Economic analysis of large-scale wind energy conversion systems in central anatolian Turkey

25 Pages·2012·0.77 MB·English

Economic analysis of large-scale wind
energy conversion systems in central anatolian Turkey 131
Economic analysis of large-scale wind energy conversion systems in
07
central anatolian Turkey
Economic analysis of large-scale wind energy Mustafa Serdar GENÇ
conversion systems in central anatolian Turkey
MustafaSerdarGENÇ
ErciyesÜniversitesi,MühendislikFakültesi,EnerjiSistemleriMühendisligˇiBölümü,
38039,Kayseri
Turkey
1. Introduction
A political, economical and technological development is influenced by social events in all
world. Increasingofindustrialproductionandraisingcompetitivenessispossiblebydevel-
opmentoftechnology.Countrieswhichfailtodevelopatechnologywillbedifficulttosurvive
in the new world order and they will take place in the class of very populated, poor coun-
tries whose revenues do not increase. Today, the developing countries make research their
ownenergysources,particularlyrenewableandcleanenergysourcesanddevelopstheirown
technologiesaboutenergyconversionsystemsbecauseofdifficultiesonenergyinalloverthe
world.
Not only the converting most efficiently an energy source into useable energy but also it is
extremely important that this source is clean and sustainable energy. Clean and renewable
energiesobtainingfromsunlight,windorwateraroundtheearthdonotmakeanetcontribu-
tionofcarbondioxidetotheatmosphere. Therefore,theseenergysourcesshouldbeusedto
protectourworld,becauseofglobalwarmingandtheinjuriouseffectsofcarbonemissions.
Pressure and temperature differences occurring in the atmosphere because of solar energy,
and the earth’s rotation, and different forms of the earth’s surface create wind. People has
beenusedthewindforvariouspurposessuchaswindmill,waterpumping,etc.forcenturies.
Not only wind energy can be used as mechanical power but also mechanical energy of the
windthroughageneratorcanbeconvertedintoelectricalenergy.But,interestinwindenergy
have always been tied to oil prices. In the 1970s, oil prices raised suddenly and both this
risingandtheinjuriouseffectsofcarbonemissionspushedpeopletoseekalternative,clean
andrenewableenergysources.
Duetothefactthatwindenergyisafuel-free, inexhaustible, andpollution-freesource, the
roleofwindenergyinelectricitygenerationincreasedintheUnitedStates,AsiaandEurope.
Inthepast25years,useofwindenergyinU.S.A.increased,andthewindenergypricewas80
cents/kWhin1980andthispricedecreasedto4cents/kWhin2002(Kakac,2006). Although
wind produces only about 1.5% of worldwide electricity use, it is growing rapidly, having
doubled in the three years between 2005 and 2009 (World Wind Energy Association, 2010).
Inseveralcountriesithasadistribution, accountingforabout19%ofelectricityproduction
inDenmark,10%inSpainandPortugal,and7%inGermanyandtheRepublicofIrelandin
2008. AndTurkeyisratherunsuccessfulinusingitspotentialandhas1002.35MWinstalled
capacity (Electricity Market Regulatory Authority, 2010). Cumulative variation of installed
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132 Clean Energy Systems and Experiences
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
0 150 300 450 600 750 900 1050 1200
InstalledpowercapacityinTurkey[MW]
Fig.1.CumulativevariationofwindpowerinstalledinTurkey
windpowerinTurkeyisshowninFig. 1(ElectricityMarketRegulatoryAuthority, 2010). It
isexpectedthattheinstalledwindpowercapacityinTurkeywillreachabout3500MWupto
endof2010year.
Windenergypricesarebasedonlocalconditionsandrequiretoanalyzeforeachcountry.The
characteristicsandthedistributionofwindspeedsofasitehavetobeinvestigatedindetailfor
effectiveusingthisenergy.Whenawindenergyconversionsystemwillinstallinasite,many
factorssuchasthewindspeed,windpower,thegeneratortypehavetobetakenintoaccount
andafeasibilitystudymustbedone. Alotofstudiesrelatedtothewindcharacteristicsand
windpowerpotentialhavebeenmadeinmanycountriesworldwidebyresearcherssuchas
Rehman(2004),AhmetShataandHanitsch(2006),Ackeret. al(2007),Bagiorgasetal. (2007),
Bouzidietal.(2009),Nounietal.(2007),ChangandTu(2007),Ngalaaetal.(2007),Zhouetal.
(2010)etc.
InTurkey,alotofstudiesoftheestimationofwindcharacteristicshavebeenachievedbyre-
searchers.Bilgilietal.(2004)andSahinetal.(2005)investigatedthewindpowerpotentialfor
selectedsevendifferentsites(Antakya,Samandag,Karatas,Adana,Yumurtalýk,Dortyoland
Iskenderun)intheSouthernAnatolia. Theirresultsshowthatthecontoursofconstantwind
speedandpowerpotentialcouldleadtheprivatepowerdeveloperstodecidethelocationsof
appropriatewindfarms. BilgiliandSahin(2009),andSahinandBilgili(2009)studiedwind
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Economic analysis of large-scale wind
energy conversion systems in central anatolian Turkey 133
energydensityinthesouthernandsouthwesternregionofTurkey.Thedominantwinddirec-
2010 tions,probabilitydistributions,Weibullparameters,meanwindspeeds,andpowerpotentials
weredeterminedaccordingtothewinddirections,years,seasons,months,andhoursofday,
2009
separately. Itisobtainedthattheseregionshaveareasonablewindpowerpotentialandthey
aresuitableforplantingwindenergyturbines.Inaddition,accordingtoauthorsBelen-Hatay
2008
isthemostpromisingandconvenientsiteforproductionofelectricityfromwindpower. Bil-
2007 gili et al. (2010) and Bilgili and Sahin (2010) investigated statistically wind energy density
ofAkhisar,Bababurnu,Belen,Datca,Foca,Gelendost,Gelibolu,GokceadaandSokedistricts
2006 whicharelocatedinthesouthern,southwesternandwesternregionofTurkey. TheWeibull
and Rayleigh probability density functions, and the Wind Atlas Analysis and Application
2005
Program (WAsP) packet program were used to analyze the measured data collected by the
General Directorate of Electrical Power Resources Survey Administration. They concluded
2004
thattheWeibullprobabilitydensityfunctionandWAsPprogramprovidebetterpowerden-
2003 sityestimationsthanRayleighprobabilitydensityfunctionforallstationsenjoyingareason-
ablewindpowerpotential.TheyfoundthatGokceadaandGeliboluwerethemostpromising
2002 andconvenientsitestoproducttheelectricityfromthewindenergy.Furthermore,Bilgiliand
Sahin(2010)presentedtheelectricpowerplantsinTurkeyand,theircapacitiesandresources
2001
usedintheelectricitygenerationinordertoupdatetheelectricenergystatistics.Thestatusof
thermal,hydro,wind,andgeothermalpowerplantsinTurkeywasclassifiedaccordingtothe
2000
electricityutilities.
1999 KurbanandHocaoglu(2010)studiedthepossiblewindenergypotentialinEskisehir,Turkey
usingthedatacollectedintheobservationstationestablishedatIkiEylulCampusofAnadolu
1998 University. Andthey(2010)investigatedthewindstatisticsandenergycalculationsforEs-
0 150 300 450 600 750 900 1050 1200 kisehir region using the Wind Atlas Analysis and Application Program (WAsP) software.
Theyselectedsuitablesitestolocatewindturbinesoptimallyaccordingtothecreatedwind
InstalledpowercapacityinTurkey[MW]
powerandwindspeedmaps.Eighteendifferentwindturbineswithnominalpowersbetween
200and2,000kWareconsideredtoproductenergy. KarsliandGecit(2003)determinedthe
windpowerpotentialoftheNurdagi/GaziantepdistrictlocatedinthesouthofTurkeyusing
Weibullparametersofthewindspeeddistribution. Theirresultsshowthatthedistricthasa
meanwindspeedof7.3m/sat10mheightandmeanpowerdensityof222W/m2. Akpinar
andAkpinar(2004)evaluatedthewindenergypotentialofMaden-ElazigineasternTurkey
andobtainedthatthemeanspeedvariesbetween5and6m/sandyearlymeanpowerden-
sityis244.65W/m2. Kose(2004)andKoseetal. (2004)determinedthepossiblewindenergy
potentialattheDumlupinarUniversity-Kutahyamaincampususingtheirownobservation
station. Celik(2003)analyzedthewindenergypotentialofIskenderunbasedontheWeibull
andtheRayleighmodelsusing1-yearmeasuredhourlytime-serieswindspeeddata.
Itcanbegeneratedmorepowerfromwindenergybyselectionofwindfarmsitewithsuitable
wind electric generator and establishment of more number of wind stations. The selection
andinstallingofsuitablewindelectricgeneratortoproduceelectricalenergyeconomicallyin
thewindyareasrequiresanumberofactivitiesthatincludetheinvestigationofthesource,
feasibilityassessmentetc. Ozerdemetal. (2006)carriedoutbothtechnicalandeconomical
feasibilitystudyforawindfarminIzmir-Turkeyusingthreediversescenariosforeconomical
evaluation. ItwasshownthatthegeneratingcostperkWhandinternalrateofreturnvalue
for all three scenarios were promising. Celik (2007) analyzed economically suitable power
generationusingwindturbineswhichhavenominalpowerrangeform0.6to500kW.This
study showed that Iskenderun was amongst the possible wind energy generation regions,
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134 Clean Energy Systems and Experiences
andthelowestcostofelectricityat$0.15perkWhwasobtainedinthewindturbinewith500
kW.
Gökçeketal. (2007a,2007b)studiedwindenergypotentialandenergycostanalysisofKirk-
lareliintheMarmaraRegion,Turkey. TheresultsoftheirstudyindicatedthatKirklarelien-
joyed well enough wind energy potential and the wind turbine with 2300 kW rated power
realizedthehighestannualenergyproductionandtheelectricalenergycostperkWhwases-
timatedasabout0.06$forturbinespecificcostas700$/kW.GençandGökçek(2009), and
Gökçek and Genç (2009) investigated the evaluation of wind potential, and electricity gen-
eration and cost of wind energy conversion systems in Central Anatolia Turkey. They has
concludedthatPinarbasiamongconsideredsiteshasaremarkablepotentialofwindenergy
forutilizationandcanbeevaluatedasmarginalareaforcost-effectiveelectricalenergygener-
ationasthecostsofwindenergyconversionsystemsarelowered. Furthermore,accordingto
theresultofthecalculations,itwasshownthatthewindenergyconversionsystemofcapacity
150kWproducetheenergyoutputabout121MWhperyearinthePinarbasiforhubheight30
mandalsoenergycostvariesintherangeof0.29-30.0$/kWhforallwindenergyconversion
systemsconsidered.
2. WindCharacteristic
2.1 WindEnergyMeteorology
Theatmosphereoftheearthabsorbssolarradiationduringtheday. Thenitdeliversheatto
spaceatalowertemperatureatnighttime.Inthisprocess,theregionswheretheairpressure
istemporarilyhigherorlowerthanaverageoccur. Thisdifferenceinairpressurecausesair
mass to flow from the region of higher pressure to that of lower pressure. This flow of air
massesiscalledaswind.
Windhastwocharacteristics: windspeedandwinddirection. Windspeedisthevelocityof
theairmasswhichtravelshorizontallythroughtheatmosphere. Windspeedisoftenmea-
suredwithananemometerinkilometersperhour(kmph), milesperhour(mph), knots, or
meters per second (mps) (Pidwirny, 2006). An anemometer (Fig. 2) consists of three open
cups attached to a rotating spindle. Wind direction is called as the direction from where a
windcomesfrom.Directionismeasuredbyaninstrumentcalledawindvanewhichisshown
inFig. 2. Thewindvaneinstrumenthasabulletshapednoseattachedtoafinnedtailbya
metalbar. Theanemometerandwindvanearepositionedintheatmosphericatastandard
distanceof10metersabovetheground.
Information on the direction of wind can be presented in the wind roses. The wind rose is
a chart which indicates the distribution of wind in different direction. Fig. 3 describes the
sixteen principal directions of wind. Meteorology reports the wind direction using one of
these sixteen directions. And aeronautical meteorology uses the degree concept based on
the360degreesfoundinacircleforthewinddirection,whileclimatologicalandsynoptical
meteorologyusesthesixteenprincipaldirections.
Wind always blows from high pressure region to low pressure region. High/low pressure
regionisaregionwhosepressureishigher/lowerthanitssurroundings.Thevelocityofwind
isbasedonpressuregradientforce. Ifthepressuregradientforceisgreater,thefasterwind
willblow.Iftheisobarswhicharealinedrawnthroughpointsofequalpressureonaweather
map (Fig. 4) are closely spaced, a meteorologist can forecast wind speed to be high due to
thefactthatthepressuregradientforceisgreat.Inareaswheretheisobarsarespacedwidely
apart,thepressuregradientislowandlightwindsnormallyexist.Forexample,whenthelow
pressureregioninthenorthofBlackSeainthesurfaceweathercharttakenfromTurkishState
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Economic analysis of large-scale wind
energy conversion systems in central anatolian Turkey 135
Fig.2.Anemometerusedtomeasurewindspeedanddirection(Pidwirny,2006)
MeteorologicalService(TurkishStateMeteorologicalService,2010)isconsidered,thewinds
intheAregionarefasterthanthewindsintheBregion.BecauseAregioninsideyellowcircle
hasthefourisobarswhileBregioninsidebrowncircleenjoyingsamediameterwithyellow
circlehasthetwoisobars.
Therearethreeanotherforcesactingonwind: coriolisforcewhichtherotationoftheEarth
creates, centrifugal force which is directed towards the center of rotation and friction force
whichtheEarth’ssurfacecreates.Thecoriolisforceandcentrifugalforceonlyinfluencewind
direction, whilefrictionalforcehaveanegativeeffectonwindspeedandarelimitedtothe
loweronekilometerabovetheEarth’ssurface(Pidwirny,2006).
2.2 WindSpeedDistributioninTurkey
TurkishWindAtlasshownforopenplainsinFigure5waspreparedusingWindAtlasAnal-
ysisandApplicationProgrambyTurkishStateMeteorologicalServicesandElectricalPower
Resources Survey and Development Administration in 2002 (Dündar et al., 2002). In this
study, the observations have been done for 96 meteorological stations distributed homoge-
neouslyoverTurkey,and45oftheseobservationstationswereusedforthepreparationofthe
WindAtlas. InthisWindAtlas,thelegendforclosedplainswasgiveninTable1. Asshown
inFigure5andTable1, therearemanysuitablesitesespeciallyincoastalareasandcentral
region(Pinarbasi)ofTurkeytoproductelectricityfromwindenergy.
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136 Clean Energy Systems and Experiences
Fig.3.Windrose
2.3 WindSpeedVariationWithHeight
Itisnecessarythatthewinddataextrapolatefortheturbinehubheightssincethewinddata
aremeasuredat10mheightaboveground.Inordertocalculateofwindspeedsatanyheight,
loglawcanbeused.Loglawboundarylayerprofile(ArcherandJacobson,2003)incorporates
aroughnessfactorbasedonthelocalsurfaceroughnessscalezs(m),
v=v ln(z/zs) (1)
0(cid:31)ln(z0/zs)(cid:30)
wherevisthewindspeedtobedetermineforthedesiredheight(z),v isthewindspeedat
0
recordedatstandardanemometerheight(z ).Surfaceroughnessisbasedonlandusecategory
0
suchasurban,cropland,grassland,forest,water,barren,tundra,etc. Thelandusecategory
can be selected from the Engineering Sciences Data Unit (Engineering Sciences Data Unit,
2010).
2.4 WeibullandRayleighWindSpeedStatistics
Inordertodescribethewindspeedfrequencydistribution,thereareseveralprobabilityden-
sityfunctions.Theprobabilitydensityfunctionspointoutthefrequencydistributionofwind
speed, and which the interspace of the most frequent wind speed is, and how long a wind
turbine is out and on of action. The Weibull and the Rayleigh functions are the two most
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Economic analysis of large-scale wind
energy conversion systems in central anatolian Turkey 137
Fig.4.Thesurfaceweatherchart(TurkishStateMeteorologicalService,2010)
Color Windspeed(m/s) Windpower(W/m2)
Darkblue >6.0 >250
Red 5.0-6.0 150-250
Yellow 4.5-5.0 100-150
Green 3.5-4.5 50-100
Cyan <3.5 <50
Table1.ThewindspeeddistributionsforclosedplainsonTurkishWindAtlas(Dündaretal.,
2002)
known. TheWeibullisaspecialcaseofgeneralizedgammadistribution,whiletheRayleigh
distributionisasubsetoftheWeibull(Johnson,2006). TheWeibullisatwoparameterdistri-
butionwhiletheRayleighhasonlyoneparameterandthismakestheWeibullsomewhatmore
versatileandtheRayleighsomewhatsimplertouse(Johnson,2006).TheWeibulldistribution
functionisexpressedas
k v k−1 v k
fw(v)= exp − (2)
c (cid:31)c(cid:30) (cid:29) (cid:31)c(cid:30) (cid:28)
where v is the wind speed, c Weibull scale parameter in m/s, and k dimensionless Weibull
shape parameter. These parameters can be determined by the mean wind speed-standard
deviationmethod(Justusetal.,1977)usingEqs.3and4.
σ −1.086
k= (1≤k≤10) (3)
(cid:31)v(cid:30)
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138 Clean Energy Systems and Experiences
Fig.5.TurkishWindAtlas(Dündaretal.,2002)
v
c= (4)
Γ 1+ 1
k
(cid:31) (cid:30)
wherevisthemeanwindspeedandσisthestandarddeviation. viscalculatedusingEq. 5
andσusingEq.6(Zhouetal.,2006).
1 n
v= ∑v (5)
n(cid:29)i=1 i(cid:28)
0.5
1 n
σ= ∑(v −v)2 (6)
(cid:27)n−1i=1 i (cid:26)
wherenisthenumberofhoursintheperiodofthetimeconsideredsuchasmonth,seasonor
year.
Thedimensionlessshapeparameter,kofWeibulldistributionisassumedas2inRayleighdis-
tributionfunctions.TheprobabilitydensityfunctionoftheRayleighdistributionisexpressed
as
πv π v 2
f (v)= exp − (7)
R 2v2 (cid:25) (cid:31)4(cid:30)(cid:31)v(cid:30) (cid:24)
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Economic analysis of large-scale wind
energy conversion systems in central anatolian Turkey 139
The wind power density of any windy site per unit area based on any probability density
functiontoestimatethewindpowercanbeexpressedas
∞
1
Pm = 2ρ(cid:31) v3f(v)dv (8)
0
where ρ is the standard air density, 1.225 kg/m3. When the Weibull function is chosen as
distributionfunction f(v),theaveragewindpowerdensityiscalculatedas
1 Γ(1+3/k)
Pmw = 2ρv3[Γ(1+1/k)]3 (9)
3. ElectricalPowerofWindEnergyConversionSystem
Annualwindenergyoutput, Ewtforanywindysitecanbecalculatedusingthetime-series
windspeeddataofthatsiteandthepowercurveofawindturbine. Inordertopredictthe
windenergyoutputtobeobtainedfromthewindturbine,analgebraicequationofdegreen
accordingtothepowercurveofthewindturbinebetweencut-inandratedspeedorcut-in
speedandcut-outspeedcanbeexpressedasEq.10.
0, v<v
ci
 anvn+an−1vn−1+...+a1v+a0 , vci ≤v<vR
Pi(v)= (cid:26)PaRn,vn+an−1vn−1+...+a1v+a0(cid:25), vvRci≤≤vv<<vvccoo or (10)
 0(cid:26), (cid:25) v≥vco
wherean,an−1,a1anda0areregressionconstants,vciisthecut-inspeed,vRistheratedspeed,
vco isthecut-outspeedand PR istheratedpowerandalso Pi(v)isthepowergeneratingin
therelatedwindspeed.
Thetotalenergygeneratedbytheoperationalturbineoveraperiodiscalculatedbyadding
uptheenergyoutputofallpossiblewindspeeds.Inthisstudy,theenergyoutputfromawind
turbinewasobtainedwithEq.11usingthehourlymeanwindspeeds.
n
Ewt = ∑Pi(v)t (11)
i=1
wherenisthenumberofhoursintheperiodoftheconsideredtimesuchasyear,seasonor
month,tisonehourtimeduration.
Capacityfactor,C isanindicatorofboththeturbinetypeandthewindspeedinasitecon-
f
sidered.Thecapacityfactorisimportantforassessingtheperformanceofawindturbineina
siteconsidered(Sathyajith,2006).Annualvalueofthecapacityfactorcanbecalculatedas
C = Ewt (12)
f E
rated
4. EnergyCostAnalysisofWindEnergy
Thefuelofwindenergymaybefree,buttheequipmentnecessarytousethewindenergycan
beexpensive,soeconomicanalysisofthewindenergyisquiteimportant. Thewindturbine
has to enjoy low operating cost. There are several factors affecting the unit energy cost of
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140 Clean Energy Systems and Experiences
electricityproducedinthewindturbines. Thesefactorsmayvaryfromacountrytoanother
country.
The total capital investment and operating cost for wind electric generators have to been
knowntodeterminetheunitcostofelectricity. Ingeneral,thecostperunitenergyisfound
bydividingtheamountofenergyproducedtothetotalexpendituresmadealongthecertain
timeinterval.Allcostsofacquiring,owning,anddisposingofasystemmustbeconsideredto
makesafelyeconomicdecisions. However,thevalueofmoneyduringtheusefullifetimeof
windenergyconversionsystemconsideredshouldbetakenintoaccountinthecostanalysis.
Thelevelizedcostofelectricitymethodisoneofthemostimportantindicatorsforevaluating
fiscalperformanceofpowersupplysystemssuchaswindenergyconversionsystem(Gökçek
and Genç, 2009). The levelized cost of electricity method can be used to calculate the unit
costthroughouttheusefullifeofasystem. Thelevelizedcostofthewindenergyconversion
systemistheratioofthetotalannualizedcostofthewindenergyconversionsystemtothe
annual electricity produced by this system (Gökçek and Genç, 2009). The generation cost
of the electrical energy of 1 kWh using a wind turbine system using the levelized cost of
electricitymethodcanbedefinedas
Cel = CwtFwt+CinFin+CciFci+ECbbFbb+CmiscFmisc+C(om)esc [$/kWh] (13)
wt
where Cel and C(om)esc are the cost of energy output and the cost of annual operation and
maintenanceescalated,respectively.AndFwt,Fin,Fci,FbbandFmiscaretheannualchargerate
oncapitalforwindturbine,inverter,civilworkandinstallation,batterybankandothermis-
cellaneousequipments,respectively. Theannualchargerateoncapitalandcanbeexpressed
bythefollowingequation;
r
F= (14)
[1−(1+r)−n]
wherenandraretheusefulsystemlifetime(year)andthediscountrate,respectively.
Thetotalinvestmentcostofawindenergyconversionsystemisgivenas;
Cwecs =Cwt+Cbb+Cci+Cin+Cmisc [$] (15)
whereCwt, Cbb, Cci, Cin andCmisc arethecostofthewindturbine,thecostofbatterybank,
thecostofcivilworkandinstallation, thecostoftheinverterandthecostofmiscellaneous
equipments(connectingcables,controlpanelandothercomponents).Furthermore,whilethe
awindenergyconversionsystemisbeingboughtfromacompany,thetotalinvestmentcost
ofthesystem,Cwecs,canbealsoknownas;
Cwecs = IwecsPr [$] (16)
whereIwecsandPrarethespecificcostandratedpowerofthewindenergyconversionsystem.
Adistributionofrelativecostsdifferentcomponentsofatypical5kWwindenergyconversion
systemisthewindmachine74%,miscellaneouscomponents10%,batterybank9%,civilwork
andinstallation4%,inverter3%(Nounietal. 2007). Inthisstudy,theevaluationofcostwas
consideredasthiscostbreak-upforallwindenergyconversionsystems.Thetotalinvestment
cost of any wind energy conversion system in terms of rated power was taken as mean of
valuereadfromTable2(Sathyajith2006). Andthecostsofthewindturbine, batterybank,
civil work and installation cost, inverter and miscellaneous equipments were calculated by
usingEqs.15and16andusedinEq.13.
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