adaptive liquid cooling methods in microchannels 11-16 web.pdffor modelling purpose of transmission...

INTRODUCTION

METHODOLOGY

Adaptive Liquid Cooling Methods in MicrochannelsJaakko McEvoy ([email protected]), Dr. Tim Persoons

Dept. of Mechanical & Manufacturing Engineering, Trinity College Dublin,

RESULTS

CONCLUSIONS

ACKNOWLEDGEMENTThis publication has emanated from research conducted with the financial support of Science Foundation Ireland under the SFI Strategic Partnership Programme Grant Number SFI/15/SPP/E3125. The opinions, findings and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of the Science Foundation Ireland.

Objective(s)

Microfluidic phenomena within the adaptive channelsare studied using μ-PIV. This consists of an inverted epi-fluorescent microscope, a high repetition pulsed Nd:YLFlaser as the light source & fluorescent microspheres astracer particles within the channels. The Nitinol spring isactuated using a heat source to simulate a CPU underheavy load. Continuous temperature, power, flow andpressure readings are used to determine the efficiency ofthe spring to act as a autonomous flow regulator.

CFD is used to predict the optimum spring location andpitch within the channel, as well as validation for someof the simpler channel geometries.Two channels are tested:• A standard copper microchannel heat sink (for thermal

measurements)• A PDMS channel with a very low relative roughness

value, as a control for the pressure drop readingsFlow pulsation which has been shown to increase heattransfer by up to 40%2 will be tested with the adaptivechannels using a Noliac piezoelectric actuator.

Data centres are estimated to consume around 2% of theglobal electricity demand and over 7% of Irelands entiredemand in 20101. EirGrid estimates that data centres willmake up 20% of the nations demand by 2025.

One of the largest consumers of energy within datacentres is the cooling system and accompanying chillersat nearly 40% of total demand. The aim of this research isto develop a chip level adaptive microchannel heat sink toremove high grade heat from servers for reuse in districtheating or onsite electricity generation.

• Study heat transfer and fluid flow at the microscalewithin complex heat-sink geometries under smoothand pulsating flow

• Development of “smart" thermally controlled self-regulating flow control using SMAs to maximize outlettemperature and target CPU hotspots under variableloads, focusing on time-varying local (server level)conditions in the context of district heating and loadshifting

• Develop a refractive index matching method fortraditional experimental PIV systems to allow for wholefield cross-correlation

REFERENCES1. S. Garimella, T. Persoons, J. Weibel, L-T. Yeh, “Technological drivers in

data centers and telecom systems: Multiscale thermal, electrical, and energy management," Applied Energy, vol. 107, 2013

2. T. Persoons, T. Saenen, T. Van Oevelen, M. Baelmans, “Effect of Flow Pulsation on the Heat Transfer Performance of a Minichannel Heat Sink”, JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME, vol. 134, (9), 2012

Refractive index matched PIV isalso further developed using aworking fluid of ammoniumthiosulfate at a high concentrationand temperature to match therefractive index of PMMA

Figure 1: Epi-fluorescent microscope & high-speed camera

Figure 2: RIM-PIV experimental setup

Figure 3: Experimental flow loop

Refractive index matched PIV was achieved at a concentration of 72.5% ammonium thiosulfate in water.

Figure 4: Light sheet visualisation of an array of PMMA pins with hollow glass sphere seeding particles in (a) pure water, and an aqueous ammonium thiosulfate solution at concentrations

of (b) 67.7% and (c) 72.5%

Figure 5: Image averaging of seeded RIM solution

Figure 5: Instantaneous velocity field for RIM solution

With a fully refractive index matched fluid the laserlight sheet passes through the studied structureunaffected, allowing for whole flow fieldillumination. With unmatched fluid “shadowregions” are formed behind structures, the velocityin these regions can not be quantified.

CFD results indicate the optimum spring location to be at the top of the channel. Weather this is too far from the heat source for the Nitinol micro-spring to activate remains to be seen.

Figure 6: CFD results for pressure drop across microchannel

Figure 7: CFD results for channel base temperature

SEM and white light interferometry wereused to accurately measure the surfaceroughness and geometry of themicrochannels.

High heat fluxes in electronics components need to be combated in an effective manor,while still recouping the maximum possible amount of high grade energy. The adaptivemicrochannel heat sink shows promise, but is still untested in a live case.RIM-PIV has been shown to be an effective whole flow field visualisation method and theworking fluid proposed has many advantages over some of the existing chemicals used.

Figure 9: SEM images of machined channel

Figure 8: Temperature and velocity contours for channel with embedded spring

METHODOLOGY1. Gas System Model:• Assumptions and Limitations • Modelling of Gas network: Steady and dynamic models2. Interactions between Electricity and Gas systems:• Coupling electrical and gas systems in P2G and G2P

M. Ali Ekhtiari1 ([email protected]), A. Chandrasekar1 ([email protected]),Damian Flynn2 ([email protected]) and E. Syron1 ([email protected])

University College Dublin, School of Chemical and Bioprocess Engineering 1, School of Electrical & Electronic Engineering2


OBJECTIVE(S)

INTRODUCTIONBALANCING BETWEEN DIFFERENT ENERGY SOURCES, MAINLY FOSSIL FUELS AND RENEWABLES, AND SEVERAL END-USERS WITH DIFFERENT BEHAVIOURS IS A BIG CHALLENGE NOWADAYSWHICH TWO LARGE GAS AND ELECTRICITY NETWORKS PLAY A VITAL ROLE IN THE ENERGY SYSTEM TO TRANSPORT, CONVERSE AND STORE ENERGY. FOCUSING ON IDENTIFYING THE ROLEOF A GAS NETWORK IN AN INTERCONNECTED ENERGY SYSTEM INSTEAD OF FOCUSING ON SINGLE ENERGY CARRIER BY MODELLING APPROACHES IS THE MAIN PURPOSE OF THIS RESEARCHWORK. IN THIS POSTER WE FOCUS ON MODELLING OF GAS NETWORK AND PRESENT SOME RESULTS AFTER INJECTING SYNTHETIC GAS FROM P2G SYSTEM INTO THE GAS NETWORK TO SEEHOW THE FLOW-RATE PROFILE BE CHANGED. IRISH GAS NETWORK AS THE CASE STUDY HAS BEEN CHOSEN FOR MODELLING PURPOSE.

1. Modelling of Steady and Transient States of the Gas Network.2. Investigation of combined gas and electrical networks in an integrated energy system

“Delivery and Storage natural Gas”, the US. Energy Information Administration (EIA), 2017.“Annual Renewable Energy Constraint and Curtailment”, Eirgrid Annual Report, 2016.

REFERENCES

End Users

Transportation

Residential

Industry

Agriculture, Services, etc.

Energy Storage

Gas Network

Electrical Network

Gas Refineries

Power Plants

Finding a modelling approach for analysing this integrated system arises challenge

Energy Sources End Users

Networks

Natural Gas Process diagram from extraction to consumption units which show the fossil fuels wells, separation units, gas refinery, storage terminals, compressor stations and end-users. For modelling purpose of transmission and distribution network, the boundary conditions should be identified such as physical properties of pipe and natural gas such as pipe diameter, length of pipe, gas pressure in injecting points, demands and etc.

Gas and Oil Wells Oil and Water

SeparationVented and Flared

Gas Refinery

Underground Storage

Compressor StationCity Gas Station

Odorizing Unit

Town Board Station

Production Lines Transmission Lines Distribution Lines

Figure 4. The Gas Network Sample which Ireland's gas network has been modelled as a pilot plan to simulate. This example consists 13 nodes and 14 branches

In this study Ireland’s gas network as case study has been chosen with 13 nodes and 14 main branches where the three Moffat, Corrib and Kinsale are the reference nodes the from there the gas was supplied to the network ate 14 MPa pressure the network has been illustrated in figure(4).

Wind Turbine

Gas Resources

P2G

End Users

Transportation

Residential

Industry

Electricity Losses

Gas-Fired Power Generation Plants

Other Energy Sources

Hydro-Electric power Generators

Bio-Methane Plants

CO2

7000 GWh

5000 GWh

700 GWh

43,000 GWh

Compressor Stations

442 GWh

37,000 tonWater source

63,000 ton

138GWh

INTEGRATED ENERGY SYSTEM MODEL

RESULTS & CONCLUSIONS

In the first step the energy flow of Ireland has been extracted which the process flow diagram of the integrated energy system is shown in figure (5) afterward the amount of annum wind dispatched down employed to calculate and evaluate the possible curtailed wind energy to convert into synthesis gas and inject into a gas network.

Figure 5. A gas network in an interconnected energy system

Excess Electricity442 GWh

P2G

Methane138 GWh

Gas Network

Carbon Dioxide37,000 ton

Water63,000 ton

9,000 ton13 bcm

Non-transportable renewable electricity

Water Hydrogen

Carbon Dioxide

Methane

Gas Network

“DR

Figure 2. An Energy System Connections by Gas and electrical Networks

Figure 1. Role of Networks in balancing of an Energy System

Figure 3. A general process flow diagram of natural gas from extraction to consumption units

Modelling of Gas Network in an Interconnected Energy System

“Hydrogen from renewable electricity: An international review of power-to-gas pilot plants for stationary applications”,

INFRASTRUCTURE DEGRADATION UNDERSTANDINGPIPELINE INFRASTRUCTURE MODIFICATION APPROACHESLEAKAGE IDENTIFICATION, QUANTIFICATION & MITIGATIONLONG-TERM RENEWABLE GAS COMPATIBILITY IN NATURAL

GAS NETWORKCOMBUSTION & ELECTO-CHEMICAL CONVERSION OF

NATURALGAS/RENEWABLE GAS MIXTURECOMBUSTION OF PURE RENEWABLE GAS

THE FUTURE ROLE OF GAS NETWORKS IN INTEGRATED ENERGY NETWORK

Devasanthini Devaraj ([email protected]), Philip Donnellan ([email protected]), Eoin Syron ([email protected])

University College Dublin


REPRESENTATIVE RESEARCH IDEASFUTURE GAS SCENARIOSUNDERSTAND ROLE OF NATURAL GAS AND ITS INFRASTRUCTURE IN MITIGATING GREENHOUSE GAS EMISSIONS AND RENEWABLE RESOURCE INTEGRATIONELECTRIC POWER AND NATURAL GAS SYSTEM INTERDEPENDENCIESEND USE APPLICATIONS (VEHICLES)ENERGY STORAGECOMPLIANCE WITH CLIMATE ENERGY ROADMAPS

INFRASTRUCTURE & PIPELINES

TRANSPORT & STORAGE

ELECTRICAL NETWORK DEPENDENCY

RENEWABLE ENERGY INTERMITTENCY

TRANSITIONS OF NG END USES TO USE RES

NATURAL GAS: A

TRANSITION FUEL

GHG EMISSION

GOALS

OVERSUPPLY OF

RENEWABLE ENERGY

NATURAL GAS

NETWORK

PARALLEL PROJECTS

COMPLEMENTARY TECHNOLOGIES

REQUISITE INVESTIGATIONS

STORE & SUPPLY IN NG NETWORK

e Dublin

UPGRADATION, PIPELINE QUALITY

PPLY IN NG NETWORK

BIOGAS

BENEFITS,

EFFICIENCY CONSTRAINTS

PtG

METHANE

CNG,

GAS ENGINES,

GAS TURBINES,

GAS BURNERS,

UNDERGROUND STORAGE,

LEAK DETECTION

HYDROGEN

PPPPtGPPPPPPPPPPPPPPPP

METMETMETMETMETMETMETTMETMETMETMMM TMMMETTTMM TTMETTTHAANNANANANANNNANAANAAAAAAAAA EEEEEEEEEEEEEEEEEEEEEEEE

BIBIBBIOBIOOBIOOOOBIOBBIOBIOBIOBIOBIOBIOBIBIOOBIBIOBIOB OBIOOOBIIOBIIOBIOOGASGASGGGGGGASGASGASAGASASSGGAGASGASAAASGASGASGASASGGGGG

HYHYHYYYDYDYYDYYYYYYHYYYYY ROROROROROROROGROOROGRRORORORORRORORORORORORRRRROORO ENENEEEEEEEEEEEEEENE

SHORT-TERM: 100% NATURAL GAS MID-TERM: NATURAL GAS/RENEWABLE GAS BLEND 100% RENEWABLE GAS

ADVANCED NGCC, ENERGY

STORAGE

GAS TURBINE, CCHP, DG

NATURAL GAS,

BIOGAS

HYBRID SYSTEMS, ADV

ENERGY STORAGE

NG, BIOGAS,

RENEWABLE H2

FUEL CELL

SYSTEMS

ADV ENERGY STORAGE,

VEHICLE-TO-GRID, SMART

GRID

PtG, BIOHYDROGEN

FUEL CELLS

RENEWABLE ENERGY GOALS

GAS NETWORK

DECARBONISATION

IN

ES

INTRODUCTIONTHE INCREASE IN RENEWABLE GENERATION FROM SOLAR PLANTSAND WIND FARMS REDUCES THE INERTIA OF THE POWER SYSTEM,WITH POTENTIAL IMPACTS FOR THE SYSTEM STABILITY. VIRTUALSYNCHRONOUS GENERATOR (VSG) CONTROL HAS BEEN PROPOSEDAS A MEANS TO PROVIDE VIRTUAL INERTIA FROM THOSEDISTRIBUTED ENERGY RESOURCES (DER). IN THIS WORK, WECOMPARE THE POWER SYSTEM PERFORMANCE OF VSG TOSYNCHRONOUS GENERATOR (SG).

METHODOLOGYa) Mathematical model of VSG and integration with a wind

farmb) Validation of VSG model by comparison with hardware test

resultc) Comparison of VSG performance to SG in IEEE 39 bus

System

Comparison between Virtual Synchronous Generator and Synchronous Generator in Power System

Junru Chen 1 ([email protected]) and Terence O’Donnell 2 ([email protected])University College Dublin/Electrical Engineering

MATH MODEL VALIDATION WITH HARDWARE RESULT

CONCLUSIONS• VSG has same performance with SG in terms of frequency (Fig. 5a) to active power regulation

(Fig.5c). That means VSG can provide same amount of inertia into the system as SG.• VSG has different performance with SG in terms of voltage (Fig. 5b) to reactive power regulation

(Fig. 5d). While to stabilize the voltage, VSG requires less reactive power than SG.• The dynamics from the wind (VSG(s)), although affects the VSG output power (Fig. 5c and Fig. 5d),

would not go into the system (Fig. 5a and Fig. 5b).• The work does not consider the dynamics from the ESS, and this will be further researched in

future.


Objectives• Provision of virtual inertia to the conventional system from

the DER

• Comparison of system performance of VSG controlled DER tosynchronous generator

VIRTUAL SYNCHRONOUS GENERATORVirtual Synchronous Generator aims to provide the virtual inertiato the power system from the DER by mimicking the dynamics ofsynchronous generator.

Fig. 1. VSG (right) mimic SG (left)

Structure: a) Renewable energy mimics SG primary moverb) Energy storage mimics SG’s kinetic energy

Strategy:The voltage output from VSG is ∠ .

Active Power Regulationa) SG dynamics or swing equation with inertia time constant :̇ = ∆̇∆ = + −Where is the renewable energy, P is the power injecting to the grid.b) Frequency to active power droop with droop gain := ( − )Where is VSG frequency, is grid frequency.

Reactive Power RegulationVoltage droop support= ∗ + ( ∗ − )Where V∗ is reference voltage, is grid voltage.

IEEE 39-BUS SYSTEM CASE STUDY

Fig. 2. Comparison VSG results on hardware and math model

Fig. 3. VSG embedded wind farm

• At 2.5 s, reference power step changes to300 W; at 12.5 s, reference reactive powerstep changes to 300 VA; at 22.5 s, gridfrequency step changes to 49.9 Hz.

• Fig. 2 validates math model, thus could befurther implemented into IEEE 39-bussystem model reliably.

• Fig. 2 also depicts that the VSG canaccurately follow the active powerreference but have steady state error onreactive power tracking.

The wind turbine/induction generator connectedconverter is still working on Maximum Power PointTracking mode. The Electric Storage Systemconnected converter regulates the DC voltage. Thegrid connected converter has embedded VSG control

Fig. 5. Simulation result: 22.5% Wind PenetrationVSG(c) - the wind is constant

VSG(s) - the wind is stochastic

0 5 10 15 20 25 30-100

0

100

200

300

400

500

600

Time (s)

Act

ive

Pow

er (W

)

ReferenceHardwareDAE Model

0 5 10 15 20 25 30-100

-50

0

50

100

Time (s)

Reac

tive

Pow

er (V

A)

ReferenceHardwareDAE model

Fig. 4. IEEE 39-bus System

VSG (Fig. 3 topology) is replacing SG5 (red) inIEEE 39-bus System. G1 and G3 is replaced bywind generator (marked) to reduce the systeminertia. The system suffered N-1 contingencywith G10 (yellow) lost at 1 s

0 10 20 300.98

0.985

0.99

0.995

1

Time (s)

Fre

quen

cy (

pu)

SGVSG(c)VSG(s)

0 5 10 15 204.85

5.25.45.65.8

Time (s)

Act

ive

Po

wer

(pu)

SGVSG(c)VSG(s)

0 5 10 15 20 25 301.5

2

2.5

3

Time (s)

Rea

ctiv

e P

ow

er (

pu)

SGVSG(c)VSG(s)

0 5 10 15 20 25 300.98

1

1.02

1.04

Time (s)

Vol

tage

(pu

)

SGVSG(c)VSG(s)

Simulation Conditions:The settings for the SG and VSG in inertiatime constant , frequency to activepower droop gain and voltage droopgain are identical.VSG self-settings, i.e. converter PI controllerand filter, are following the design standard.While SG self-settings, i.e. sub-transienttime constant and reactance, are followingthe experienced value.The ESS in Fig. 3 is assumed ideal storagewith infinite capacity and unlimited rate ofcharge/discharge.

INTRODUCTION• THE GROWTH OF DISTRIBUTED GENERATION (DG) FROM

RENEWABLE SOURCES POSES MANY TECHNICALPROBLEMS FOR THE OPERATION AND STABILITY OF THEPOWER SYSTEM.

• THE RENEWABLE DG DOES NOT PROVIDE GRIDSTABILISATION FEATURES SUCH AS INERTIA,SYNCHRONISING TORQUE, DAMPING TORQUE, ETC.

• THERE IS A NEED TO FIND ALTERNATIVE WAYS TOPROVIDE GRID STABILISATION SERVICES SUCH ASFREQUENCY SUPPORT AND VOLTAGE SUPPORT.

• APPROACHES SUCH AS THE USE OF DISTRIBUTEDDEMAND RESPONSE AND ENERGY STORAGE ARE BEINGEXPLORED FOR PROVISION OF FREQUENCY SUPPORT.

• IN ORDER TO MANAGE AND COORDINATE THESEDISTRIBUTED ENERGY RESOURCES (DER) NEWTECHNOLOGIES AND CONTROL STRATEGIES AREDEVELOPED AND THERE IS A NEED TO RIGOROUSLY TESTAND VALIDATE THEM BEFORE ONSITE IMPLEMENTATION.

METHODOLOGYa) Development of a real-time simulation, hardware in

the loop platform to evaluate the impacts andperformance of DER

b) Testing and evaluation of various technologies Suchas: Demand Response , PV and Storage.

c) Development of new control approaches for stableand flexible operation of DERs

Provision of Power System Support Services From Distributed Energy Resources

PhD Student: Ismail Ibrahim ([email protected])Supervisor: Terence O’Donnell ([email protected])

University College Dublin/Electrical Engineering

REAL-TIME SIMULATION, HARDWARE IN THE LOOP PLATFORM

CONCLUSIONS• The HIL test platform had been developed.• Aggregated Demand Response test results (Fig.2) shows that current demand response controller causes

instability.• Distributed Battery Storage test results (Fig.3) shows that droop control provides stable operation but

fails to improve the system RoCoF.• VSM controlled Demand response and Battery storage could provide solution for RoCoF improvement.


Objectives• To provide grid support such as synthetic inertia

and fast frequency response from DER

• To provide flexibility and stability for operation ofDER

VIRTUAL SYNCHRONOUS MACHINEVirtual Synchronous Machine (VSM) could be one of thecontrol approach for stable and flexible operation of DERs.The DERs are controlled to mimic the synchronousgenerator to provide inertial and droop response.

Strategy:is used to provide virtual inertia, according to the Rate

of Change of Frequency (RoCoF);is used to provide droop, according to the frequency

deviation from the nominal value ;is the power output from the renewable energy;

is the power output from the energy storage;P is the power output from the DES to the grid= + ( − )= +

• The network contains three feeders with 330houses, 6350 nodes and three phases, fourwire configuration distribution cables.

• The loads are modelled as per therecommendations by the IEEE Task Force onLoad Representation for DynamicPerformance.

RESULTS

• Aggregated Demand Response (This work was presented in CIGRE Dublin Symposium- May 2017)

• Distributed Battery Storage (This work was presented in IEEE APPEEC Conference- Bengaluru, Nov 2017)

Fig. 1. An ENWL distribution grid in the Manchester area

Fig. 2. System Frequency Response for aggregate Demand Response

• Hardware in the Loop (HIL) test was performed forthe distribution system in fig.1 with single hardwaredemand response controller and the controllerresponse is fed to 48 controlled loads. A frequencyperturbation is created by disconnecting 10% oftotal generation

• Fig. 2 shows the system frequency response fordistribution system for three cases, where there isno demand response, where the switching of allcontrollers is synchronised with the single hardwarecontroller (synchronised switching), and where theresponse from controllers is time delayed withrespect to the hardware controller (delayed response).

• Hardware in the Loop (HIL) test was performed for thedistribution system in fig.1 with single storage deviceand the response is fed to 48 controlled loads. Afrequency perturbation is created by disconnecting10% of total generation

• Fig. 3 shows the system frequency response fordistribution system for four cases, where there is noenergy storage, 16,32,48 houses with Battery Storagein Droop Control Mode.Fig. 3. System Frequency Response for

Distributed Battery Storage

adaptive liquid cooling methods in microchannels 11-16 web.pdffor modelling purpose of transmission...

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