12023ফ2ଈ28႘(औዹ႘) Ө11:30-12:05

༌11षզIEA Wind‫׿ؔװ‬՛էߦே఑‫ףؠ؂ם‬՛৿৘ӡIEAӢ֮ӣᆭ፛ਙട੤፛،‫(ؕ؞ץآ‬ጸൺӱIEA Wind TCP)‫ב‬೗௹֖֥փ‫׊‬ӧTask44ӱ‫׾بיכ‬؊‫ז‬՛֭ؕጺ‫׋‬඘ฑ୞䕔OA䠄Operating Agent䠅Paul Fleming (NREL), Jan-Willem van Wingerden (TU Delft)
䕔Web Page
https://iea-wind.org/task44/
օ֠֟֞֊֭‫׉‬ၾဂ ୽ਈࣤዿ፛ॺଞ੄സӹශ‫ףؠ؂ם‬՛፛ॺᆪ኷ӹᆭ୿ॺᇀኾӹനੱ೨଍ኃ ӱ ӡࣤዿ፛ॺଞ੄സӢಛ๹‫ףؠ؂ם‬՛ျ஽ጦዿ‫״بװ‬՛଍ኃ ӱ ዼඑᆭ፛ଞ੄ੱࡱ‫״بװ‬՛ӹؓ‫צ׮׶ؠ‬՛‫ؠ‬ዼඑᆭੳଞ੄ᆪ኷IEA Wind TCP Task44

2What is the wind turbine
wake phenomenon ?
WakeStructure:SideViewડೱ་ॺࣤዿ፛ॺଞ੄സࣽဗถພᆭၒ֪֥వࢬ
2020Ⴉ11ଈ12႘

3IEA Wind TCP Task44
Under dedicatedmeteorological conditions,
the wakes are visible within
a wind energy farm.
Photo taken on 12 February
2008 at the offshore Horns
Rev 1 wind farm, which has
a minimum spacing of 7.5
rotor diameters.
Graphic courtesy ofVattenfall

Wind farm control is an active andgrowing field of research in which thecontrol actions of individual turbines in awind power plant are coordinated tominimise wake interactions.

‫׾بטכ‬؊‫ז‬՛ؕฑ୞֮Ւᆭ፛ᄇဃസၾ଼֭y֭ᆭೆ֭ฑ୞၌ఢ‫ྔב‬ธ֖֥Ւᆭೆ‫֭פיםכ‬ະୗఢዿ‫ב‬௻൚଺֪ጌև
‫׊‬Ւঊᄇ֦ถྙ֖֥փ‫׊‬ଞ੄ᇀኾ֦ց‫׊‬Փ

IEA Wind TCP Task44
Task 44 (Wind Farm Flow Control) ֭‫ר׮‬՛،• ᆭ፛ᄇဃസ֭ฑ୞ᇀኾ֪։֐‫׊‬ே఑੢၍ଞ੄• ᆭ፛ᄇဃസ֭ฑ୞‫֧ؕׯ؟שؠח‬ตႷ୶එַ֭஭ଝ֋൳࿾(ଞ੄֭ኬ࿨)Քᆭ፛ᄇဃፘ֭ໃౌ֪‫׊ׇ‬ဃ፛‫׃ؕ׻׮׬‬ဃ፛౦඘֪։֐‫׊‬ᆭ፛ᄇဃ֭अཏ֭௻་ँՔᆭೆ֭‫פילכ‬झഓ֭࿃ଲ֪‫׊ׇ‬Ւᆭ፛ᄇဃ‫֭׽׮ר‬࿃ଲँՔᆭ፛ᄇဃസ֭ฑ୞‫ؓ׶ب؎֭ؠ׼ؗ‬՛‫׽׮؎֧פ‬،‫्֭׮ט׻פ؞‬ᄇՒฑ୞֪௻ශཐಡՒ‫׮װפח့ַ֭ؕׯ؟שؠח‬Ւ੢၍ଞ੄Ք؎‫׽׮‬،‫׮ט׻פ؞‬Ք‫׼‬՛‫״‬୪হ້֭ු45Task44֭ౄइ໲ฑ
೗֩ౄइ৿৘႘቎֭໲ฑ• ડೱ་ॺ/ၾဂ ୽ਈ (༉ᅳೄ)ዼඑᆭ፛ଞ੄֪৘֘‫׸׽॒ॆ׊‬،་ॺӹଞ੄സ֋ౄब

• ဪੜ་ॺ/ุମଞ੄ಬ/๲ ၟ႞ൃੱ• ‫ؘ׭‬؆‫ب‬Ք‫ؚ؀؟‬՛‫ח‬؋‫ؠ‬Ք‫׭׿ם‬՛, 4኎• ဪಷ‫ףؠ؂ם‬՛‫ׯؕ׻׮׬‬, 3኎• ႘ጵ່๫, 4኎• ဪੜ‫׮ס‬, 2኎
IEA Windேၾ࡙ࡿवӡ࿙ዃ৿৘ӱNEDOӢ֊‫׈‬֭෮๬Քලਢ‫ב‬૪֥ౄबӣ2021Ⴉ12ଈ15႘⿤

ౄइே ᇚேӣ‫׵ب؞ן‬ӣࢷேӣ؊‫׾ب؞بט‬ӣ ‫׾ب؞ؠיח‬ӣ ‫ؓب׼‬՛‫פ‬ӣ‫بי؏׮‬ӣ‫׹י׾‬ӣ ‫לכؠ؃‬՛ӣ႘቎(10‫ت‬ே)6

Task44֭‫ؤ‬՛‫פ‬؆‫צ׸‬՛‫(׭‬WP)
No
WP0WP
Management and coordination /‫؟‬՛‫׾‬ຎද႘቎֊‫֭׈‬ౄइNREL / TUD

ȸ

CENER / NRELဪੜ་ॺTBD(To be defined)ડೱ་ॺՒဪಷEESՒJREՒဪੜ‫׮ס‬Ւ႘ጵ່๫Ւဪੜ་ॺ

TUD / CENER

ဪੜ་ॺDTUȸ৉ጫ֧ྔธ
WP1

Collection of research results /ଞ੄ถऐ֭೭ആWP2

Uncertainty quantification /ᆊ॰ಲต֭࿊ፘँWP3

Overview of technology / algorithms /ਙടՔ‫्֭ؕׯ؟שؠח‬ᄇ

WP4Interaction with other projects /໢֭،‫֧֭׽פל׭آ‬ᎌૢ

Task44֭ேၾ໲ฑ֭‫מכ‬՛ؔ‫׸חץب‬،

8

Task44֭ঊ၌ඡੳ
1) WESC 2023, Glasgow, United Kingdom֦WS‫ב‬ያ࿊

7

IEAWindTask44Wiki:WindFarmFlowControl

2) WP֮ցֽ‫֎֮֩ྜྷු׉‬Ւଵඡ֮Task44 Wiki‫ב‬ఢถཨ3Ӣ २Ԧԟ֭࿊ৼ࿨֩‫بי؞بן‬वਢ֭ಲ౮Ւ‫ؤ‬՛‫׸؜׬פ‬،Ւؔ‫्֭ؕכ׭ؒب׬؀‬௹‫ב‬ያ࿊

https://ieawindtask44.tudelft.nl/9ॆ॒֭ଞ੄၌୶֭ൾऴWind farm control has been a topic
of research for more than twodecades. It has been identified as acore component of grand challenges
in wind energy science to support
accelerated wind energy
deployment and transition to aclean and sustainable energy system
for the 21st century.

1Introduction
1.1Maincontrolobjectivesstudiedtodate
1.2Controlapproaches
1.3Outline
2Windfarmflowcontrolphysics:turbulence,wakesandtheatmosphericboundarylayer
2.1QuasiͲsteadyfloweffects
2.1.1AxialͲinductionͲbasedcontrol
2.1.2Wakesteeringusingyawoffsets
2.2Wakedynamicsandturbulence
2.2.1Wakedynamics
2.2.2BoundaryͲlayerturbulence䖃

2.3Mesoscaleeffects,blockageandwindfarmwakes䖃3Controlalgorithms

䖃

3.1Currentpractice— OpenͲloopcontrol
3.2TheclosedͲloopparadigm
3.3Synergieswithartificialintelligenceandotherdigitalizationconcepts
3.4Controllability,observability,andsensors䖃䖃4Validationandindustrialimplementation
䖃

Overview of wind farm flow control concepts andimportant elements that play a roleIn summary, the field of wind farm
flow control is an active area of
research and innovation, with many
interesting multidisciplinary
challenges, and exciting prospects
for the increase of the total value ofwind energy for society.

4.1ProofͲofͲconceptstudiesinhighͲfidelitysimulationtools
4.2Validationinwindtunnelexperiments
4.3Validationviafieldtests
4.4Industrialimplementation
5Integrateddesignandsystemsperspective
5.1Progressinwindfarmdesignoptimizationresearch
5.2WindfarmcontrolcoͲdesign(CCD)
5.2.1WindfarmCCDforAEPandLCoE objectives
5.2.2WindfarmCCDforprofitabilityobjectives
5.2.3WindfarmCCDfornonͲeconomicobjectives
6Conclusionsᆭೆ‫्֭ؠ׼ؗפילכ‬ᄇ֧‫ץب؟ח׻׮פילכ‬ฑ୞‫ב‬ጦዿ֖֞ᆭ፛ᄇဃസഞ፛֭௻་ँ 10ဪੜ་ॺ་ॺࢇ୿ॺ૩ଞ੄ऎ ุମኢ ӹӨ๲ ேࡖ ໣ഓ‫(ؠ׼ؗפילכ‬Analytical model)्֭ᄇ֧ଙආ ‫ץب؟ח׻׮פילכ‬ฑ୞֭࿓ࡎ኱つᶍ㢼ຊⓎ㟁ᡤ䛻㐺⏝䛷䛝䜛ከ㔜䜴䜵䜲䜽ୗ䛾஘ὶᙉᗘ䛾ண䝰䝕䝹䜢㛤Ⓨ䛧䚸ᩘ್ὶయゎᯒ䛸ほ 䝕䞊䝍䛻䜘䜚䚸ᥦ᱌䛧䛯䝰䝕䝹䛜㧗䛔ண ⢭ᗘ䜢᭷䛩䜛䛣䛸䜢♧䛧䛯㻔㢼㌴䜴䜵䜲䜽䛾㧗㏿ᗘ䞉㧗⢭ᗘண 㻕䚹໙㓄ἲ䜢⏝䛔䛯䜴䜱䞁䝗䝣䜯䞊䝮䛾Ⓨ㟁㔞䜢᭱኱໬䛩䜛䜰䝹䝂䝸䝈
䝮䜢㛤Ⓨ䛧䚸㢼㏿䞉㢼ྥ䛾ศゎ⬟䛜䜴䜵䜲䜽䝇䝔䜰䝸䞁䜾ไᚚ䛾ண⢭ᗘ䛻୚䛘䜛ᙳ㡪䜢ホ౯䛧䛯䚹䜎䛯䚸Ⓨ㟁㔞䛾᭱኱໬䛸㢼㌴䛾Ᏻ඲ᇶ‽䜢ྠ᫬䛻‶㊊䛷䛝䜛᭱㐺䝶䞊䜸䝣䝉䝑䝖⠊ᅖ䠄㼼15㼻䠅䜢♧䛧䛯䚹

G.W. Qian, T. Ishihara, Wind Farm Power Maximization through Wake Steering with a New Multiple Wake Model for
Prediction of Turbulence Intensity, Energy, Vol. 221, pp.1-17, 2021

෾ཏጺ໲‫ءؚؔ׬‬՛‫(ب؜׬‬RIAM-COMPACT)֪‫׊ׇ‬ᆭೆ‫֭פילכ‬ई౽ँ֧ฑ୞ַ֭࿪ዿ

11ડೱ་ॺࣤዿ፛ॺଞ੄സ ၾဂ ୽ਈՒ‫ؘ׭‬؆‫ب‬Ք‫ؚ؀؟‬՛‫ח‬؋‫ؠ‬Ք‫׭׿ם‬՛, ဪಷ‫ףؠ؂ם‬՛‫ׯؕ׻׮׬‬, ႘ጵ່๫, ဪੜ‫׮ס‬Alpha Ventus Offshore Wind Farm (崱崌崬)12ෘ୳嵊崯嵓峘Mini Alpha Ventus峼ৌ଴峒峁峉崡崹崛嵛ගRIAM-COMPACT峘ਙચ௬੼

BenchmarkTestingofMiniAlphaVentus(12WindTurbines)

Takanori Uchida et al., Numerical visualization of wind turbine wakes using passive
scalar advection-diffusion equation and its application for wake management,
Wind Engineering, July, 2022, https://doi.org/10.1177/0309524X221113011

প஑୆ੀಽ௯ྍ嵣ಖഡ௯੤ெ஑峼৷岮峉মু১峘ਫ਼઒

13ম઀੧ু১(CFD)म‫ؚ‬প஑୆ੀಽ௯ྍ॑৷ःञ૭ଳ৲ৰୡध৒ਙ৓पଐ஀ऩ঳ಱෘ୳嵊崯嵓峘Mini Alpha Ventus峑峘ਙચ௬੼

FlowFlow

Volume source௯੤ණषभ
௯भ෶োഓ২
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Volume sourceᆭೆַ֭ᅀ᎕ӱ௻൚
WF๺໲֭ᄇဃፘӱ௻་ӡ‫ץب؟ח׻׮פיםכ‬Ӣ௯੤ණषभ௯भ෶োഓ২
(15deg)14

15ෘ୳嵊崯嵓峘Mini Alpha Ventus峑峘ਙચ௬੼ᆭೆ؄؋ஸ֦֭֔ᆭ໒

ᆭೆ؄؋ஸ֦֭֔ᆭ໒

No.11

௯੤ණषभ
௯भ෶োഓ২
(0deg)

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WF๺໲֭ᄇဃፘӱ௻་

No.11

௯੤ණषभ
௯भ෶োഓ২
(15deg)16֓พྐց‫֧֋׉‬օ֓֕փֽ֖֞
KYOTO, JAPAN-NOVEMBER222015: Ancient paintings of Wind and Thunder Gods on partitions at Kenninji Temple

https://www.shutterstock.com/ja/image-photo/kyoto-japan-november-22-2015-ancient-463824266