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