Wave Energy - University of Adelaide

Junhua Wu,Slava Shekh,NataliiaSergiienko,BenjaminCazzolato,Boyin Ding,

FrankNeumann,andMarkusWagner

PresentedbyMarkus

§Waveenergyisawidelyavailablebutlargelyunexploitedsourceofrenewableenergy

§ Therearedozensofactivewaveenergyconverter(WEC)projectsexploringavarietyoftechniquesforharnessingwaveenergy

§ InpartnershipwiththeSchoolofMechanicalEngineering,weareconsideringawaveenergyconverter(WEC)calledCETO

§ TheCETOsystemconsistsofoneormorefullysubmergedbuoys

SingleWECoptimisation§ Ringwood(2004),McCabe(2010)andHals(2011)optimisevariousaspectsofsemi-submergedbuoys,suchasgeometryandcontrol

§ Korde (2015)investigatesdifferentcontrolstrategies formaximisingpowerabsorptionoftwobuoys,oneofwhichisfullysubmerged

WECarraysandtheiroptimisation§ Cruz(2009)andWeller(2010)exploretheeffectofvariousfactorsonarrayperformance,includingdevicespacingandarraylayout

§ Fitzgerald(2007),Child(2010)andSnyder(2014)optimisearraysofsemi-submergedWECs

ThereisalackofresearchonoptimisingarraysoffullysubmergedWECs

Submerged buoy

Tether

Power take-off system

Sea floor

Advantages• Invisible from the shore• Higher survival in storm conditions• Hydrodynamics allow 2 times more

power to be absorbed from surge motion (e.g. via three-tether or asymmetric mass)

§ ThevariablesoftheCETOmodelleadtoanoptimisation problem:Whatisthebestcombinationofbuoyradiitousefordifferentarraysizes?

§ Asolution(configuration)canberepresentedas:(r1,…,rn)e.g.thelayoutshown is(2,2.5,4,5)

§ Asolutioncanbeevaluatedusingtheq-factor,whichistheratioofthepowerabsorptionofabuoyarraycomparedtothepowerabsorptionofthesamebuoysinisolation

2x2Array 3x3Array

Best(q-Factor) 0.999 0.996

Worst (q-Factor) 0.965 0.933

Best2x2 Best3x3

waves

Hiddenbiasofqfactor:smallerbuoysarealwaysmoreefficientthanlargeronesàWidth(considersbuoydimensions)

1.10E+07'

1.11E+07'

1.12E+07'

1.13E+07'

1.14E+07'

1.15E+07'

1.16E+07'

1.17E+07'

1' 22'

43'

64'

85'

106'

127'

148'

169'

190'

211'

232'

253'

274'

295'

316'

337'

358'

379'

400'

Power'out'(W

a9)'

Genera=ons'

Best'Power'

Mutated'Power'

0.65%

0.7%

0.75%

0.8%

0.85%

0.9%

50v10% 50v5% 50v4% 50v3% 50v2% 50v1%

Accuracy%

Power%

RCW%

Speed-upbyfrequencyreductionfrom2100minutesto42minutes(50buoys).

Anoldcomputersciencetrick…caching!!!Matlab mostfrequentlycalls:integral,factorial,bessel.Fora50-WEC-array,1millioncallstointegral aremade(90%duplicates).èCachingreducestheruntimeby85%.

Now:runtime6minutes(factor350).

(400g) (200g)1+1 EA CMA-ES

Po

we

r O

ut

(Wa

tt)

×107

1.2

1.21

1.22

1.23

1.24

1.2525 Buoys

(400g) (200g)1+1 EA CMA-ES

Po

we

r O

ut

(Wa

tt)

×107

2.14

2.16

2.18

2.2

2.22

2.2450 Buoys

80070060050040030020010000

100

200

300

400

500

600

700

800×10

5

3.8

4

4.2

4.4

4.6

4.8

5

5.2

5.4

5.6

5.8

à TuningintheendwithCMA-ESispossible,though.

0 100 200 300 400 500 600 700 800 900 10000

100

200

300

400

500

600

700

800

900

1000×10

5

3

3.5

4

4.5

5

5.5

6

010020030040050060070080090010000

100

200

300

400

500

600

700

800

900

1000×10

5

3

3.5

4

4.5

5

5.5

6

1800160014001200100080060040020000

200

400

600

800

1000

1200

1400

1600

1800×10

5

2

2.5

3

3.5

4

4.5

5

5.5

6

Algorithms:localoptimanotexploitedSpeed-up:simplificationnotadequate

Computationtime:8CPUdaysvs.7CPUyears

§ TranslationtoC§ Parallelisation§ Increaseinaccuracy§Multi-objectiveoptimisationà PPSN2016:142-foldspeed-upwhilestillusing25frequencies.

Actualnextsteps§Wavedirections:distribution(happeningnow)§ “mechanicalengineering”-analysisofresults(happeningnow)§ CarnegietosetuparraysofWECsaroundAustralia (jointARCgranthappeningnow)

§ Power-takeoff-controlleroptimisation§Machinelearningmodelstolearntheinteraction(happeningnow)

§Over100peopleplayedthe“optimisepoweroutput”gameusingAndroidtabletsatOpenDay 2017

§ Leaderboard:http://od.mewx.org/

§RefinedversiontobeusedatIngenuity2017(31Oct,thousandsofattendees)

MSSoftwareEngineeringstudents:Chenwei Feng,Mengyu Li,Yuanzhong XiaSupervisor:Dr. MarkusWagner

§ Goal:model&predictpoweroutputbasedonfarmlayout§ MachinelearningtechnologyasquickandprecisesurrogatesforNataliia’s analyticalmodel(frequencydomain)

§ https://mse.mewx.org§ 2buoysdoable,4buoysdifficult(imprecise)

MSSoftwareEngineeringChenwei Feng,Mengyu Li,

Yuanzhong Xia

§ Goal:model&predictpoweroutputbasedonspringconstantk,dampercoefficientd

§ 4buoys§ Scikit-learn(Python)§ https://github.cs.adelaide.edu.au/a1668648/HonoursWEC

Onesettingforallbuoys(neuralnetwork,randomforest)

Differentsettingsforeachbuoy(best100settings)

§ Educatedguessasareference:Whatisagoodlayout?Grid?Linear?Hexagonal?

§Wavescomefromtheleft…

PhDstudentMehdiNeshatMSstudentYuanzhong Xia

Andthesamefor4and9buoys…

Similarfor4and9buoys…

Outputof1isolatedbuoy:4.92e5W Thisis1-dimensional… howabout2D?

2buoys– Characterisationofeffectsforoptimisationpurposes§Wavescomefrombottomleft,50msafetydistance§ 1st buoyisat(100,0),shownisthewavefarm’stotalpoweroutputlandscapedependingonthe2nd buoy

Best:notnexttoeachother,butslightlyoffset

4 buoysMappingforeachbuoygiventheotherthreebuoys:

Besteverfound:

16buoys§Weseepatterns…

Besteverfound:

Farm’spower,withomittedbuoy’slocationasdashedline

Maxtetherelongationacrossfarm(arbitrarylimit:3m,here:4.5mreached)

§ Basedonthecharacterisation,wecandesignproblem-specificalgorithms.Whyisthisimportant?

4buoys:maxoutputisverysimilaracrossapproaches(scalenotvisible)

16buoys:+5%fortherightmosttwocustomapproaches

§ Basedonthecharacterisation,wecandesignproblem-specificalgorithms.Whyisthisimportant?

Markus [email protected]

http://cs.adelaide.edu.au/~markus/Theslideswillbemadeavailabletoday.