR = 155 MW, POR=75% largest infeed
✓ Unit parameters obtained from SEM public data
✓ Carbon price = 60 euro/tonne
✓ Gas price and interconnector modelled with GJ/MWh time series
✓ 2015 assumed as climate year, 40 representative days considered

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Open Offshore Wind Analysis
Derek O’Callaghan and Sheila McBreen
University College Dublin
Irish Wind Energy Research Network Webinar - June 28, 2022

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Earth Observation Offshore (EOOffshore)
SEAI funded project (RD&D 00469)
Objectives
1. Investigate use of open EO etc data to
increase wind measurement coverage of
Irish Continental Shelf (ICS), for
renewable energy assessment of offshore
Areas Of Interest (AOIs)
2. Scalable data processing for offshore
wind analysis e.g. wind speed
extrapolation, power density estimation
3. Prototype wind atlas, demonstrating
interactive offshore AOI wind and power
density maps
Open Offshore Wind Analysis 12th Irish Wind Energy Research Network Webinar - June 28, 2022

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Traditional (Wind) Analysis
(Static) web interface, e.g. map
layers
Manual retrieval of individual
products for AOI
One/low number of providers
Local computation
Low number of products used
Range of data formats
Separate approach for each
data provider
Process doesn’t scale
Data/source code often not
provided => restricted
reproducibility, difficult to
extend

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Proposed Approach
Analysis-Ready Cloud-Optimized (ARCO) Data Catalogs
I AR: data set per provider, no individual product retrieval;
reduced/no preprocessing
I CO: object storage compatible, e.g. Amazon S3, Google
Cloud Storage etc.
Data-Proximate Computing
I Open frameworks for scalable (distributed) data processing
Same approach for all data, regardless of provider

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Open Software Ecosystem

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Areas Of Interest (AOIs)
1. Marine Institute Irish Weather Buoy Network (IWB)
operational buoys (M2-6)
2. Synthetic wind farm coordinates

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ICS Wind Data Catalog
Available Data Issues
Multiple providers with varying access; API (with registration),
HTTPS, SSH etc.
Retrieval issues, ”older” products may be unavailable
Product formats (NetCDF, GRIB), files etc.
Variables, e.g. wind u, v components vs wind speed, direction
Spatial (horizontal/vertical) and temporal resolutions
Level-3 data (uniform spatial/temporal resolution) vs Level-2
(uniform processing required)
Retrieval/preprocessing time-consuming - Repeated by all
users

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Zarr Stores/CSV 2001-2021
Products (NetCDF/GRIB) retrieved (API/Utilities, HTTPS, SSH)
Preprocessing e.g.
I Wind speed/direction from u, v variables (MetPy)
I Level-3 regridding (xESMF)
I Variable chunks with Dask arrays
Zarr stores created with xarray/Dask/rechunker
Data Provider Time # Products Products Size (GB) Zarr (GB)
ASCAT Near Real Time L3 Sea Winds Copernicus Marine Service 2016-01 to 2021-09 324 16 11
ASCAT Reprocessed L3 Sea Winds Copernicus Marine Service 2007-01 to 2021-07 412 21 14
CCMP Wind V2.1 NRT Remote Sensing Systems 2015-01 to 2021-09 2,436 109 0.5
ERA5 Hourly Single Level Copernicus Climate Change Service 2001-01 to 2021-09 249 9.9 16
Met Éireann Re-Analysis (MÉRA) Met Éireann 2001-01 to 2016-12 1,920 226 196
New European Wind Atlas (NEWA) NEWA 2009-01 to 2018-12 14,611 27 20
Sentinel-1 L2 OCN
Copernicus Open Access Hub
Alaska Satellite Facility 2015-06 to 2021-09 17,698 241 1.2
Irish Weather Buoy Network Marine Institute 2001-05 to 2021-09 1 0.08 n/a

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Zarr format
Data variables stored as
multi-dimensional arrays:
I Grid (latitude/longitude)
I Time
I Height (above the surface)
Zarr format: compressed chunk
arrays, along any dimension(s)
Chunk arrays subsequently
processed in parallel
Zarr stores may be local/remote
Sanket Verma 2022

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Scalable Wind Analysis
Jupyter + xarray + Dask + Zarr
Abernathey et al., 2021: Cloud-Native Repositories for Big Scientific Data

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Lazy execution with xarray + Dask for AOI
assessment
I Original variables e.g. mean wind speed
over time
I New/extended variables e.g. wind speed
extrapolation to turbine hub height;
power density estimation
I Variables computed as required ->
reduces redundant storage
requirements
Same approach used for all data sets (size
agnostic)
Julius Busecke 2022

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Example Variable (MÉRA Wind Speed)

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Example Outputs
MÉRA 125m ICS power density estimate
NEWA 150m wind speed comparison
MÉRA 125m ICS power density estimate

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Interactive Wind Atlas

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Summary
Project Jupyter notebook outputs available at EOOffshore
website: https://eooffshore.github.io
I Data catalog and Zarr store creation
I Processing and AOI data set comparisons
I Wind atlas prototype
Plan to release data sets
Acknowledgements
I SEAI funding
I AWS credits
I Data providers
I Pangeo/Python library
teams
@dgocallaghan @EoOffshore

Open Offshore Wind Analysis
Derek O’Callaghan and Sheila McBreen
University College Dublin
Irish Wind Energy Research Network Webinar - June 28, 2022

Developing damping parameters for Irish offshore wind farms
• Dr. David Igoe – Assistant Professor in Trinity
College Dublin _ Project PI
• This project is funded through SEAI RDD and
started in Jan 2020
• Due to be completed in 2023
• Led by Trinity College Dublin and includes
industry partners Gavin and Doherty
Geosolutions (GDG) and Dublin Offshore
Consultants (DOC)
• The project is focused on fixed bottom
offshore wind turbines.
58 www.seai.ie

59 www.seai.ie
Increasing Water Depth
Monopiles
Jacket Structures
Gravity Base
Cumulative substructures for
offshore wind to end of 2019
Offshore Wind Substructures

What is damping?
• Damping is an influence on an oscillatory
system that has the effect of reducing or
preventing its oscillation.
60 www.seai.ie

What is damping?
61 www.seai.ie
https://www.youtube.com/watch?v=4SpSwTvbZI4

What is damping?
62 www.seai.ie

What is damping?
63 www.seai.ie

What is damping?
64 www.seai.ie

What is damping?
65 www.seai.ie

What is damping?
66 www.seai.ie

What is damping?
67 www.seai.ie

What is damping?
68 www.seai.ie

What is damping?
• Damping is an influence on an oscillatory
system that has the effect of reducing or
preventing its oscillation.
• Damping is produced by processes that
dissipate the energy stored in the oscillation
69 www.seai.ie

Why is damping important for offshore wind?
• Offshore Wind turbines are lightly damped,
dynamically sensitive structures
• For a Load Assessment, realistic values of
damping are required as an input for dynamic
wind turbine models.
70 www.seai.ie

Why is damping important for offshore wind?
• Offshore Wind turbines are lightly damped,
dynamically sensitive structures
• For a Load Assessment, realistic values of
damping are required as an input for dynamic wind
turbine models.
• Larger the values of damping lead to reduced peak
loads on the structure and fatigue loads on the
structure.
• Better estimation of foundation damping and
improved fatigue design could potentially extend
the wind farm lifetime by 40% (Kallehave 2015)
• Estimated savings in the region of 5 - 10% of
foundation steel tonnage may be possible.
71 www.seai.ie
CarswellW,JohanssonJ,LøvholtF,ArwadeS,MadshusC,DeGrootD,etal.Foundationdam
pingandthedynamicsofoffshorewindturbinemonopiles.Renew Energy 2015;80:724–
36.

Sources of damping for an offshore
wind turbine
• Aerodynamic damping
• Hydrodynamic damping
• Steel damping
• Supplemental damping provided by
mechanical dissipating devices
• Foundation (or soil) damping
72 www.seai.ie

Typical ranges of damping ratio for an offshore
wind turbine
• Aerodynamic damping
– during operating conditions 4%–8% in the for-aft
(FA)
– Much smaller during idling conditions <0.2%
• Hydrodynamic damping
– between 0.07% and 0.23% in the literature
• Steel damping
– steel damping values between 0.2 and 0.3% are
often used
• Foundation (or soil) damping
– Values in range of 0.25 - 1.5% reported in
literature
– Foundation damping is the largest contributor
during idling conditions and has the largest
degree of uncertainty
73 www.seai.ie

Foundation damping for offshore wind turbines
• Primarily comes from non-linear hysteretic
behaviour of the soil
74 www.seai.ie
From Page 2018 – PhD Thesis

Aims of the project
• This project aims to develop new methods for estimating foundation damping, with particular
relevance for the Irish offshore wind industry.
• This is achieved through combination of experimental soil element testing and advanced
numerical modelling
• Ultimately recommendations will be provided in different formats depending on the stage of
engineering design
– For preliminary design foundation damping values will be provided in terms of single
representative damping ratio values for each soil type
– For Front End Engineering Design (FEED) design charts will be provided of soil damping in
terms of damping ratio vs shear strain for each soil type
– For Detailed Design a detailed methodology for developing site specific damping values from
cyclic soil element test data will allow engineers to develop their own site-specific damping
parameters
75 www.seai.ie

Project work packages
The project is divided into 5 main work packages as follows:
76 www.seai.ie
WP1 - Preliminary
desktop study,
data collation and
numerical
analysis
WP2 -
Experimental soil
damping study
WP3 – 3DFE
study of soil
damping for
monopiles
WP4 - Fully
coupled dynamic
aeroelastic model
of OWT
WP5 Design
recommendations
damping values &
project impact
study

WP1 Preliminary desktop study, data
collation and numerical analysis (GDG)
• Perform desktop study defining scope
and range of conditions relevant for Irish
Offshore Wind Sector
• Collate data relevant for Irish OWTs
including water depth, soil types and
meteorological data
• Perform initial parametric 3D FE study of
monopiles to define appropriate lab test
stress paths
77 www.seai.ie

WP2 Experimental soil damping study (TCD)
• Perform suite of laboratory soil element tests
using state-of-the-art advanced dynamic
cyclic triaxial testing
• The tests cover a range of soils which is
anticipated to including both cohesive (clay /
glacial till) and non-cohesive (sand) soil
types.
• The results from this testing provide database
of soil damping vs shear strain curves which
feed into the numerical models (WP3)
78 www.seai.ie

WP3 Numerical study of soil damping for
monopiles (GDG/TCD)
• Calibrate constitutive soil models against
experimental data from WP2
• Develop 3D FE monopile models for range of
conditions and validate against field test data
• Post process 3D FE results and extract damping
foundation damping values
• Used to calibrate Kinematic hardening Macro-
element models
79 www.seai.ie
0
0.5
1
1.5
2
2.5
3
0 5 10 15 20
Total
Damping
Ratio
(%)
Cyclic Amplitude (KN)
Field Test (Lower Limit)
Field Test (Upper Limit)
3DFE

WP4 Fully coupled dynamic aeroelastic
model of OWT (TCD)
• Develop coupled numerical aeroelastic
model for OWT (NREL 15MW turbine
model developed in Matlab)
• Undertake Load Assessment based on
conditions specific to potential offshore
wind zones around Ireland (using data
from WP1)
• Analyse different cases considering the
range of soil types, foundation sizes and
wind turbine sizes.
• The outputs from this will include a full
load history of the OWT for each
analysis case and the total damping for
the OWT.
80 www.seai.ie

WP4 Benchmarking Matlab model vs Openfast software
81 www.seai.ie
Parameter Description
Rotor Orientation Upwind
Number of Blades 3
Hub Height 150 m
Rotor Diameter 240 m
Blade Length 117 m
Cut-in, Rated, Cut-out
Wind Speed
3 m/s, 10.59 m/s, 25
m/s
Minimum, Maximum
Rotor Speed
5 rpm, 7.56 rpm
Design tip speed ratio 9.0
Monopile Diameter 10 m
Monopile Embedment
Depth
45 m
Control Type Variable Speed-
Collective Pitch

WP5 Design recommendations for damping &
project impact study (TCD)
• Develop design recommendations and guidance
document on monopile damping for Irish offshore
wind farms
• Perform project impact study highlighting the
potential savings in OWT development costs by
undertaking the project
82 www.seai.ie

Summary / Conclusions
• Estimating damping is highly
important for offshore wind
• Aim of the project is to develop new
methods for engineers to estimate
damping on fixed offshore wind
turbines
• Different outputs will be provided
suitable for different stages of
engineering design
• The project is ongoing. Results to be
published by end of 2023.
• Thanks for listening!
83 www.seai.ie

12th Irish Wind Energy Research Network Meeting

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12th Irish Wind Energy Research Network Meeting