Renewable Energy Conversion Systems: EAC4027-N

This report covers the topic of Renewable Energy Conversion Systems submitted by XYZ under the supervision of Dr.XYZ. It covers topics like Photo voltaic, Wind Turbine, RES integration issues, Experiment on Photovoltaic, Experiment on Wind( DFIG), Computer aided design part and more.

Renewable Energy Conversion Systems:
EAC4027-N
Submitted report
B.tech
logo
Submitted by
XYZ
(Student Id: XXXXXXXX)
Under the Supervision of
Dr.XYZ
Department of Electrical Engineering
College name
December 2018

Table of Contents
1. Introduction......................................................................................................................................4
2. Renewable Energy Sources (RES).....................................................................................................4
2.1. Photo voltaic..............................................................................................................................5
2.2. Wind Turbine.............................................................................................................................7
3. RES integration issues.......................................................................................................................9
4. Experiment on Photovoltaic...........................................................................................................11
4.1. MPP Tracking without shading................................................................................................11
4.2. MPP Tracking with shading......................................................................................................12
4.3. Inverter Efficiency Factor.........................................................................................................14
5. Experiment on Wind( DFIG)............................................................................................................15
5.1. Influence of Mechanical speed on generator voltage..............................................................15
5.2. Influence of variable rotor frequency on stator frequency......................................................16
5.3. Influence of rotor current on stator voltage...........................................................................16
6. Computer aided design part...........................................................................................................16
7. References......................................................................................................................................26

List of Figures
Figure 1 PV output at Victoria University Melbourne..........................................................................4
Figure 2 WT output at Victoria University Melbourne.........................................................................5
Figure 3 Standalone solar system.........................................................................................................7
Figure 4 Direct in line induction generator...........................................................................................8
Figure 5 Double fed induction generator.............................................................................................9
Figure 6 Typical 75 W PV module test condition................................................................................12
Figure 7 Shading condition.................................................................................................................13
Figure 8 Partially shaded output.........................................................................................................13
Figure 9 MPP without shading............................................................................................................14
Figure 10 DFIG control........................................................................................................................16
Figure 11 PVsyst desing......................................................................................................................17
Figure 12 PVsyst desing......................................................................................................................18
Figure 13 PVsyst solar data.................................................................................................................19
Figure 14 PVsyst tracking....................................................................................................................20
Figure 15 PVsyst Horizon line.............................................................................................................21
Figure 16 PV and inverter sizing.........................................................................................................22
Figure 17 PVsyst shading....................................................................................................................23
Figure 18 PVsyst PV and inverter sizing..............................................................................................24
Figure 19 Module...............................................................................................................................25
Figure 20 Simulation...........................................................................................................................26
Figure 21 Output................................................................................................................................27

1. Introduction
The increase in population and the pollution is the biggest issue that world is facing, the use
of conventional fuels is the key problem of pollution around the world. Majority of countries
ae moving to the non pollutant energy sources. The use of solar is on the top, while the use of
wind is also increasing day by day. The sun is the main foundation of energy for the
photovoltaic which converts heat energy into electricity. Wind is use to drive the rotor of the
wind turbine which converts kinetic energy to electrical energy. Both the sources are
subjected to uncertainties due to variation in atmospheric parameters. The actual output from
PV and wind is dependent on the certain conditions, that is known as capacity factor. The
capacity factor of WT is around 20-40% while in case of PV its around 12-15%. However it
always dependent on the location, wind speed, solar irradiation and temperature of that
particular location [2]. The solar power available during day time and peak during afternoon
periods while the wind power is available most of the time specially during night due to high
wind velocity [7]. tIntpractice,tthis impliest thet possibility toftforming tathybrid
tpowertsystemt totmediatetthetpowertimbalances, withtthet PVtcells
tprovidingtelectricitytduring the tday tand twindtprovidingt electricitytat night in
wintertandtsummertseasons.
2. Renewable Energy Sources (RES)
In considerationtoftthetbehaviourtoftthetrenewabletenergytresources,tsolar and wind actually
havetcomplementarytbehaviour.tHybridtsystemtwithtthetcombination of PV and wind
renewabletsourcestthereforetensurestthetenhancementtoftthetoverall system reliability,
reductiontoftstoragetsizetrequirement,tandtcontributionttotlowertgenerationtcostt[9].t
Figure 1 PV output at Victoria University Melbourne

Figure 2 WT output at Victoria University Melbourne
2.1. Photo voltaic
ConvertingtsolartenergytintotelectricaltenergytbytPVtinstallationstistthetmost recognized
way to usetsolartenergy.tSincetsolartphotovoltaictcellstaretsemiconductortdevices, they have
a lot
in common withtprocessingtandtproductionttechniquestoftother semiconductor devices such
as computerstandtmemorytchips.tAstittistwelltknown,tthetrequirementstfortpurity and quality
controltoftsemiconductortdevicestaretquitetlarge.tWithttoday'stproduction, which reached a
largetscale,tthetwholetindustrytproductiontoftsolartcellsthastbeentdevelopedtand, due to low
productiontcost,tittistmostlytlocatedtintthetFartEast.tPhotovoltaictcellstproduced by the
majoritytofttoday’st most larget producerst aretmainly tmade toft crystallinet silicon as
semiconductort material.tSolartphotovoltaictmodules,twhichtareta result of combination of
photovoltaic cellsttotincreasettheirtpower,tarethighlytreliable,tdurabletandtlow noise devices
totproducetelectricity.tThetfueltfortthetphotovoltaictcelltistfree.tThetsuntis the only resource
that is requiredtfor tthetoperationtoftPVtsystems,tandtitstenergytistalmosttinexhaustible. A
typical photovoltaic cell efficiencytistaboutt15%,twhichtmeanstittcantconvert 1/6 of solar
energy into electricity.tPhotovoltaictsystemstproducetnotnoise,ttheretaretno moving parts and
they dotnottemittpollutantstintotthetenvironment.tTakingtintotaccounttthe energy consumed
in the productiontoftphotovoltaictcells,ttheytproducetseveralttenstofttimestless carbon
dioxide per
unittintrelationttotthetenergytproducedtfromtfossiltfuelttechnologies.tPhotovoltaic cell has
lifetime oftmoretthantthirtytyearstandtistonetoftthetmosttreliable semiconductor products.
Most solartcellstaretproducedtfromtsilicon,twhichtis non‐toxic and is foundtin abundance in
thetearth's crust. The increase in population and the pollution is the biggest issue that world is
facing, the use of conventional fuels is the key problem of pollution around the world.
Majority of countries ae moving to the RES. The use of solar is on the top, while the use of
wind is also increasing day by day. The sun is the main source of energy for the photovoltaic
which converts heat energy into electricity. Wind is use to drive the rotor of the WT which
converts kinetic energy to electrical energy. Both the sources are subjected to uncertainties
due to variation in atmospheric parameters. The word „photovoltaic“
consiststofttwotwords:tphoto,tatgreek word for light, and voltaic, which
definestthetmeasurementtvaluetbytwhichtthetactivitytoftthe electric field is expressed, i.e.
thetdifferencetoftpotentials.tPhotovoltaictsystemstuse cells to converttsunlight into
electricity. Convertingtsolartenergytintotelectricitytintatphotovoltaictinstallationtis the most
known way oftusingtsolartenergy.tThetlightthastatdualtcharactertaccording to quantum
physics.tLighttistatparticletandtittistatwave.tThetparticlestoftlighttare called photons. Photons

aretmasslesstparticles,tmovingtattlighttspeed.tThetenergytoftthetphoton depends on its
wavelengthtandtthetfrequency,tandtwetcantcalculatetit by the Einstein's law, which is:
E=hv
“E” is known as the photon energy
“h” is called the planck’s constant=6.626 x10-34
v- photon frequency
Part of thetphotontenergytistconsumedtfortthetelectrontgettingtfreetfrom the influence of the
atomtwhichtittistattachedtto,tandtthetremainingtenergytistconverted into kinetic energy of a
nowtfreetelectron.tFreetelectronstobtainedtbytthe photoelectric effect are also called
photoelectrons.tThetenergytrequiredttotreleasetatvalencetelectrontfromtthe impact of an atom
is calledtat„worktout“tWi,tandtittdependstontthettypetoftmaterialtintwhichtthetphotoelectric
effect hastoccurred.tThetequationtthattdescribestthistprocesstistastfollows:
hv=W i+ W kin
W kin- kinetic energy of emitted electrons
W i- workout
hv- photon energy
Functioning of photo voltaic cell
η= Pel
Psol
= U . I
E . A
Pel- Electrical output power
Psol- Radiation power
U is the effective output voltage
I stands for effective electricity output
E stands for specific radiation power
A is the Area of PV
Energy conversiontefficiencytofta solar photovoltaic cell (η "ETA") is the percentage of
energy
from thetincidenttlighttthattactuallytendstuptastelectricity.tThististcalculatedtattthetpoint of
maximum power,tPm,tdividedtbytthetinputtlighttirradiationt(E,tintW/m2), all under standard
test conditions (STC) andtthetsurfacetoftphotovoltaictsolartcells (AC in m2).

η= Pm
E × Ac
Thetmosttcommontmaterialtfortthetproductiontoftsolartcellstistsilicon.tSilicon is obtained
from sand and is one of the most common elementstintthetearth'stcrust,tsottheretistnotlimittto
the availabilitytoftrawtmaterials.
 Monocrystalline
 polycrystalline,
 Bar‐crystalline silicon,
 thin‐film technology.
Cells madetfromtcrystaltsilicont(Si),taretmadetoftatthinlytsliced piece (wafer), a crystal of
silicon (monocrystalline) tor ta twhole tblockt oft silicont crystalst (multicrystalline);ttheir
efficiencytrangestbetweent12% and 19%.
Figure 3 Standalone solar system
2.2. Wind Turbine
AccordingttotEWEAtestimation,t12%toftthetpowertdemandtoftthetwhole world will be
providedtbytwintgenerationtfortyeart2020.tAttpresent,tthettotaltinstallation capacity of wind
powertgeneratorsthastreachedt31128tMWtandtthetgenerationtcosttpertkilowatt-hour has been
reducedtfromt38tcentstint1982ttot4tcentstint2001.tThetwindtpowertgeneratorstcan be
installedtbytgridtconnectiontwithtthetelectricaltnetwork.tFortthetoffshoretislandstor remote
areatwhichtcannottbetreachedtbytbulktpowertsystemtnetworks,tthetwind power generators
cantbetoperated-standalone ortintegratedtwithtdieseltgeneratorstandtphotovoltaic (PV) panels
totservetthetpowertdemandtThetutilizationtoftwindtenergytmay be an attractive alternative in
placestsuchtastoffshoretislands,twheretfueltistusuallytexpensivetandtwindtregimestare
particularly favourable. The windtpowertistmainlytgeneratedtbytrotatingtthetbladetof wind
turbinestviatthetairflowttotconverttthetwindtenergytintotelectricaltenergy.tThe wind power
generationtcantbetassumedttotbetvariedtwithtthetwindtspeed.tDispersedtpower generation
systems aretexpectedtastimportanttelectrictpowertsupplytsystemstfortthetnext generation.
Wind power generationtsystemt(WPGS)tistwidelytbeingtintroducedtintthetworldwide power
utilities. ThetWPGStoutputtpowertfluctuatestduettotwindtspeed variations. Hence, if a large
number oftwindtpowertgeneratorstaretconnectedttotthetgridtsystem,ttheir output can cause
serious powertqualitytproblems,tthattis,tfrequencytandtvoltagetfluctuationstmaythappen.tIn
order to solve thesetproblems,tthetsmoothingtcontroltoftwindtpowertgeneratortoutput is very
important.tIntaddition,tSuperconductingtMagnettEnergytStoraget(SMES)tistsurelytonetoftthe
tkeyttechnologiesttotovercometthese fluctuations.

Energy source - Solartradiationtdifferentiallytabsorbedtbytearthtsurfacetconverted through
convective processes duettottemperaturetdifferencestairtmotion.tFundamental Equation of
Wind PowertWindtPower depends on:
• Air (volume)
• velocity of wind
• Density of air, which is flowing through the surface of flux
Energy definition :
K . E= 1
2 m v2
Where m= dm
dt
Fluid mechanics gives mass flow rate
−dm
dt =ρAV
So p= 1
2 ρA V 3
WT usage the wind’s kinetic energy to produce electrical energy which can be utilized in
residential and commercial purposes. Each wind turbinestcantbetusedttotgeneratetelectricity
on a small scalet–ttotpowertatsinglethome,tfortexample.tAtlargetnumbertof WT grouped
together, sometimes known tastatwind tfarm tor twindt park,t cantgeneratetelectricity on a
much larger scale.tAtwindtturbinetworkstliketathigh-techtversiontoftantold-
fashionedtwindmill. The wind blows on thet angled bladest of tthet rotor, tcausing tit ttot
spin,tconverting some of the wind’s kinetict energy intot mechanical tenergy.tSensorst
intthetturbinetdetect how strongly the windt istblowingtand tfrom twhich
tdirection.tThetrotortautomaticallytturnsttotfacetthe wind, and automaticallyt brakes tin
tdangerouslythightwindsttotprotecttthetturbine from damage. A shaft and
tgearboxtconnecttthetrotorttotatgeneratort(1),tsotwhentthetrotortspins, so does the generator.
Thetgeneratortusestantelectromagnetictfieldttotconverttthistmechanical energy into electrical
energy.tThetelectricaltenergytfromtthetgeneratortisttransmittedtalongtcables to a substation
(2). Here, thetelectricaltenergytgeneratedtbytalltthetturbinestintthetwindtfarm is combined
and converted to athightvoltage.tThetnationaltgridtusesthightvoltagesttottransmittelectricity
efficientlytthroughtthetpowertlinest(3)ttotthethomestandtbusinessestthat need it (4). Here,
otherttransformerstreducetthetvoltagetback down to a usable level.
Figure 4 Direct in line induction generator

Recenttdevelopmentstseekttotavoidtmosttdisadvantagestoftdirect-in-line converter based
ASGs. Fig.4 tshowstantalternativetASGtconcepttthattconsiststoftatdoublytfedtinduction
generator (DFIG)twithtatfour-quadranttac-to-ac converter basedtontinsulated gate bipolar
transistors (IGBTs)tconnectedttotthetrotor windings. Comparedttotdirect-in-line systems, this
DFIGtofferstthetfollowing advantages:
 Reduced invertertcost,tbecausetinvertertratingtisttypicallyt25% of total system
power, while thetspeedtrangetoftthetASGtist33% around thetsynchronous speed.
 Reduced cost oftthetinvertertfilterstandtEMItfilters,tbecuase filters are rated for 0.25
p.u.ttotaltsystemtpower,tandtinvertertharmonicstrepresentta smaller fraction of total
system harmonics.
 Improvedtsystemtefficiency,
 IGBTtinverters.tApproximatelyt2-3%tefficiencytimprovement can be obtained.
 Power-factor controltcantbetimplementedtattlowertcost,tbecause the DFIG system
(four-quadranttconvertertandtinductiontmachine)tbasicallytoperatestsimilar to a
synchronous generator.
Thetconverterthasttotprovidetonlytexcitation energy
Figure 5 Double fed induction generator
3. RES integration issues
The uncertaintytandtvariabilitytoftwindtandtsolartgenerationtcan pose challenges for grid
operators.tVariabilitytintgenerationtsourcestcantrequiretadditionaltactionstto balance the
system[3]. Greatertflexibilitytintthe system maytbe needed to accommodate supply-
sidetvariabilitytand the relationshiptto generationtlevels andtloads. Sometimestwind
generationtwill increasetas load increases,tbut in casestin which renewable generation
increasestwhentloadtlevelstfallt(ortvicetversa),tadditionaltactionstto balance the system are
needed.tSystemtoperatorstneedttotensuretthattthey havetsufficienttresources to accommodate
significant up or downtrampstintwindtgenerationttotmaintaintsystem balance. Another
challengetoccurstwhentwindtortsolartgenerationtis available duringtlow load levels;tin some
cases,tconventionaltgeneratorstmaytneedtto turn downttottheir minimum generation levels.
Figuretprovidestantexampletoftthetflexibilitytneededtforta high penetration of wind energy.
Utilizingtalltoftthetwindtenergytwould require conventional generators to meet the nettload,
whichtistdefinedtastthetdemandtminustthetwindtenergy[4].tThetgraphtshowstthe load and net
loadtfortatsampletweek.tTheretaretperiodstwhentthetnettload changes, or ramps, more

quickly thantthetloadtalone.tAlso,tthetremainingtgenerators must be operated at a
lowtoutputtlevel (sometimestcalledt“turndown”)tattnighttwhenttheretistatlottof wind power.
In contrastttotwind, solar generation is often more coincidenttwithtload.tHowever, in regions
with eveningtloadtpeaks,tlosstoftsolartgenerationtattsunsettcantexacerbatetramping needs to
meet the evening demand. Some of the event analysis in the Western Wind and Solar
Integration Study Phase 2 (WWSIS-2),has proved that RES integration upto 33 % the off
periods such as (sunrise and sunset) are dominate the ramping requirements [5]. Because it is
possible to plan for thistaspecttoftsolartpowertvariability,tincreasedtoperatingtreserve levels
need to focus onlytontthetunpredictabletcloudtvariability,twhichtis reduced by aggregation of
geographicallytdiversetsolartpowertplantst(astwelltastaggregationtwithtwind and load
variability).tAstatresult,tWWSIS-2tfoundtthattoperatingtreserves were lower for the high
solar scenariot(25%tsolar)tthantthe high wind scenario (25%twind) (Lew 2013)[6].
Solartpowertthat is connectedttotthetdistributiontsystemthastsimilar impacts as that
connectedttotthetbulktpowertsystem;thowever,ttheretaretdifferences. Transmission-level
solar powertplantstprovidetreal-timetgenerationtdatattotpowertsystemtoperators; whereas
distributedtsolartpowertplantstdotnot.tThattmakestittdifficult for atsystemtoperator to know
whethertantincreasetintnettloadtistbecausetoftincreasingtdemandtor decreasing solar
generation.tAnothertdifferencetistthetwaytthetsolartgenerationtreactsttotfaultstor voltage
excursions.tTransmission-leveltsolartpowertcantbetdesignedtto maintain synchronization
duringtfaultstoftlimitedtduration.tHowever,tcurrenttstandardst(Institute of Electrical and
ElectronicstEngineerst1547)trequiretdistribution-leveltsolarttotquicklytdisconnect during
thesetevents.tThetresulttistthattittmaytbetmoretdifficultttotavoidtor recover from some system
disturbances.
A varietytoftoptionstaretavailablettotaddresstintegrationtchallenges. Key considerations
in selecting methodsttotaddresstthetvariabilitytandtuncertaintytoftthe renewable generation
are thetcost-effectivenesstoftthetmethodtandtthetcharacteristicstoftthe existing grid system.
Grid infrastructure,toperationaltpractices,tthetgenerationtfleet,tand regulatory structure all
impact the typestoftsolutionstthattaretmostteconomictandtviable.tGenerally,tsystems need
additional flexibility to be ablettotaccommodatetthetadditionaltvariabilitytoftrenewables.
Flexibility can be achievedtthroughtinstitutionaltchanges,toperationaltpractices,tstorage,
demand-side flexibility, flexible generators,tandtothertmechanisms.tSeveraltoftthese are
discussed below, with
antemphasistonttheirtbenefits,twherettheythavetbeentimplemented,tand effectiveness in
addressing integrationtchallenges.tManythavetbeentadoptedtbecausetthey reduce power
systemtcoststindependenttoftvariable renewable generation.
Wind andtsolartpowertforecastingtcanthelptreducetthetuncertaintytof variable renewable
generation. Thetusetoftforecaststhelpstgridtoperatorstmoretefficiently commit or de-commit
generators to accommodatetchangestintwindtandtsolartgenerationtand prepare for extreme
eventstintwhichtrenewabletgenerationtistunusuallythightortlow.tForecaststcan help reduce
the amounttoftoperatingtreservestneededtfortthetsystem,treducingtcoststof balancing the
system. CaliforniatIndependenttSystemtOperatort(CAISO)twastthetfirsttto implement
forecasting in 2004,tandttodaytittistwelltestablishedtandtusedtintalltindependenttsystem
operators (ISOs). In thetWesterntUnitedtStates,tapproximatelytatdozentbalancing authority
areas, which encompass 80% oftwindtcapacity,tusetforecasting (WGA 2012).
Improvementsthavetbeentmadetintrecenttyearsttowardtreducingtmean average forecast errors.
Fortexample,tXceltEnergytreducedtitstmeantaverageterrorstfromt15.7%ttot12.2% between

2009 and 2010,tresultingtintatsavingstoft$2.5tmilliont(WGAt2012). Today, forecast errors
typically rangetfromt3%ttot6%toftratedtcapacitytonethourtaheadtand 6% to 8% a day ahead
on atregionaltbasist(astopposedttotfortatsingletplant).tIntcomparison,terrors for forecasting
load typicallytrangetfromt1%ttot3%tday-aheadt(Lewtettal.t2011). Day ahead forecast is key
part for the scheduling of the solar and wind to make unit commitment and the efficiency
with cost for the demandtresponse,tortothertmitigatingtoptiontand thus drive reliability.
Solartforecastingtistemerging,talthoughtnottwidelytused today. Clouds are the primary
cause oftvariabilitytfortsolartgeneration,tasidetfromtthetpredictabletchangestduring the
course of thetdaytandtthroughouttthetyear.tThetabilityttotaccuratelytforecasttsolar power
depends on the charactertoftcloudtcover,tincludingtthetamounttoftwatertorticetin clouds and
aerosols[7]. To predict
impactstduringtthetnexttfewthours,tsatellitetimagestcantbetusedttotassess the direction and
speedtoftapproachingtclouds.tFortlongertperiods,tweathertmodelstcantbe used to determine
howtcloudstmaytformtand change (WGA, 2012).
Reservet managementtpracticest cant betmodifiedttothelptaddresstthetvariability of wind
and solartpower.tPracticestthattreducetoveralltreservetrequirementstcantlead to substantial
cost savings.tPotentialttoolstfortmanagingtvariabilitytincludetplacingtlimitston wind energy
ramps totreducetthetneedtfortreservestandtenabletvariabletrenewablesttotprovide reserves or
othertancillary services.
Limitingtuptrampstistanothertpotentialttooltfortmanagingtvariability.tBecause reserve levels
aretsetttotaddresstrelativelytlow-probability,tlargetchangestin wind output, modest limits
ontwindtgenerationtcantsignificantlytreducetthetneedtfortbalancingtreserves, yielding cost
savings. Rampteventstthattaffecttplantstacrosstatbalancingtauthoritytareatresult from large-
scale weatherteventstthattcantbetmoreteasilytpredictedtthantlocaltweathertevents. By
imposingtrampingtlimitstontwindtgeneratorstwhentlarge-scaletweathertevents are forecasted,
balancing reservetrequirementstmaytbetsignificantlytreduced.tRamptrate controls are a
relativelytlow-costttooltfortminimizingtsystemtimpacts;tthetprimarytcoststare associated with
the curtailedtgenerationtandtthetcommunicationstandtcontroltequipment.tRamp rate controls
on renewabletgeneratorsthavetbeentimplementedtintthetElectrictReliabilitytCouncil of Texas
(ERCOT),tIreland,tGermany,tandtHawaii (WGA 2012).
Another optiontisttotdesigntincentivestsotthattwindtandtsolartpower plants can provide
regulation,tinertia,tortothertancillarytservicestiftittisteconomicalttotdotso. Wind and solar
plants are especially goodtattprovidingtdowntreservestattverytlowtcost.tThe provision of
ancillary services uptreservestfromtwindtortsolartpowertplantstwilltnecessarilytreduce energy
production—as it does fortconventionaltplantstthattprovidetthosetservices—but incentives
such as thetproductionttaxtcredittdoestnottrecognizetthetpotential value of wind-provided
ancillary services
4. Experiment on Photovoltaic
4.1. MPP Tracking without shading
Maximum Power Point Tracking,tfrequentlytreferredttotastMPPT,tistan electronic system
that operatestthetPhotovoltaict(PV)tmodulestintatmannertthattallowstthetmodules to produce
all thetpowerttheytaretcapabletof.tMPPTtistnottatmechanicalttracking system that “physically
moves” thetmodulesttotmaketthemtpointtmoretdirectlytattthetsun.tMPPT is a completely
electronic system that contrasts the electrical working point of the units so that the modules
are able to deliver maximumtavailabletpower.
Additional powertharvestedtfromtthetmodulestistthentmadetavailabletas increased battery
charge current.tMPPTtcantbetusedtintconjunctiontwithtatmechanicalttracking system, but the

two systemstaretcompletelytdifferent.tTotunderstandthowtMPPTtworks, let’s first consider
the operationtoftatconventionalt(non-MPPT)tchargetcontroller[8]. When a conventional
controller is chargingtatdischargedtbattery,tittsimplytconnectstthetmodulestdirectly to the
battery.tThistforcestthetmodulesttotoperatetat batterytvoltage,ttypically not the
idealtoperating voltage at which thetmodulestaretablettotproducettheirtmaximumtavailable
power. The PVtModule Power/Voltage/Current chart demonstrations the old-style
Current/Voltage curve
fortattypicalt75Wtmoduletattstandardttesttconditionstoft25°Ctcellttemperature and
1000W/m2toftinsolation.tThistgraphtalsotshowstPVtmoduletpowertdeliveredtvs module
voltage. Fortthetexampletshown,tthetconventionaltcontrollertsimplytconnects the module to
thetbatterytandtthereforetforcestthetmodulettotoperatetatt12V.tBy forcing the 75W module to
operatetatt12Vtthetconventionaltcontrollertartificiallytlimitstpowertproduction to 53W.
Rather thantsimplytconnectingtthetmodulettotthetbattery,tthetpatentedtMPPT system in
aSolar Boost™ chargetcontrollertcalculatestthetvoltagetattwhichtthetmoduletis able to
produce maximumtpower[9].tIntthistexampletthetmaximumtpowertvoltagetoftthe module
(VMP) is 17V.tThetMPPTtsystemtthentoperatestthetmodulestatt17Vttotextracttthe full 75W,
regardless oftpresenttbatterytvoltage.tAthightefficiencytDC-to-DCtpowertconverter converts
the 17V moduletvoltagetattthetcontrollertinputttotbatterytvoltagetattthetoutput.tIftthetwhole
system wiringtandtalltwast100%tefficient,tbatterytchargetcurrenttintthistexampletwouldtbe
VMODULEt¸ VBATTERY x IMODULE, or 17V ¸
12Vtxt4.45At=t6.30A.t
A charge currenttincreasetoft1.85Atort42%twouldtbetachievedtbytharvestingtmodule power
thattwouldthavetbeentlefttbehindtbytatconventionaltcontrollertandtturning it into useable
chargetcurrent.tBut,tnothingtist100%tefficienttandtactualtchargetcurrent increase will be
somewhattlowertastsometpowertistlosttintwiring,tfuses,tcircuittbreakers, and in the Solar
Figure 6 Typical 75 W PV module test condition
Actual charget current increaset varies witht operating conditions.t As shown above, the
greater the differencetbetweentPVtmoduletmaximumtpowertvoltagetVMP and battery
voltage, the greatertthetchargetcurrenttincreasetwilltbe[10].tCoolertPVtmodule cell
temperatures tend to producet highert VMPt andt therefore tgreatert charge tcurrentt increase.
tThistis because VMP and available tpowert increaset ast module tcellt temperature decreases
tas tshownt in the PV Module Temperature tPerformance tgraph. tModules twitht at 25°Ct
VMPt ratingt higher tthan t17V will also ttendt to tproduce tmore tcharge tcurrent tincrease
tbecause tthet difference between actual VMPt andtbattery tvoltaget will tbet greater. tAt
highly tdischarged tbatteryt will also increase charge current since tbatteryt voltage is
tlower,t andt output ttot the battery during MPPT could be thought tof tas tbeing
“constant power”.

4.2. MPP Tracking with shading
The shading is the key obstacle in the solar power generation facility which could not be
avoided completely, byttrees,tchimneys,tsatellitetdishestandtmore.tIntthesetsystemstpartial
shading losses are estimatedttotresulttinta 5%-25% annual energy loss.
Impact of shading on MPP
Shading of anytparttoftPVtarraytwilltreducetitstoutput.tClearly,tthetoutput of any shaded cell
or moduletwilltbetloweredtintcorrelationtwithtthetreductiontintlighttfalling on it. However in
systems withttraditionaltstringtinverters,tunshadedtcellstortmodulestmay also be affected by
thetshade.tFortexample,tiftatsingletmoduletintatserieststringtistpartiallytshaded,tits current
output will betreducedtandtthistmaytdictatetthetoperatingtpointtof all the modules in the
string. Alternately, the shadedtmoduletmaytbetbypassed,tleadingtthistmodulettotstop
producing powertentirelyt(Fig.t7).tIftseveraltmodulestaretshaded,tthetstringtvoltage may be
reduced to atvaluetlowertthantthetinverter’stminimumtoperatingtpoint,tcausing that string to
produce no power.
Figure 7 Shading condition
The low voltage tracking is the key parameter to harvest the energy in efficient way for the
completely or partially shaded PV modules[11].
However, microinverterstneedtrelativelythightvoltages,toftabout 20V, totbe able to
tracktatmodule’stMPP.tThistmeanstthattiftatmodule’stvoltagetdropstbelow this point, the
microinvertertwilltnotttracktitstMPP,trathertittwouldtmaintaintatvoltagethigh enough for it to
continuettotoperate,tbuttattantun-optimizedtpoint.tIntcontrast,tthetSolarEdge power
optimizers startttrackingtMPPtfromtatvoltagetastlowtast5V,tmeaningtthey track a module’s
MPP even undertseveretpartialtshading[12]

Figure 8 Partially shaded output
Table 1 Shading test of PV
4.3. Inverter Efficiency Factor
By efficiency, we are reallytsaying,twhattpercentagetoftthetpowertthattgoes into the inverter
comestouttastusabletACtcurrentt(nothingtistevert100%tefficient,tthere will always be some
lossestintthetsystem).tThistefficiencytfiguretwilltvarytaccordingttothowtmuch power is
utilized when the efficiency is much higher at the time of production of energy
fromtsomethingtjusttovert50%twhentattrickletoftpowertis being used, to something over 90%
whentthetoutputtistapproachingtthetinverterstrated output. An inverter will
usetsometpowertfromtyourtbatteriesteventwhentyoutaretnot drawing any AC powertfrom it.
This results intthetlowtefficienciestat low power levels[13].
Figure 9 MPP without shading
A 3kW inverter may characteristically attraction about 20 watts after your batteries at the
time where there is not Alternating current power is available. A small 200W inverter may on

the other hand only draw 25 watts from the battery to give an AC-output of 20 watts,
subsequent intantefficiency of 80%[14].
Bigger inverters willtgenerallythavetatfacilitytthattcouldtbetnamed a "Sleep Mode" to
increase overalltefficiency.tThistinvolvestatsensortwithintthetinvertertsensingtiftAC power is
required. Iftnot,tittwillteffectivelytswitchtthetinvertertoff,tcontinuingtto sense if power is
required. This cantusuallytbetadjustedttotensuretthattsimplytswitchingtatsmalltlight on is
sufficient to "turn thetinverterton".tThistdoestoftcoursetmeantthattappliancestcannottbetlefttin
"stand-by" mode, and
ittmaytbetfoundtthattsometappliancestwithttimerst(e.g.twashingtmachine)treach a point in
their cycletwherettheytdotnottdrawtenoughtpowerttotkeeptthetinvertert"switched on", unless
something else, e.g.tatlight,tistontattthetsamettime.tAnothertimportanttfactor involves the
wave formtandtinductivetloadst(i.e.tantappliancetwheretantelectricaltcoiltis involved, which
will includetanythingtwithtatmotor).tAnytwaveformtthattistnottattruetsinetwave (i.e. is a
square, ortmodifiedtsquaretwave)twilltbetlesstefficienttwhentpoweringtinductive loads - the
appliance maytuset20%tmoretpowertthantittwouldtiftusingtatpuretsine wave. Together with
reducing efficiency,tthistextratpowertusagetmaytdamage,tortshortentthetlife of the appliance,
duettotoverheating.
Efficiency of inverter is defined as the how much power from DC is converted into the AC
power losttastheat,tandtalsotsometstand-bytpowertistconsumedtfor keeping the inverter in
poweredtmode.tThetgeneraltefficiency formula is
η= P AC
PDC
wheretPACtistACtpowertoutputtintwattstandtPDCtistDCtpowertinputtintwatts. High quality
sine wavetinverterstaretratedtatt90-95%tefficiency.tLowertqualitytmodifiedtsine wave
inverters are lesstefficientt-t75-85%.tHightfrequencytinverterstaretusuallytmore efficient than
low-frequency.tInvertertefficiencytdepends on inverter load.
5. Experiment on Wind( DFIG)
Doubly-fed electric machines aretbasicallytelectrictmachinestthattaretfedtac currents into
both thetstatortandtthetrotortwindings.tMosttdoubly-fedtelectric machines in industry today
are three-phasetwound-rotortinductiontmachines[15].tAlthoughttheirtprinciplestoftoperation
have been knowntfortdecades,tdoubly-fedtelectrictmachinesthavetonlytrecently entered into
common use.tThististduetalmosttexclusivelyttotthetadventtoftwindtpower technologies for
electricity generation.t As the frequency of rotor varies the stator frequency also changes, two
factor are important for stator frequency one is the mechanical speed of rotor and second is
rotor frequency. Mechanical speed can be controlled by gear box arrangement still perfect
control is not possible while the rotor frequency can be controllable from the converter stage.
Any change in rotor frequency will leads to change in stator frequency. Doubly-
fedtinductiontgeneratorst(DFIGs)taretbytfartthe most widely used type of doubly-fed
electrictmachine,tandtaretonetoftthe most common types of generator used
totproducetelectricitytintwindtturbines[16].tDoubly-fedtinductiontgeneratorsthave a number
of advantagestovertotherttypestoftgeneratorstwhentusedtin wind turbines. The primary

advantage oftdoubly-fedtinductiontgeneratorstwhentused in wind turbines is thattthey allow
the amplitudetandtfrequencytofttheirtoutputtvoltagesttotbetmaintainedtat a constant value, no
matter the speedtoftthetwindtblowingtontthetwindtturbinetrotor.tBecausetof this, doubly-fed
induction generators cantbetdirectlytconnectedttotthetactpowertnetworktand remain
synchronized at allttimestwithtthetactpowertnetwork.tOthertadvantagestincludetthe ability to
control the powertfactort(e.g.,ttotmaintaintthetpowertfactortattunity),twhile keeping the
power electronics devicestintthetwindtturbinetattatmoderatetsize[17].tThistmanualtcovers the
operation of doubly-fedtinductiontgenerators,tastwelltasttheir use in wind turbines. It also
covers the operation oftthree-phasetwound-rotortinductiontmachinestusedtastthree-phase
synchronous machines and doubly-fedtinductiontmotors.tAlthoughtittistpossible to use these
machines by themselves,ttheytaretprimarilytstudiedtastatsteppingtstonetto doubly-fed
induction generators.
5.1. Influence of Mechanical speed on generator voltage
In other words, thetfrequencyt f statoroftthetactvoltagestproducedtattthe stator of a doubly-fed
induction generator istproportionalttotthetspeedtη ∅ f rotortoftthetrotatingtmagnetic field at the
stator.tThetspeedtη ∅ f stator toftthetstatortrotatingtmagnetictfieldtitself depends on the rotor
speed ηrotor (resulting from the mechanical powertattthetrotortshaft)tand the frequency f rotor
oftthetactcurrentstfedtinto the machine rotor[18]. The rotor current of DFIG is controllable by
the dual stage converter stage, still any change in rotor current affect the stator voltage as the
current in the rotor winding changes the flux of rotor and the induced voltage on stator
terminal also get affected. To smoothly control the stator voltage of the DFIG the rotor fed
control from converter must be implemented.
If the rotor oftatdoubly-fedtinductiontgeneratortrotatestintthetopposite direction to the
magnetic fieldtcreatedtintthetrotor,tthetamplitudetandtfrequencytoftthe voltages produced by
the generatortwilltbetlower than during normal singly-fed operation (at the same rotor speed)
[19, 20].
Using doubly-fedtinductiontgeneratorstintwindtturbinestinsteadtoftasynchronous generators
offers thetfollowingtadvantages:t1)tOperationtattvariabletrotortspeedtwhiletthe amplitude and
frequency oftthetgeneratedtvoltagestremaintconstant,t2)tOptimizationtoftthetamounttof
power generated as atfunctiontoftthetwindtavailabletupttotthetnominaltoutputtpower of the
wind turbine generator,t3)tVirtualteliminationtoftsuddentvariationstintthetrotorttorque and
generator output power, 4) Generation of electrical power at lower wind speeds, and 5)
Control of the power factor (e.g., in order to maintain the power factor at unity).

Figure 10 DFIG control
5.2. Influence of variable rotor frequency on stator frequency
As the frequency of rotor varies the stator frequency also changes, two factor are important
for stator frequency one is the mechanical speed of rotor and second is rotor frequency.
Mechanical speed can be controlled by gear box arrangement still perfect control is not
possible while the rotor frequency can be controllable from the converter stage. Any change
in rotor frequency will leads to change in stator frequency.
5.3. Influence of rotor current on stator voltage
The rotor current of DFIG is controllable by the dual stage converter stage, still any change in
rotor current affect the stator voltage as the current in the rotor winding changes the flux of
rotor and the induced voltage on stator terminal also get affected. To smoothly control the
stator voltage of the DFIG the rotor fed control from converter must be implemented.
6. Computer aided design part

Figure 11 PVsyst desing
Figure 12 PVsyst desing

Figure 13 PVsyst solar data

Figure 14 PVsyst tracking

Figure 15 PVsyst Horizon line

Figure 16 PV and inverter sizing

Figure 17 PVsyst shading

Figure 18 PVsyst PV and inverter sizing

Figure 19 Module

Figure 20 Simulation

Figure 21 Output
The full report is attached below designed using PVsyst utilized in evolution mode.

Ev
a
lu
a
tio
n
PVSYST V5.74 15/12/18 Page 1/3
Grid-Connected System: Simulation parameters
Project :
Geographical Site Melbourne Country Australia
Situation Latitude 37.5°S Longitude 144.6°E
Time defined as Legal Time Time zone UT+10 Altitude 38 m
Albedo 0.20
Meteo data : Melbourne, Synthetic Hourly data
Simulation variant : New simulation variant
Simulation date 15/12/18 11h11
Simulation parameters
Tracking plane, two axis Minimum Tilt 10° Maximum Tilt 80°
Rotation Limitations Minimum Azimuth -80° Maximum Azimuth 80°
Horizon Free Horizon
Near Shadings No Shadings
PV Array Characteristics
PV module Si-poly Model VSPS-310-72-A
Manufacturer Voltec Solar
Number of PV modules In series 1 modules In parallel 1 strings
Total number of PV modules Nb. modules 1 Unit Nom. Power 310 Wp
Array global power Nominal (STC) 310 Wp At operating cond. 282 Wp (50°C)
Array operating characteristics (50°C) U mpp 34 V I mpp 8.3 A
Total area Module area 2.0 m² Cell area 1.8 m²
Inverter Model YC500-SAA/EU
Manufacturer APS
Characteristics Operating Voltage 22-45 V Unit Nom. Power 0.50 kW AC
PV Array loss factors
Thermal Loss factor Uc (const) 20.0 W/m²K Uv (wind) 0.0 W/m²K / m/s
=> Nominal Oper. Coll. Temp. (G=800 W/m², Tamb=20°C, Wind=1 m/s.) NOCT 56 °C
Wiring Ohmic Loss Global array res. 70 mOhm Loss Fraction 1.5 % at STC
Module Quality Loss Loss Fraction 0.1 %
Module Mismatch Losses Loss Fraction 2.0 % at MPP
Incidence effect, ASHRAE parametrization IAM = 1 - bo (1/cos i - 1) bo Parameter 0.05

User's needs : Unlimited load (grid)

PVSYST V5.74 15/12/18 Page 2/3
Project :
Simulation variant : New simulation variant
Main system parameters System type Grid-Connected
PV Field Orientation Tracking two axis
PV modules Model VSPS-310-72-A Pnom 310 Wp
PV Array Nb. of modules 1 Pnom total 310 Wp
Inverter Model YC500-SAA/EU Pnom 500 W ac
User's needs Unlimited load (grid)
Main simulation
System Production Produced Energy 543 kWh/year Specific prod. 1753 kWh/kWp/year
Performance Ratio PR 80.7 %
GlobHor T Amb GlobInc GlobEff EArray E_Grid EffArrR EffSysR
kWh/m² °C kWh/m² kWh/m² kWh kWh % %
January 214.9 19.07 280.1 275.9 71.97 68.32 12.94 12.29
February 167.3 19.32 226.9 223.7 58.54 55.51 13.00 12.32
M arch 136.1 17.79 190.6 187.5 49.83 47.13 13.17 12.45
April 95.6 14.80 155.1 152.8 41.37 39.05 13.44 12.69
M ay 64.6 12.23 104.4 102.6 28.15 26.39 13.58 12.73
June 57.4 9.86 114.6 113.0 31.37 29.54 13.79 12.99
July 60.8 8.89 110.2 108.6 30.33 28.51 13.86 13.03
August 81.4 10.05 140.1 138.1 37.90 35.72 13.62 12.84
September 119.4 10.94 174.1 171.3 47.29 44.75 13.69 12.95
O ctober 165.8 13.32 221.2 217.7 58.86 55.78 13.40 12.70
N ovember 171.9 14.82 217.6 213.9 57.44 54.32 13.30 12.58
D ecember 197.1 17.29 237.3 232.8 61.79 58.47 13.12 12.42
Year 1532.3 14.00 2172.3 2137.7 574.86 543.49 13.33 12.60
Le gends: GlobHor Horizontal global irradiation EArray Effective energy at the output
of T Amb Ambient Temperature E_Grid Energy injected into grid
GlobInc Global incident in coll. plane EffArrR Effic. Eout array / rough area
GlobEff Effective Global, corr. for IAM and shadings EffSysR Effic. Eout system / rough
area
the array

Evalua
tio
n
PVSYST V5.74 15/12/18 P
aMain system parameters System type Grid-Connected
PV Field Orientation Tracking two axis
PV modules Model VSPS-310-72-A Pnom 310 Wp
PV Array Nb. of modules 1 Pnom total 310 Wp
Inverter Model YC500-SAA/EU Pnom 500 W
ac User's needs Unlimited load (grid)
Loss diagram over the
whole year
1532 kWh/m² Horizontal global irradiation
+41.8% Global
incident in coll. pl ane
-1.6% IAM factor on global
2138 kWh/m² * 2 m² coll. Effective irradiance on collectors
efficiency at STC = 15.77% PV conversion
669 kWh Array nominal energy (at STC effic.)
-3.2% PV loss due
to irradiance level
-8.2% PV loss
due to t emperat ure
-0.1% Module quality loss
-2.2% Module array mismatch loss
-1.2% Ohmic wiring loss
575 kWh Array virtual energy at MPP
-5.5% Inverter Loss during operation (efficiency)
0.0% Inverter Loss over
nominal inv. power
-0.0% Inverter Loss due
to power t hreshold
0.0% Inverter Loss over
nominal inv. voltage
0.0% Inverter Loss due to
voltage t hreshold
543 kWh Available Energy at Inverter Output
543 kWh Energy injected into grid

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