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
M. Acuna et al. Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics (225–238)
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
M. Acuna et al. Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics (225–238)
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
Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics (225–238) M. Acuna et al.
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
M. Acuna et al. Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics (225–238)
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
Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics (225–238) M. Acuna et al.
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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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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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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:[email protected]–UniversityofSunshineCoastPrivatebag12Hobart,TASAUSTRALIAPerttuAnttila,PhD.e-mail:[email protected],MSc.e-mail:[email protected],PhD.e-mail:antti.asikainen@metla.fiFinnishForestResearchInstituteP.O.Box68FI-80101,JoensuuFINLANDProf.LauriSikanen,PhD.e-mail:[email protected],JoensuuFINLAND