Professor Deborah Greaves - Supergen ORE€¦ · May 2015 Aug 2015 Nov 2015 Feb 2016 May 2016 Aug...
Transcript of Professor Deborah Greaves - Supergen ORE€¦ · May 2015 Aug 2015 Nov 2015 Feb 2016 May 2016 Aug...
Professor Deborah Greaves
Supergen ORE Hub – DirectorUniversity of Plymouth
WP4 Design for future ORE systems
• Siya Jin• Tom Tosdevin• Martyn Hann• Dave Simmonds• Deborah Greaves
WP4: OverviewAim: Develop methodology for identification of failure mode conditions in floating offshore renewable energy (FORE) systems, optimise to reduce uncertainty in key parameters, enhancing reliability to enable LCOE reduction Learn: Experience / methods from
• (Offshore) Wind turbines• Oil & Gas structures• Coastal structures
Identify: Gaps and limitations: dynamic response
Design: Failure mode conditions identification approach tailored for FORE systems
WP4 Work flow
Objectives• Develop methodologies for
failure mode assessments• Determine confidence
intervals by probabilistic process and identify key uncertainties
• Reduce level of uncertainty in key parameters and optimize system reliability level to reduce the LCOE
• Evaluate methodologies applicable to different device types
Environment Characterisationwind, wave and tidal stream
FORE System Response Modelling
DoF, responses focused on extreme
Failure Mode Conditions Identification
objective function and strength data: limit states-ULS or fatigue
Probabilistic AssessmentMonte Carlo simulations / DLG/ Design wave
groups
Sensitivity Analysis uncertainties
Reduce uncertainty in key parameters
‘optimal’ reliability level
WP4 Work flow
Objectives• Develop methodologies for
failure mode assessments• Determine confidence
intervals by probabilistic process and identify key uncertainties
• Reduce level of uncertainty in key parameters and optimize system reliability level to reduce the LCOE
• Evaluate methodologies applicable to different device types
Environment Characterisationwind, wave and tidal stream
FORE System Response Modelling
DoF, responses focused on extreme
Failure Mode Conditions Identification
objective function and strength data: limit states-ULS or fatigue
Probabilistic AssessmentMonte Carlo simulations / DLG/ Design wave
groups
Sensitivity Analysis uncertainties
Reduce uncertainty in key parameters
‘optimal’ reliability level
Environment Characterisation:Site selection Billia Croo
(58.96° N, 3.38° W)
Scapa Flow (58.89° N, 2.95° W)
0Hebrides(57.88° N, 7.19° W)
Wave Hub(50.19 ° N, 5.43° W)
FabTest (50.13° N, -5.01° W)
Pembrokeshire Demonstration Zone
Wave data for wave Hub (water depth 51-57m):
Physical data by waverider buoy 2015/06/01 – 2018/05/31, interval 0.5 hours
Hindcast data from Met Office 1980/01/01 – 2018/12/31, interval 3 hours
Reanalysis data from ECMWF1979/01/01-present, interval 6 hours
Environment Characterisation:Data selection
Comparison with buoy data Reanalysis data selected
May 2015 Aug 2015 Nov 2015 Feb 2016 May 2016 Aug 2016 Nov 2016 Feb 2017 May 2017 Aug 2017 Nov 2017 Feb 2018 May 2018Time
2
4
6
8
10
12
14
16
Tz [s
]
Measured Tz against Hindcast and Reanalysis Data
Measured
Hindcast-Met Office
Reanalysis-ECMWF
May 2015 Aug 2015 Nov 2015 Feb 2016 May 2016 Aug 2016 Nov 2016 Feb 2017 May 2017 Aug 2017 Nov 2017 Feb 2018 May 2018Time
0
2
4
6
8
10
12
Hs
[m]
Measured Hs against Hindcast and Reanalysis Data
Measured
Hindcast-Met Office
Reanalysis-ECMWF
Hindcast Reanalysis
HsRE -14.45% -1.80%
NRMSE 0.55 0.68
TzRE 4.16% -3.32%
NRMSE 0.46 0.47
DirRE 9.73% -3.20%
NRMSE -0.63 0.06
Environment Characterisation:Design conditions
10 -3 10 -2 10 -1 10 0 10 1 10 2 10 3
Return Period [years]
0
2
4
6
8
10
12
14
16
Hs
[m]
Return Values in 3-Parametric Weibull Model
Fitted Curve
Original Data
95% confidence interval
Two distributions are used to evaluateuncertainties in extremes: 1. Weibull-Lognormal (overall distribution)2. GPD-Lognormal (extreme distribution)
Hs return value analysis: less than 3% difference
Reanalysis data (40 years)
Model 40 years 50 years 100 years
10.05 m
Weibull 10.61m(8.93m 12.30m)
10.77m(9.03m 12.51m)
11.26m(9.36m 13.16m)
GPD 10.40m(9.61m 11.50m)
10.55m(9.65m 11.85m)
10.96 m(9.78m 13.05m)
10 -3 10 -2 10 -1 10 0 10 1 10 2 10 3
Return Period [years]
6
8
10
12
14
16
18
20
22
Hs
[m]
Return Values in GPD Model
Fitted Curve
Original Data
95% confidence interval
Environment Characterisation:Design conditions
2 4 6 8 10 12
Zero-crossing Wave Period [s]
0
2
4
6
8
10
12
Sign
ifica
nt W
ave
Hei
ght [
m]
Overall Hs-Tz
50 year
100 year
Measured Data
7.5 8 8.5 9 9.5 10 10.5 11 11.5 12
Zero-crossing Wave Period [s]
6.5
7
7.5
8
8.5
9
9.5
10
10.5
11
Sign
ifica
nt W
ave
Hei
ght [
m]
Extreme Hs-Tz
50 year
100 year
Measured Data
Direction [degree] / Period [second]
Wave Power Given on Mean Wave Direction and Tz
5
10
15
30
210
60
240
90270
120
300
150
330
180
0
Hs-Tz joint probability distribution for Wave Hub
Weibull-Lognormal (overall distribution)
GPD-Lognormal (extreme distribution)
FORE system response modelling: Design wave
Long time series from a random seastate
Short wave profiles: • New Wave • Design Load
Generator (DLG)
• Ensemble of 500 DLG wave profiles • 1000 MC non-linear WEC-Sim simulations • Comparison of mooring extension probability• DLG under-prediction due to the preceding wave train
and non-linearity
FORE system response modelling: Extreme response using DLG DLG for X-MED buoy
Xmed nonlinear, 500 DLG vs 1000 runs comparison
0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55
Extension
0
0.02
0.04
0.06
0.08
0.1
Prob
abilit
y
1000 runs
DLG 500
FORE system selection and modelling: Reference model selection
Botto
m-r
efer
ence
Floa
ting
Heaving buoy Hinged raft
FORE system selection and modelling:Tools
Potential flow based (linear, superposition): • BEM (e.g., WAMIT, NEMOH, AQWA) + WEC-Sim +
ParaviewN-S formula based (CFD, fully non-linear): • Fluent, CFX, Star C++, LS-DYNA, OpenFOAM
FORE system selection and modelling:WEC-Sim Validation
H=1.8m, T=7s
Newman, J.N., 1994. Wave effects on deformable bodies. Applied Ocean Research 16, 47–59.Sun, L., Taylor, R., Eatock, Choo, Y.S., 2011. Responses of interconnected floating bodies. The IES Journal Part A: Civil and Structural Engineering 4 (3), 143–156.Zheng, S.M., Zhang, Y.H., Zhang, Y.L. and Sheng, W.A., 2015. Numerical study on the dynamics of a two-raft wave energy conversion device. Journal of Fluids and Structures, 58, pp.271-290.
5 m
Newman (1994)Sun et al. (2011)Zheng et al. (2015)WEC-Sim
Normalized pitch RAO at hinge
FORE system selection and modelling:CFD and WEC-SimH
=1.8
m, T
=10s
H=1.8m, T=7sH=
1.8m
, T=7
s
Linear results (WEC-Sim)
Nonlinear results (CFD)InWaveby MaRINET2WEC-SimCFD
Linear vs Non-linear - Marinet2 hinged WEC
Summary• Introduce the failure mode conditions identification process for FORE systems• Characterise the wave conditions of Wave Hub, evaluating the 50 year return
values• Preliminary assessment of DLG design wave method• Build and validate numerical modelling tools for a hinged-raft WECNext Steps• Identify failure mode conditions using design wave method• Apply methodologies to different reference WEC types • Guide design wave methodology for physical tank tests• Select reference floating offshore wind structure• Extend modelling to fully coupled soil-structure-wave interaction