EAC4027-N: Renewable Energy Conversion Systems Design Report

This report investigates the design and operation of photovoltaic (PV) and wind energy systems through experiments and computer simulations using PVsyst software. The experimental section covers MPP tracking in PV systems with and without shading, determination of inverter efficiency, and analysis of a Doubly Fed Induction Generator (DFIG) wind turbine, including the influence of mechanical speed, rotor frequency, and rotor current on generator voltage and stator frequency. The computer-aided design part focuses on designing a grid-connected PV system using PVsyst, detailing the selection of PV modules, inverters, and system performance analysis. The report includes detailed figures, data, and analysis of the experimental results and simulation outcomes, providing a comprehensive overview of renewable energy conversion systems.

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”.