Originalscietificpaper–Izvorni znanstveni rad

Croat. j. for. eng. 33(2012)2 225

Predicting and Controlling Moisture Content

to Optimise Forest Biomass Logistics

Mauricio Acuna, Perttu Anttila, Lauri Sikanen, Robert Prinz, Antti Asikainen

Abstract – Nacrtak

Wood fuel quality attributes have to be considered by logistics planners if fuel procurement from forests and energy production at the plant are considered simultaneously. The single most important quality attribute is the moisture content (MC) of chips or raw material delivered to energy plants. It affects heating value, storage properties, chipping and transport costs of the fuel. To assess the impact of forest biomass moisture content on supply chain costs, we devel­oped a linear programming-based tool for optimization decision support that minimizes sup­ply chain costs including harvesting, storage, chipping, and transportation of fuels. A CHP plant in Finland was used as the study case and three biomass raw materials (supply chains) were used for the analysis: whole trees from early thinnings, stemwood from early thinnings, and logging residues from final fellings. Our results indicate that both the proportion and volume of the biomass material delivered to the plant are very sensitive to specifications on MC range limits and the length of the storage (drying) period. Compared to a scenario with no storage, a reduction in volume harvested of up to 33% can be achieved to meet the month­ly energy demand if proper drying methods, such as covering of biomass material, are imple­mented before chipping and delivering the biomass materials to the energy plant.

Keywords: moisture content, biomass supply chain, optimal storage and transportation, linear programming, biomass covering

1. Introduction – UvodTosustainablymeettheincreasingdemandforfor-

estbiomass,properharvestingtechnology(includingcomminution,handlingandstorage)andworkmeth-odsmustbedevelopedandimplementedwiththegoaltoproducehighqualityfuels(Röseretal.2010).Fuelqualityisassessedbasedonthepropertiesthataffect theenergyyieldandcosts.Moisturecontent(MC),grosscalorificvalueandashcontentofthelog-gingresiduearethreepropertiescommonlyusedtoassessthefuelquality,aseachofthesepropertiesde-terminetheviabilityofbiomassprocurementforen-ergyproduction(Gautametal.2012;Brandetal.2011),aswellastheusabilityoftheplantandefficiencyandeconomyofcombustion(Röseretal.2011).ThemostimportantsinglequalityfactoristheMCofchips.Itaffectstheheatingvalue,storagepropertiesandtrans-portcostsofthefuel(Asikainenetal.2001;Röseretal.2011).MCisadirectcostfactor,anditistakeninto

accountinthepricingofthefuel.AnexcessiveMCresultsinapricereduction,whilealowMCbringsabonus.Theprocurementof logging residue for energy

productioncanbeuneconomicalduetohighMCandlowcalorificvalue.HighMCinbiomasslowerstheenergydensityandtransportationbecomeslesseffi-cient(Gautametal.2012).Therefore,naturaldryingoftimberduringtheprocurementprocessesshouldbepromotedtofacilitatethedryingprocessandensuretheavailabilityofhighqualityfuelintheshortandlongterm(Röseretal.2011).Someconsiderationshavetobemadebylogisticsplannersiffuelprocurementfromforestsandenergyproductionattheplantareconsideredsimultaneously.Ononehandtheextensionofstoragetimelowerssystemcostsbyloweringtrans-portation costs andby improving efficiency at theplant.Theefficiencyimprovementistheresultofin-creasingheatingvalueandlowerneedleandimpurity

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226 Croat. j. for. eng. 33(2012)2

contentinthematerial.Ontheotherhand,extensionof storage time increases systemcostsbecause thewoodstartstodecomposecausingmateriallossesandbecauseofthecapitalinvestedinthestoredfuel(Asi-kainenetal.2001;PetterssonandNordfjell2007).Drying(MC)curvesareavitalpieceofinformation

whenimplementingoptimalstorage,harvesting,chip-pingandtransportationdecisionsinabiomassplan-ningmodel.Althoughmathematicalmodels havebeendevelopedtooptimizebiomasslogisticsforshortperiods(ErikssonandBjorheden1989;Gunnarsonetal.2004;Kanzianetal.2009),wearenotawareofanylogisticsmodelorstudythatinvestigatedtheeffectofMConsupplychaincostsforlongerperiods(>1year)throughtheuseofanoptimizationmodelthatexplic-itlyusesMCasaninputparameter.Takingpreviousstudiesasareferencepoint,wedevelopeda linearprogramming-baseddecisionsupporttooltoconductaninvestigationintotheeffectofbiomassMConsup-plychaincostsforanoperationalplanningunderdif-ferentscenarios.

2. Materials and methods – Materijali metode

2.1 Supply chains used for the analysis – Lanci dobaveThestudyisbasedontheparametersofalarge

scalecombinedheatandpowerplant(CHP)inJoen-suu,Finland,andthedescribedsupplychainsapplytotheJoensuufacility.ThisplanthasatotalCHPout-putof180MW,outofwhich30MWiselectricalout-put. The produced heat is distributed to the citythroughadistrictheating(DH)system.IntheDHareaofJoensuu,41640inhabitants(or57%ofthemunici-palitypopulation)areconnectedtothe200kmpipe-lineDHnetwork(Energiateollisuus2011).Inourstudy,anumberof forestenergysupply

chainswereselectedandincludedintheoptimizationlogisticsmodel.ThebiomassmaterialsselectedandtheircorrespondingsupplychainswereadaptedandsimplifiedtomeettheobjectivesoftheinvestigationusingtheJoensuuCHPplantstudycase.

Supply chain I:Wholetreesupplychainfromthin-ningswithchippingattheroadside.InFinland,log-gingsystemsinsmalldiameterwholetreethinningcanbeclassifiedintothosebasedonthemotor-manu-alormechanizedcuttingoftrees.SupplychainIisbasedonthetraditionaltwomachinesystemwithaharvesterandaforwarder,wherebothmachinesuti-lizethemulti-treeprocessingtechnique.Sincethefell-

ingphaseisstillthemostdemandingandcostlypartoftheproductionchaininenergythinning,thecuttingofwholetreescanbedonewithpurposebuiltaccu-mulatingfellingheadsorbynormalharvesterheadsequippedwithmulti-treehandlingaccessories(Laitila2012).Afterfelling,thinningtreesareforwardedtoroadsidewheretheyareleft(stored)todryforafewmonths.Inthelaststep,comminutionofwholetreesisdoneattheroadsideusingheavytruck-mountedchippers or crushers in large-scale operations. Toavoiddelayscausedbytheinteractionofmachines,thetruckmountedchipperandchiptruckcanbere-placedbyasinglechippertruck.Thatblowsthechipsdirectlyintoacontainerandthenhaulstheloadtotheplant.Asthechippertruckisequippedwithitsownchippingdeviceandcrane,loadcapacitysuffersandtheoperationradiusaroundtheplantisreduced(Hak-kila2004).

Supply chain II:Delimbedstemsfromthinningswithchippingattheplant.Theharvestingunitsareequippedwithdelimbingknivesandfeedrollersthataresuitableformultiple-treeprocessing(Laitila2012).The costs ofmulti-stemharvesting toproducede-limbedshortwoodare,onaverage,23%greaterthanharvestingwholetreesduetothedifferenceinproduc-tivity(Heikkiläetal.2005;Laitilaetal.2010;LaitilaandVäätäinen2011). In this supplychain, loggingresidues(branches,needles,etc.)areleftinthestand,andonlythedelimbedstemsareforwardedtoroad-side for storage.Wood stems are dried for a fewmonthsattheroadsideafterwhichtheyaretransport-edtotheplantforcomminution.Thisisperformedusing highly efficient chippers or crushers whichmakesroadtransportationandchippingoperationsindependentofeachotherandverycostefficient,es-peciallywithshorttransportationdistances.Thispro-videssomeadvantagessuchas increasedtechnicalandoperativeavailabilityoftheequipment,aninde-pendentandlesslaborintensiveprocurementprocessandtheimprovementoffuelquality(Hakkila2004).

Supply chain III.Loggingresidueswithchippingatroadside.InFinland,loggingresiduesareobtainedprimarilyduringfinalfellingsconductedeachyearfromNovember toMarch (wintermonths). In thiscase,theprocurementofloggingresiduesisbasedonthelooseresiduesystem.Theharvestingmethodisadaptedsothatloggingresiduesareleft(stored)inthestandduringthetimberprocessing.Afterdrying,theloggingresiduesareforwardedtoroadside,normallybya forwarderwithanenlarged loadspaceandaresiduegrapple.Inanextstep,theloggingresiduesarecomminutedattheroadsidelandingclosetotheloggingsiteinasimilarfashiontosupplychainI.

Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics (225–238) M. Acuna et al.

Croat. j. for. eng. 33(2012)2 227

2.2 Biomass supply chain optimization system Optimizacija sustava dobave biomase

2.2.1 Implementation of the system – Primjena sustavaWedevelopedandimplementedalinearprogram-

ming,MSExcel©-basedtoolforoptimizationdecisionsupportnamedBIOPLANtoinvestigatetheeffectofMConstorage,chippingandtransportationcostsofbiomassmaterialdeliveredtoanenergyplant(Fig.1).Theobjectivefunctionofthestrategic,non-spatialop-timizationmodelminimizesthetotalcostsassociatedwithharvesting,storage,chippingandtransportac-cordingtoMCcurves,whichareincludedasexplicitparametersintheoptimizationmodel.In its current version (1.1), BIOPLAN includes

wholetreesfromthinning,delimbedstemsfromthin-ning,andloggingresiduesasbiomassmaterialsalongwiththeircorrespondingsupplychains.BIOPLANisstructuredinsuchawaythatalltheinformationisdisplayedinaseriesofmatriceswhichinclude:

Þ Decisionvariablesontonsandcorrespondingsolidvolumeofbiomassmaterialtoharvestineachperiod,

Þ Loosevolumeofwoodchipsproducedineachperiod(roadsideorenergyplant),

Þ Numberoftruckloadsdeliveredtotheenergyplant,

Þ Energycontentofchips,Þ Harvesting and forwarding costs (includingsubsidiesforwholetreesandstemwoodfromthinningoperations),chippingcosts(roadsideorenergyplant),storagecostofmaterialattheroadside,andtransportationcost(stemwoodorchips).

Themodelconsidersa2-yearplanninghorizonanddecisionsontonsorvolumeofbiomassmaterialtoharvestaremadeonamonthlybasis(24periods)overthattimehorizon.ExceptinsupplychainII,thebiomassmaterialisstoredforanumberofperiodsandthenchippedattheroadside.Chipswithadetermined

Fig. 1 BIOPLAN 1.1 user’s interfaceSlika 1. Računalni program BIOPLAN 1.1 – sučelje

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228 Croat. j. for. eng. 33(2012)2

Table 1 Sets, parameters, and variables used in the mathematical formulation of the modelTablica 1. Grupe, parametri i varijable primijenjeni u matematičkom formuliranju modela

Term – Termin Definition – Definicija

Set – Grupa Set – Grupa

i,j = periods i I = {1...24}, j J = {13...24}

Parameters – Parametri

a, b, gConversion factors from m3 solid to m3 loose for whole trees, stem wood and logging residues, respectively

Faktori pretvorbe iz rasute u čvrstu drvnu tvar dobivenu od cijelih stabala, debla i drvnoga ostataka

ECwt, ECsw, EClr

Energy content for chips produced from whole trees, stem wood and logging residues, respectively

Energija iz iverja cijelih stabala, debla i drvnoga ostatka

HC1wt, HC1

sw, HC1lr Harvesting cost (€/m3 solid) for whole trees, stem wood, and logging residues harvested in period i

Troškovi sječe (€/m3 čvrste tvari) za cijela stabla, debla i šumski ostatak u godini i

ST1,jwt, ST1,j

sw, ST1,jlr Storage cost (€/m3 solid) for whole trees, stem wood, and logging residues stored at roadside from period i to j (i ≤j)

Troškovi skladištenja uz šumsku cestu (€/m3 čvrste tvari) za cijela stabla, debla i šumski ostatak u vremenu od i do j (i ≤ j)

CH1,jwt, CH1,j

sw, CH1,jlr

Chipping cost (€/m3 solid) for whole trees, stem wood, and logging residues harvested in period i and chipped in period j at roadside or plant

Troškovi iveranja (€/m3 čvrste tvari) cijelih stabala, debala i drvnoga ostatka, sječenih u vremenu i, iveranih uz šumsku cestu ili u energani, u vremenu j

TR1,jwt, TR1,j

sw, TR1,jlr

Transportation cost (€/m3) for whole trees chips (solid volume), stem wood (solid volume), and logging residues chips (loose volume) harvested in period i and transported to plant in period j

Troškovi prijevoza iverja (€/m3) cijelih stabala (čvrsta tvar), debala (čvrsta tvar) i drvnoga ostatka (rasuta tvar) posječenih u vremenu i te prevezenih u energanu u vremenu j

Variables – Varijable

xi,j

Solid volume of whole trees harvested in period i and stored at roadside until period j for chipping

Obujam čvrste tvari iz cijelih stabala posječenih u vremenu i te skladištenih uz šumsku cestu do vremena iveranja j

yi,j

Solid volume of stem wood trees harvested in period i and stored at roadside until period j for transport and chipping at the plant

Obujam čvrste tvari iz deblovine pridobivene u vremenu i te skladištenih uz šumsku cestu do vremena j uz iveranje u energani

zi,j

Solid volume of logging residues harvested in period i and stored at roadside until period j for chipping

Obujam čvrste tvari iz drvnoga ostatka pridobivenoga u vremenu i te uskladištenoga uz šumsku cestu do vremena iveranja j

xi,jr xi,j × a = Loose volume of chips from whole trees harvested in period i and stored at roadside until period j for chipping

xi,j × a = Obujam rasutoga iverja dobivenoga iz cijelih stabala posječenih u vremenu i te uskladištenih uz šumsku cestu do vremena iveranja j

zi,jr zi,j × g = Loose volume of chips from logging residues harvested in period i and stored at roadside until period j for chipping

zi,j × g = Obujam rasutoga iverja dobivenoga iz drvnoga ostatka u vremenu i te uskladištenoga uz šumsku cestu do vremena iveranja j

moistureandenergycontentarethentransportedtotheenergyplantforconsumption.InsupplychainII,stemwoodisstoredattheroadsideforanumberofperiodsandthentransportedtotheenergyplantforchippingandconsumption.Storageofanybiomassmaterialattheroadsideisallowedforaperiodofupto24months(fromJanuaryYear1toDecemberYear

2)andallthematerialsuppliedmustmeettheplantmonthlydemandforenergy(MWh)intheyear2(En-ergyGenerationYear)atminimumcost.Thatmeansthatanybiomassproducedintheyear1willbecom-bustedintheyear2.Initsbasicformulation,thesup-plychainmodelcanbeexpressedas follows.Sets,parameters,andvariablesarepresentedinTable1:

Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics (225–238) M. Acuna et al.

Croat. j. for. eng. 33(2012)2 229

Objectivefunction(FO)Equation1minimizesthetotalsupplychaincosts

(€),associatedwithbiomassharvesting,storage,chip-pingandtransport.

(1)

ConstraintsEquation2ensuresthattheenergycontentofthe

chipssuppliedsatisfythemonthlyenergydemandattheplant(MWh).

(2)

Equation3ensuresthatanevenvolumeofwholetreesisharvestedevenlyineachyear.Thisallowsforcontinuousworkfortheharvestingandhaulagecon-tractors. (3)Equation4ensuresthatanevenvolumeofstem

woodisharvestedevenlyeachyear.Thisallowsforcontinuousworkfortheharvestingandhaulagecon-tractors. (4)Equation5ensuresthatanevenvolumeoflogging

residuesisharvestedevenlyduringthewintermonthsofeachyear. (5)Themodelassumesthatinanyperiodthechips

arrivingattheenergyplantmustbeconsumedinthesameperiod,andtherefore,therearenocostsassoci-atedwiththestorageofchipsattheplant.Othercon-straintsmodeledinthesystemincludeMClimitsforchipsandstemwoodarrivingattheplant,anddryingperiodlimitsforthematerialsthatarestoredattheroadside.Stumpagepriceisnotincludedaspartofthetotalsupplychainscosts.Asoutputs,BIOPLANreports total cost for the

wholeoperationandtotalcostbyactivity(harvesting,storage,chipping,andtransportation),aswellastotalenergyofthefuelsuppliedtotheplantinMWh.Ad-ditionally,foreachsupplychain,thesystemreportssolidvolumeandfreshtonsofbiomassmaterialhar-vested,loosevolumeofchipsproducedattheroad-sideorplant,totalenergycontent(MWh),andtotalnumberoftruckloadswithchipsorstemwoodarriv-

ingattheplant.Withineachsupplychain,thesystemreportsthecostperm3solid,costpergreenton,costperm3loose,costpertruckloadandcostperMWh.

2.2.2 Optimization model parameters – Parametri optimizacijskoga modelaTable2showstheparametersusedinthecontrol

scenarioforthethreesupplychainsanalysed.Severalreferenceswereconsultedtogettheparam-

etersforBIOPLAN.Basicdensity,calorificvalues,andsolidcontentforthemainspeciesinFinlandwereob-tainedfromNurmi(1993);Hakkila(2004);andLau-rilaandLauhanen(2012).Harvesting,chipping,andtransportcostsarepresentedinTable3.Thesecostswerepreliminarilycalculatedandvalidatedfromcost-ingspreadsheetsdevelopedbyMETLA(Heikkilaetal.2005;Laitila2006;Laitila2008).Thesevaluesweresubsequentlyupdatedbyusingresultsfrommorere-centstudies(Laitilaetal.2010;LaitilaandVäätäinen

Table 2 Parameters and conversion factors used in BIOPLANTablica 2. Paramateri i faktori pretvorbe primijenjeni u BIOPLAN-u

Parameters & conversion factors

Parametri i faktori pretvorbe

SCH

I

SCH

II

SCH

III

Energy content at 0% MC, MJ/kg

Količina energija pri 0 % udjela vlage, MJ/kg19.5 19.0 20.0

Basic density, kg/solid m3

Osnovna gustoća, kg/čvrste tvari, m3 410 400 415

Bulk density, kg/solid m3

Obujamna gustoća, kg/čvrste tvari, m3 172.2 168.0 174.3

Solid content

Udio čvrste tvari0.42 0.42 0.42

Ratio loose – m3 to solid m3

Odnos (m3) rasute prema čvrstoj tvari2.38 2.38 2.38

Truck payload, tons

Nosivost kamiona, t35.0 35.0 35.0

Truck volume, m3

Obujam tovarnoga prostora, m3 130.0* 47.0** 130.0*

Round trip distance, km

Puni obilazak, km128 150 185

Dry matter loss rate, %/month

Stopa suhe tvari, % /mjesečno1.0 1.0 2.0

Interest rate, %/month

Kamatna stopa, % /mjesečno0.5 0.5 0.5

* m3 loose, ** m3 solid* m3 rasuta tvar, ** m3 čvrsta tvar

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230 Croat. j. for. eng. 33(2012)2

2011;TahvanainenandAnttila2011).Storagecostsinthemodelarebasedontheassumptionthattherehavebeencostsassociatedwithharvestingandtransport-ingthematerialtoroadsideandthatthesecostshavebeenpaidforatthetimeofharvest.Thus,storagecostsare then the interest chargeon theharvestingandtransporttoroadsidecostssincethewoodownerin-cursadelayduetostorageinbeingreimbursedforthese.Anannualinterestrateof6%wasusedfortheanalysis,asithasbeensuggestedandusedinpreviousbiomassstudiesinFinland(Laitila2006).

2.2.3 Drying curves and algorithm – Krivulje i algoritam

MCofbiomassmaterialsforanygivenmonthwascalculatedwiththedryingmodelsdevelopedbySi-kanen(2012)basedonheuristicfitting.Themodelspredictdailymoisturechangeforsevendryingperi-odsofayearbasedonpreviousempiricalexperimentsandhistoricaldata. Forwhole trees anddelimbedstemwood,valuesbyHakkila(1962)wereused.AsnodataontheannualvariationinMCforcrownbiomassfromfinalfellingswerefound,Hakkila’s(1962)valuesfor small-sizedNorwaySprucewereused, but in-creasedby2%units.Forthepurposeoftheanalysis,andduetothelackofpredictiveMCmodelsforeachbiomassmaterial,dryingcurveswereassumedtobethe same forwhole trees, stemwood,and loggingresidues(Fig.2).Inaddition,drymatterlossratespermonthdue to storagewere assumed to be 1% forwholetreesandstemwood,and2%forloggingresi-dues(Laitila2006).

2.3 Data analysis – Obrada podatakaTheanalysisinthispaperfocusesprimarilyonthe

effectofMConsupplychaincosts.Threeaspectsofthebiomasssupplychainandtheirimpactontotalcostsandtheoptimalfuelsupplysolutionwereinves-tigatedwiththeBIOPLANsystem:

ÞEffectofdifferentMClimitsonthematerialar-rivingattheCHPplant,

Fig. 2 Drying curves for biomass materials at different felling timesSlika 2. Krivulje udjela vlage tijekom obaranja i skladištenja

Table 3 Harvesting, chipping, transport cost parameters used in BIOPLANTablica 3. Parametri troškova sječe, iveranja i prijevoza primijenje-ni u BIOPLAN-u

Parameters – ParametriSCH

ISCH

IISCH

III

Mechanized felling, bunching & forwarding, €/m3

Strojna sječa i izrada te privlačenje, €/m3 13.0 14.6 10.0*

Chipping, €/m3 – Iveranje, €/m3

MC% <=35 – Udio vlage, <=35 % 5.8 3.8** 7.4

36=MC%<=50 – Udio vlage, 36 – ≤50 % 5.1 3.1** 6.7

MC%>50 – Udio vlage, >= 50 % 4.3 2.3** 5.9

Transport, €/km – Prijevoz, €/km 2.4 1.8 2.5

* It includes just forwarding – Uključuje privlačenje forvarderom** Chipping at the energy plant – Iveranje u energani

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Croat. j. for. eng. 33(2012)2 231

ÞEffectofdryingperiodlimitsonthematerialstoredattheroadside,

ÞEffectofmoreefficientdryingmethods.Theresultsoftheanalysisineachsupplychainare

presentedintermsofthemonthlyvolumeofbiomassmaterialthatisharvested,aswellasthetotalsupplychaincostsandthecostsofdifferentoperationalac-tivities(harvesting,storage,chipping,andtransporta-tion).Statisticaldifferencesofmonthlyvolumehar-vestedand costsbybiomassmaterial between thescenariosanalyzedwerecheckedwitht-testsconduct-edatthep=0.05levelofsignificance.

2.3.1. Effect of different MC limits on total supply chain costs – Utjecaj graničnih sadržaja vlage na ukupne troškove lanca dobave biomase

ThreescenariosweresetuptoinvestigatetheeffectofMClimitsonsupplychaincosts.Thefirst(basic)scenariodidnotincludespecificconstraintstolimittheMCofthebiomassmaterial(chipsinsupplychainsIandIII,andstemwoodinsupplychainII)arrivingattheCHPplant.Inthesecondandthirdscenario,weaddedaconstrainttolimittheMCofthebiomassma-terialarrivingattheplant,whichwassetto41–49%,and41–43%,respectively.ThelatterMCrangeistheJoensuuCHPplantpreferenceintheirlogisticsopera-tions.

2.3.2. Effect of storage time on total supply chain costs – Utjecaj duljine skladištenja materijala na ukupne troškove lanca dobave biomase

InBIOPLAN,thestorageofanybiomassmaterialat the roadside isallowed foraperiodofup to24months(fromJanuaryYear1toDecemberYear2).Theoptimizationmodeldeterminesthemonthlyvolumethatisharvestedandstoredattheroadsidesothatthesupplychaincostsareminimizedduringthatperiod.Toinvestigatetheeffectofbiomassstoragetimeattheroadsideontotalsupplychaincosts,aconstraintwasaddedtolimitthenumberofperiods(months)ofstor-age.Therewasparticularinterestinknowingifstor-ageforaperiodshorterthan12monthshadasubstan-tialeffectonthebiomasssupplychaincosts.Therefore,inadditiontotheunconstrainedscenario(nolimitsonstorage),twoscenarioswereestablishedwhichcon-strainedthestorageperiodtoamaximumof6periods,andaminimumof3periods,respectively.

2.3.3 Effect of more efficient drying methods on supply chain costs – Utjecaj djelotvornijih načina sušenja biomase na ukupne troškove lanca dobaveEffectivedrying of biomassmaterial, including

covering,isessentialtodecreasetheMCofbiomass

material.MCcanbe reduced ina fewmonthsby10–20%usingonlysolarandwindpowerifbiomassmaterialiscovered(Röseretal.2010)Toanalyzetheeffectofcoveringonbiomasssupplychaincosts,andintheabsenceofaccuratedryingcurvesforcoveredmate-rial,weestablishedtwohypotheticalscenarioswherethedryingratesforallthebiomassmaterialsweread-justed by 10% and 15% in the autumn andwintermonths(OctobertoApril),assumingalowerrateofrewettingofthebiomassmaterialswhentheyarecov-eredduringthesemonths.Duetothelackofinforma-tion,coveringcostswereassumedtobe€1/m3.

3. Results and Discussion – Rezultati s raspravom

3.1 Effect of different MC limits on supply chain costs – Utjecaj graničnih sadržaja vlage na ukupne troškove lanca dobave biomaseForthethreescenariosanalyzed(unconstrained,

41–49%MC,41–43%MC),Fig.3showstheMC(%)curvesofbiomassmaterial(chipsorstemwood)de-liveredtotheplantduringyeartwo.Intheuncon-strained scenario, the biomassmaterials present amuchhighervariationinMCthroughouttheyear,es-peciallyforwholetreesandloggingresidues.Maxi-mumandminimumMCvalueswere52.3%and41.5%forwholetrees,53.7%and39.6%forloggingresidues,and51.2%and42.6%forstemwood.Asexpected,thebiomassmaterialdeliveredto theplantduring thesummerhadamuchlowerMCthaninautumnandwinter. During the winter months (November toMarch),loggingresidueshadalowerMC(average48.6%MC)comparedtowholetreesandstemwood(average50.3%MC),whichresultedfrommuchlongeraveragedryingperiods(>1year)attheroadsideforloggingresidues(7monthscomparedtolessthan1.5monthsforwholetreesandstemwood).Variationinpost-storageMCforloggingresidues

wasmuchhigherthanforstemwoodandwholetrees(std.dev.5.4versus2.8 for stemwoodand3.4 forwholetrees)intheunconstrainedscenario.Converse-ly,therewasnovariationforanyofthebiomassma-terialsproduced(wholetreesandloggingresidues)(std.dev.=0)whenMCwasconstrainedto41–43%,astheMCofthesematerialswasalwaysatthetopoftherange(43%).Fig.4showsthevolumeharvestedperyearbybio-

massmaterialforthethreescenariosanalyzed.Onlythemeanvolumedifferencesbetweenwholetreesandloggingresiduesharvestedintheyear1and2werestatisticallysignificant(p<0.05).Intheunconstrained

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232 Croat. j. for. eng. 33(2012)2

Fig. 3 Variation in post-storage MC for whole trees, stem wood, and logging residues used in the second year for energy generation in the three MC scenarios analyzedSlika 3. Promjene u sadržaju vlage kod cijelih stabala, debla i šumskoga ostatka pri dužem skladištenju (korištenje tek druge godine)

Fig. 4 Solid volume (m3) harvested for whole trees, stem wood, and logging residues in the three MC scenarios analyzedSlika 4. Obujam čvrste tvari za cijela stabla, debla i drvni ostatak u tri različita scenarija

scenario,loggingresiduesweremostlyproducedintheyear1(47118m3or100%ofthetotalbiomassma-terialharvestedinthatyear)andstoredattheroadsideforlongerperiods(averageof7months)beforebeing

deliveredtotheplantintheyear2.Thisistheresultoflowerharvestingcostsforloggingresidues,whichal-lowsforlongerstorageperiodsastheinterestontheharvestingcost(storagecost)isreducedincomparison

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towholetreesandstemwood.Conversely,duetothecoststructureandlowerenergycontentofwholetrees(andtoalesserextentstemwood),theoptimalsolutiononlyallowsforshortperiodsofstorageattheroadside,withchippingandtransportationoccurringjustafewperiodsafter theharvestandstorage.Thesesupplychainswereusedprimarilyintheyear2,whenapprox-imately41%ofthematerialharvested(94770m3)cor-respondedtowholetreesand57%ofthematerialhar-vested(130979m3)correspondedtostemwood.WhenMCwasconstrainedto41–43%,thesolution

precludedtheharvestofstemwoodandtheenergydemandwasmostlymetwithloggingresidueshar-vestedduringthefirstyearandwholetreesharvestedduringthesecondyear.Similarly,whenMCwascon-strainedto41–49%,thevolumeharvestedofstemwoodwasjustmarginalandaccountedforlessthan1%ofthetotalvolumeharvestedintheyear1,andabout3%ofthetotalvolumeharvestedintheyear2.Thevolumeofloggingresiduesharvestedinthe

year1was43170m3(87%ofthetotalvolumehar-vested)whentheMCrangedbetween41–49%and152161m3(92%ofthetotalvolumeharvested)whentheMCrangedbetween41–43%.Wholetreeswasthepre-dominantbiomassmaterialharvestedintheyear2with151161m3(69%ofthetotalvolumeharvested)whentheMCrangedbetween41–49%and99209m3 (88.2%ofthetotalvolumeharvested)whentheMCrangedbetween41–43%.Thepredominanceoflog-

gingresiduesandwholetreesisduetotheirlowerharvestingcosts(whichisthemaincostcomponentinthethreesupplychains)incomparisontowholetrees.Thisreductioninharvestingcostsoffsetsthehigherchippingandtransportationcostsofthesetwobio-massmaterials.Inaddition,thereductioninharvest-ingcostsmakesstoragemorecosteffectiveforloggingresiduesandwholetrees,allowingforlongerstorageperiods of these biomassmaterials (average of 1.5monthsforwholetreesand7monthsforloggingres-idues,versusaverageof1monthforstemwood).DespitetheeffectofMClimitsonthevolumeand

distributionofthebiomassharvested,nostatisticaldifferenceswereobtainedintermsofsupplychaincosts(Fig.5)inthethreescenariosanalysed(p<0.05).Inpart,thisisexplainedbythefactthattheharvestingandextractionofbiomassmaterialstoroadsidearethemajorsupplychaincostcomponent,whichhowever,arenotaffectedbymoisture content.Also, in con-strainedscenarios, the solution tends toadjust theproportionofthematerialsthatminimizesthesupplychaincosts,basedonthecontributionoftheiropera-tionalactivities (harvesting, storage, chipping,andtransportation)totheobjectivefunction.Onaperm3 solidbasis,thetotalsupplychaincostsintheuncon-strainedscenariowereabit lowerthanthoseinthe41–49%MC,andthe41–43%MCconstrainedscenarios.Thiswasbasicallyduetothebalancedproportionofstemwoodinrelationtowholetreesandstemlogging

Fig. 5 Supply chain costs per solid m3 (left) and MWh (right) by operational activity in the three MC scenarios analysedSlika 5. Troškovi lanaca dobave u tri različita scenarija

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residues,andthelowersupplychaincostsassociated.Due to itshighharvestingand storage costs, stemwoodvolumewasmarginalinthe41–49%MCsce-nario,andwasnilwhenMCwasconstrainedtoatight41–43%.OnaperMWhbasis,therewasnomajordif-ferenceinsupplychaincostsbetweenthethreesce-narios,althoughchippingandstoragecostswerebig-gerinthe41–43%MCscenario.Totaltransportationcostsweresimilarinthethreesupplychains.Despitethefactthattransportationcostperkmwascheaperforloggingresidues,thelongerdistanceassumedforthissupplychainoffsetthesavingsthatresultedfromalowercostperkm.

3.2 Effect of drying period limits on supply chain costs – Utjecaj vremena sušenja materijala na troškove lanca dobave biomaseFig.6showsthetotalvolumeharvestedintheyear

1and2forwholetrees,stemwood,andloggingresi-dues,whenthedryingperiodwaslimitedtoamaxi-mumof6andaminimumof3months,andcomparedtotheunconstrainedscenario.Intheunconstrainedscenario,stemwoodandwholetreeswerethepre-dominantmaterials,accounting forapproximately47%and34%ofthetotalvolumeharvestedintheyear1and2,respectively.Itisclearthatincreasingthestor-

Fig. 6 Volume harvested of whole trees, stem wood, and logging residues, when the drying period is limited to a min. of 3 months (a), max. of 6 months (b), and unconstrained (c)Slika 6. Obujam posječenih stabala, debala i drvnoga ostatka kada je vrijeme sušenja materijala najmanje 3 mjeseca (a), najviše 6 mje-seci (b) i bez ograničenja (c)

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age(drying)periodtolowertheMCofthebiomassmaterialsfavorstheproductionofwholetreesandloggingresidues,sincethehighharvestingandstor-agecostsofstemwoodprecludetheproductionanddeliveryofthismaterialtotheenergyplant.Forex-ample,whenstoragewaslimitedtoamaximumof6months,wholetreesandloggingresiduesaccountedfor10.2%and89.0%ofthetotalvolumeharvested,respectively.Thesamepatternwasobservedwhenstoragewasconstrainedtoaminimumof3months.Inthiscase,wholetreesandloggingresiduesaccount-edfor8.2%and91.8%ofthetotalvolumeharvested,respectively.Intermsoftheaveragestorageperiod,mostofthe

volumeofstemwoodisonlystoredforareducednumberofperiods. In theunconstrainedscenario,79%ofthestemwoodvolumeisstoredforlessthanonemonth,whereaswhenthemaximumstoragepe-riodisconstrainedto6months,90%ofthevolumeisstoredforlessthanonemonth.Inthecaseofwholetrees,shorterstorageperiodsareobtainedintheun-constrainedscenarioandwhenthestorageperiodisconstrainedtoamaximumof6periods.Inthesetwoscenarios,100%of thevolumeharvestedofwholetreesisstoredforlessthan5months,andahighpro-portionofthismaterial(about75%ineachscenario)isnotstoredattheroadsidebutdeliveredtotheplantrightaftertheharvesting.Conversely,loggingresi-dues are stored for longer periods. In the uncon-strainedscenario,52%of thevolumeharvestedofloggingresiduesisstoredforaperiodbetween10and12months.Likewise,whenthedryingperiodiscon-strainedtoaminimumof3months,100%ofthevol-umeharvestedofloggingresiduesisstoredforape-riodlongerthan8months,withamaximumandanaveragestorageperiodof22and12months,respec-tively.Thelongerstorageperiodofloggingresiduesisexplainedbythelowerharvestingcosts,aswellasbythelowerstoragecosts,whicharecalculatedastheinterest chargeon theharvestingand transport toroadsidecosts.Despitethedifferencesinproductionthatresulted

fromtheconstraintsaddedtolimitthestorageperiod,nosubstantialdifferencesinsupplychaincostswereobservedacrossthescenarios.Incomparisonwiththeunconstrainedscenario,thecostperm3andperMWhonlyincreasebylessthan1%whenthestorageperiodislimitedtoamaximumof6monthsortoaminimumof3months.Theseresultsindicatethatthevolumedistributionofthebiomassmaterialsisquitesensitivetothestorageperiod,althoughnomajordifferencesareobtainedintermsofthesupplychaincostsperm3 harvested.

3.3 Effect of more efficient drying methods on supply chain costs – Utjecaj djelotvornijih načina sušenja biomase na troškove lanca dobaveThepositiveeffectofproperpiling,covering,and

handlingmethods,tolowertheMCandmaintainthelowerMCoverthewintermonthshasbeennotedinseveralearlierstudies(Ryan2009;Anheller2009;Rös-eretal.2011).Thesemethodsprovidedirectfinancialbenefitsbyincreasingtheenergycontentandfacilitat-ingamoreefficientchippingandgrindingoperation.Table4presentstheresultsofsimulatedcoveringonsupplychaincosts.Whenthedryingratesofthemate-rialsareadjustedby10%and15%(lessrewettinginautumnandwintermonths),supplychaincosts in-creasebyabout€0.43/m3and€0.81/m3,respectively.Thisriseisbasicallyexplainedbytheadditionofcover-ingcostsaswellasthehigherchippingcostsofwholetrees(thepredominantbiomassmaterialinbothsce-narios)thatresultfromalowerMC.Tosomeextent,thegreatercostisalsoexplainedbytheharvestingcostsofwholetreesandstemwood.Intheunconstrainedsce-nario,thesolutionincludesasubstantialvolumeoflog-gingresidues,duetotheirlowerharvestingcostsincomparisonwithwhole treesand logging residues.Conversely,whenthedryingratesofthebiomassma-terialsareadjustedby10%and15%,thesolutionpre-cludestheharvestofloggingresiduesbecauseoftheirhighchippingandtransportationcosts,andthepro-curementsystemreliesentirelyonwholetreesandstemwood.Althoughthetotalsupplychaincostsperm3 solidincreasewhentheMCisadjustedby10%and15%,theresultsoftheanalysisshowthatonaperMWhbasis,thesecostsareoffsetbythehigherenergycontentofwholetreesandloggingresidues,andoverall,thecoveringofbiomassmaterialsdoesnotresultinanysubstantialchangeinthetotalsupplychaincostsperMWh.Theuseofmoreefficientmethodshasanim-portanteffectonthevolumeofbiomassmaterialsthatneedtobeharvestedtomeetthemonthlydemandoftheenergyplant.Whencomparedtoascenariowithnostorage,areductioninthevolumeharvestedofupto33%(fromabout406000m3to269000m3)canbeachievedifproperdryingmethods,suchascoveringofbiomassmaterial,areimplementedbeforechippinganddeliveringthebiomassmaterialstotheenergyplant.

4. Conclusions – ZaključciInthisstudy,alinearprogramming-basedoptimal

decisionsupporttool,namedBIOPLAN,hasbeende-velopedandimplementedtoassesstheeffectofbio-

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236 Croat. j. for. eng. 33(2012)2

massmoisturecontentonsupplychaincosts.Incom-plex supply chains, there are a number of factorsassociatedwiththeproductionandprocurementofbio-massmaterialstoenergyplantsthatdrivethesolutionswhenusinganoptimizationapproach.Theseconsider-ationshavetobetakenintoaccountbylogisticsplan-nersiffuelprocurementfromforestsandenergypro-ductionat theplantare consideredsimultaneously.Gettingabetterunderstandingofthetradeoffsassoci-atedwiththestorageofbiomassmaterialsbeforetheyaredeliveredtoenergyandheatingplantsiskeytomeettheenergydemandatminimumcost.Thesecon-siderationsincludeanunderstandingoftheeffectofthelengthof time instorageanditspositive impactontransportcostsandtheefficiencyattheplant,aswellasthenegativeimplicationssuchasbiomassmaterialde-composition,higherchippingandstoragecostsassoci-atedwiththecapitalthatisboundtothestorages.Resultsofthisstudyindicatethatinthemajorityof

thescenariosassessed,wholetreesandloggingresi-duesarethepredominantdeliveredbiomassmaterialtotheCHPplant.Thisistheresultofthelowerhar-vestingcostsandthehigherenergycontentassociatedwiththisbiomassmaterials.Thelowerharvestingandstoragecostsof loggingresiduesallows for longerstorageperiodsasopposedtowholetreesandstemwoodwhicharemostlystoredforshortperiods.Inconstrainedscenarios(includingalimitoftheMCofthebiomassmaterialsdeliveredtotheplant,andalimitofthestorageperiod),thesolutionprecludestheproductionofstemwoodduetoitshighharvestingandstoragecostsandlowerheatingvalueincompar-isontologgingresiduesandwholetrees.Inregardtothevolumeofbiomassmaterialsrequiredtomeetthemonthlydemandoftheenergyplant,areductionof

upto33%canbeachievedifcoveringofbiomassma-terialisimplementedbeforechippinganddeliveringthebiomassmaterialstotheenergyplant.Despitethelimitationsofourstudy(limitednum-

berofsupplychains,samedryingcurvesforallthebiomassmaterial,genericparametersineachsupplychain),theresultsofthestudyshowtheimportanceofcountingonoptimaldecisionsupporttoolsthatallowsfortheassessmentofkeyfuelqualityattributesandtheireffectonsupplychaincosts.

Acknowledgements – ZahvalaTheauthorsthankthefollowingpeopleandinsti-

tutionsfortheirsupportincarryingoutthisresearchproject:

ÞAFORA –University of the SunshineCoast,Australia,

ÞMETLA,Joensuu,Finland,ÞUniversityofEasternFinland,Joensuu,Finland,ÞFORTUM,Joensuu,Finland.

5. References – LiteraturaAnheller,M.,2009:Biomasslossesduringshort-termstorageofbarkandrecoveredwood.DepartmentofEnergyandTechnologyUppsala.SwedishUniversityofAgriculturalSciences,FacultyofNaturalResourcesandAgriculturalSci-ences,DepartmentofEnergyandTechnology.Examensar-beteISSN1654-9392.

Asikainen,A.,Ranta,T.,Laitila,J.,Hämäläinen,J.,2001:Hak-kuutähdehakkeenkustannustekijätjasuurimittakaavaisenhankinnanlogistiikka(Costfactorsandlargescaleprocure-mentofloggingresiduechips).In:Researchnotes131.Uni-versityofJoensuu,FacultyofForestry;(InFinnish).

Table 4 Costs per m3 and MWh by operational activity for different rewetting rate scenariosTablica 4. Troškovi različitih radnih aktivnosti po scenarijima

Unconstrained – Bez ograničenja 10% LRR* 15% LRR**

Activity – Radnje €/m3 €/MWh €/m3 €/MWh €/m3 €/MWh

Harvesting – Pridobivanje drva 13.19 7.04 13.87 7.32 13.43 6.94

Storage – Skladištenje 0.24 0.13 0.15 0.08 0.15 0.08

Covering – Prekrivanje 0.35 0.18 0.35 0.18

Chipping – Iveranje 4.02 2.15 4.11 2.17 4.79 2.48

Transport – Prijevoz 6.99 3.74 6.39 3.37 6.54 3.38

Total – Ukupno 24.44 13.06 24.87 13.13 25.25 13.06

*10% lower rewetting rate – * 10 % niži udio vlaženja**15% lower rewetting rate – ** 15 % niži udio vlaženja

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Brand,M.A.,BolzondeMuñiz,G.I.,Ferreira,W.,Brito,J.O.,2011:Storageasatoolto improvewoodfuelquality.BiomassandBioenergy35(7):2581–2588.

Energiateollisuus,2011:DistrictHeatinginFinland2010.Energiateollisuusry(FinnishEnergyIndustries).ISSN0786-4809,ET-Kaukolämpökansio7/6.72p.Availableat:http://www.energia.fi/sites/default/files/district_heating_in_fin-land_2010_web.pdfEriksson,L.O.,Bjoerheden,R.,1989:Optimalstoring,trans-port andprocessing for a forest-fuel supplier.EuropeanJournalofOperationalResearch43(1):26–33.Gautam,S.,Pulkki,R.,Shahi,Ch.,Leitch,M.,2012:Fuelqual-itychangesinfulltreeloggingresidueduringstorageinroadsideslashpilesinNorthwesternOntario.BiomassandBioenergy42:43–50.Gunnarsson,H.,Rönnqvist,M.,Lundgren,J.,2004:Supplychainmodellingofforestfuel.EuropeanJournalofOpera-tionalResearch158(1):103–123.Hakkila,P., 1962:Polttohakepuunkuivuminenmetsässä.Summary:Forestseasoningofwoodintendedfotfuelchips.CommunicationesInstitutiForestalisFenniae54.4.82p.Hakkila,P.,2004:Developingtechnologyforlarge-scalepro-duction of forest chips.Wood Energy Technology Pro-gramme1999-2003,Finalreport.Helsinki99p.Heikkilä,J.,Laitila,J.,Tanttu,V.,Lindblad,J.,Sirén,M.,Asi-kainen,A.,Pasanen,K.,Korhonen,K.T.,2005:Karsitunen-ergiapuunkorjuuvaihtoehdotjakustannustekijät.[Harvest-ingalternativesandcostfactorsofdelimbedenergywood].Metlantyöraportteja/WorkingPapersoftheFinnishForestResearchInstitute10.56p.(InFinnish).Kanzian,C.,Holzleitner,F.,Stampfer,K.,Ashton,S.,2009:Regionalenergywoodlogistics–Optimizinglocalfuelsup-ply.SilvaFennica43(1):113–128.Laitila,J.,2006:Costandsensitiveanalysistoolsforforestenergyprocurementchains.ForestStudies/Metsandusli-kudUurimused45:5–10.ISSN1406-9954.Laitila,J.,2008:Harvestingtechnologyandthecostoffuelchipsfromearlythinnings.SilvaFennica2008,42(2):267–283.Laitila,J.,2012:Methodologyforchoiceofharvestingsystemforenergywoodfromearlythinning.DissertationesFores-tales143.68p.Availableat:http://www.metla.fi/dissertatio-nes/df143.htm

Laitila,J.,Heikkilä,J.,Anttila,P.,2010:Harvestingalterna-tives,accumulationandprocurementcostofsmall-diameterthinningwoodfor fuel inCentral-Finland.SilvaFennica44(3):465–480.Laitila,J.,Väätäinen,K.,2011:Kokopuunjaranganautokul-jetus jahaketustuottavuus.Metsätieteenaikakausikirja2:107–126.Laurila,J.,Lauhanen,R.,2012:Weightandvolumeofsmall-sizedwholetreesatdifferentphasesofthesupplychain.ScandinavianJournalofForestResearch27(1):46–55.Nurmi,J.,1993:Heatingvaluesoftheabovegroundbiomassofsmall-sizedtrees.ActaForestaliaFennica236.30p.Pettersson,M.,Nordfjell,T.,2007:Fuelqualitychangesdur-ingseasonal storageof compacted logging residuesandyoungtrees.BiomassandBioenergy31(11–12):782–792.Röser,D.,Erkkilä,A.,Mola-Yudego,B.,Sikanen,L.,Prinz,R.,Heikkinen,A.,Kaipainen,H.,Oravainen,H.,Hillebrand,K.,Emer,B.,Väätainen,K.,2010:Naturaldryingmethodstopromote fuelqualityenhancementofsmallenergywoodstems.Metlantyöraportteja/WorkingPapersoftheFinnishForestResearchInstitute186.60p.ISBN978-951-40-2279-1.Available at: http://www.metla.fi/julkaisut/workingpa-pers/2010/mwp186.htm.Röser,D.,Mola-Yudego,B.,Sikanen,L.,Prinz,R.,Gritten,D.,Emer,B.,Väätäinen,K.,Erkkilä,A.,2011:NaturaldryingtreatmentsduringseasonalstorageofwoodforbioenergyindifferentEuropeanlocations.Biomass&Bioenergy35(10):4238–4247.Ryan,M.,2009:Qualityissuesintheforestbiomasssupplychain.In:CanbioAnnaualconference.Oct.20-21,2009.Ed-monton,Canada.Presentationavailableat:http://canbio.ca/upload/documents/edmonton09ryans.pdfSikanen,L.,Röser,R.,Anttila,P.,Prinz,R.,2012:Forecastingalgorithmfornaturaldryingofenergywoodinforeststor-ages.PapertobesubmittedtotheJournalofForestEnergy(inpress)Tahvanainen,T.,Anttila,P.,2011:Supplychaincostanalysisoflong-distancetransportationofenergywoodinFinland.BiomassandBioenergy35(8):3360–3375.

Sažetak

Predviđanje i praćenje sadržaja vlage radi poboljšanja u logistici pridobivanja biomase

Kako bi se zadovoljila sve veća potražnja za šumskom biomasom, moraju se usavršiti pravilne tehnologije prido­bivanja biomase (uključujući usitnjavanje, rukovanje i skladištenje biomase) radi proizvodnje biogoriva visoke kakvoće. Potrebno je bolje poznavanje skladištenja biomase prije nego što se ona dopremi na glavno stovarište ili u energanu kako bi se postigli viši energijski učinci uz manje troškove. To uključuje poznavanje razdoblja skladištenja biomase s

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238 Croat. j. for. eng. 33(2012)2

mogućim pozitivnim utjecajem na troškove prijevoza i energijsku učinkovitost u energani, te predviđanje mogućih negativnih učinaka kao što su razlaganje drvnoga materijala i viši troškovi iveranja i skladištenja nastalih zbog ve­zanoga kapitala u skladištima.

Najvažnija značajka kakvoće iverja ili sirovine za proizvodnju iverja jest udio vlage (MC). Ona utječe na toplin­sku vrijednost, svojstva skladištenja, troškove iveranja i prijevoza. Za procjenu utjecaja sadržaja vlage biomase na troškove lanca dobave razvijen je alat (linearno programiranje) za potporu odlučivanja koji smanjuje troškove lanca dobave, uključujući troškove pridobivanja biomase, skladištenja, iveranja i prijevoza. Pri istraživanju je korištena postojeća bioenergana u Finskoj te su proučena tri lanca dobave biomase: biomasa od cijelih stabla iz ranih proreda, deblovina iz ranih proreda i šumski ostatak iz dovršnoga sijeka. Najveći udio biomase bio je iz cijelih stabala te iz drvnoga ostatka (zbog nižih troškova pridobivanja i više energijske vrijednosti). Niži troškovi pridobivanja i skladištenja drvnoga ostatka omogućuju dulje razdoblje skladištenja, za razliku od skladištenja cijelih stabala i deblovine koji se uglavnom skladište u kraćim razdobljima. Prilikom postavljenih ograničenja u pridobivanju biomase (uključujući granične vrijednosti udjela vlage te dopuštenoga vremena skladištenja) isključuje se proizvodnja biomase iz deblovine zbog troškova pridobivanja i skladištenja te niže energijske vrijednosti. Moguće je smanjiti mjesečnu potražnju en­ergane za biomasom za 33 % ako bi se materijal pokrivao prije samoga iveranja i prijevoza.

Unatoč ograničenjima u istraživanju (ograničen broj lanaca dobave, iste krivulje sušenja biomase, generički parametri u svakom lancu dobave) rezultati istraživanja pokazuju važnost pravoga alata za podršku odlučivanju koji omogućuje procjenu ključnih značajki te njihov utjecaj na troškove lanca dobave biomase.

Ključne riječi: udio vlage, lanac dobave biomase, razdoblje skladištenja i prijevoza, linearno programiranje, prekrivanje biomase

Received(Primljeno):July20,2012Accepted(Prihvaćeno):August19,2012

Authors’address– Adresa autorâ:

MauricioAcuna,PhD.e-mail:macuna@usc.edu.auAFORA–UniversityofSunshineCoastPrivatebag12Hobart,TASAUSTRALIAPerttuAnttila,PhD.e-mail:perttu.anttila@metla.fiRobertPrinz,MSc.e-mail:robert.prinz@metla.fiProf.AnttiAsikainen,PhD.e-mail:antti.asikainen@metla.fiFinnishForestResearchInstituteP.O.Box68FI-80101,JoensuuFINLANDProf.LauriSikanen,PhD.e-mail:lauri.sikanen@uef.fiUniversityofEasternFinlandP.O.Box111FI-80101,JoensuuFINLAND