Dual-Control of Autothermal Thermophilic Aerobic Digestion Using Aeration and Solid Retention ...

15 Pages·2017·2.87 MB·English

water
Article
Dual-Control of Autothermal Thermophilic Aerobic
Digestion Using Aeration and Solid Retention Time
SilvanoNájera*,MontserratGil-MartínezandJavierRico-Azagra
ElectricalEngineeringDepartment,UniversityofLaRioja,c/SanJosédeCalasanz31,26004Logroño,Spain;
[email protected](M.G.-M.);[email protected](J.R.-A.)
* Correspondence:[email protected];Tel.:[phone]
AcademicEditor:JoséManuelPoyatos
Received:11March2017;Accepted:9June2017;Published:13June2017
Abstract: Autothermal thermophilic aerobic digestion (ATAD) is an advanced sewage sludge
treatmentwhichallowscompliancewithincreasinglydemandingregulations. Concerningsludge
pasteurization,acertainaveragetemperaturemustbeassuredinthedigesterduringbatchtreatment.
Aerationflowisthevariablemostmanipulatedtoregulatethedigestertemperature.Additionally,the
manipulationofthebatchsludgeflow—whichisrelatedtothesolid-retention-time—isconsideredto
improvetemperatureregulationdespitevariationsinairandsludgetemperaturesandthevariability
ofrawsludgeorganiccontent. Thus,adual-inputcontrolstructurewasprovidedwheretheaeration
and solid-retention-time contributed as faster and slower inputs, respectively. Two controllers
intervened,andtheset-pointforthebatchaveragetemperaturewaschosentomeettheminimum
effluentqualityestablishedbytheUSregulationsorEuropeanrecommendations,consideringthat
lowersetpointtemperaturessaveaerationcosts. Aset-pointfortheaerationallowedustoachieve
anextragoal,whichaimedateitherreducingoperationcostsorincreasingproductionrates. Thetwo
feedbackcontrollersweredesignedfollowingtherobustcontrolmethodologyknownasquantitative
feedback theory (QFT). Improvements were compared with single-input (aeration-flow) control
strategyandopen-loopcontrolstrategy. Simulationswereperformedonabenchmarknon-linear
simulationmodelforATAD.
Keywords:AutothermalThermophilicAerobicDigestion(ATAD);sludgepasteurization;wastewater
treatment(WWT);mid-rangingcontrol;quantitativefeedbacktheory(QFT);processcontrol
1. Introduction
Newregulationsintheincreasinglystringentwastewatertreatmentsectorpromotetheuseof
advancedwastewaterandsludgetreatments. Thesludgethatisobtainedinwastewatertreatments
is rich in nutrients and organic matter, which makes it reusable as a soil fertilizer [1] after proper
processing. Autothermalthermophilicaerobicdigestion(ATAD)isareferencetechnologyforsludge
stabilizationandpasteurization[2,3]. ATADtreatmentisbasedontheaerationoftherawsludgein
aclosedreactorforaspecifiedretentiontime. Whensludgepasteurizationismandatory,thedigester
isusuallyoperatedinbatch-mode(asequenceoffeeding-reaction-withdrawalthatisrepeatedbatch
afterbatch)toavoidhydraulicshortsandensuretime-temperatureconditions. Bysupplyingasuitable
amountofair,severalbiochemicalreactionsconsumetheorganicmattercontentinthesludge,which
reducesthepotentialofthesludgetoattractdiseasevectors(insects,rodents,birds,etc.)[4].Exothermic
reactionsgenerateheat,whichmaintainsthereactortemperatureataround55◦Cwithouttheneed
to apply external heat energy. The high temperature during the batch time reduces the pathogen
concentrationinthesludge[5–7].
Thecontrolofthereactionisvitaltoachievingproperstabilization(vectorattractionreduction)
andpasteurization(pathogenreduction)levelsaspertheregulationsandrecommendationsguidelines.
Water2017,9,426;doi:10.3390/w9060426 www.mdpi.com/journal/water
Water2017,9,426 2of15
ThestandardsbytheUSEnvironmentalProtectionAgency(USEPA)[4,8]andtheEUCommission[9]
wereconsidered. SeveralATADcontrolapproacheshavebeenproposedinthescientificliterature.
Breideretal.[10]describedanintuitivewaytoregulatethedigestertemperaturethroughaerationflow.
KimandOh[11]developedacontrolmethodusingfluorescencemonitoringofthebiologicalactivityto
searchforaerationsavings. Warehametal.[12]pursuedthebeststabilizationlevelandconsideredthe
oxidation-reduction-potential(ORP)tocutoffaeration. Zambrano[13]non-linearlyvariedtheaeration
duringthebatchbasedontheslopeofthetemperatureevolution,whichaimedtoobtainmaximum
organicmatterdegradationwithoutexcessiveaeration. Withthesameobjectives,Nájeraetal.[14]
proposedafeedbackcontrolstructurewhosecontrollerwasdesignedfollowinglinearrobustcontrol
techniques.Garcíaetal.[15]comparedATADasasingletreatmentwithdualATADandpost-anaerobic
digestion, where both layouts looked for a medium level of stabilization. Nájeraetal.[16] also
consideredthetreated-sludgequality,thetreatment-cost,andtherateoftreated-sludgetopropose
differenttrade-offcontrolstrategies. Sincerelativelysmallthermophilictemperaturescomplywiththe
pasteurizationcriteria,pasteurizationisacommongoalinallATADcontrolapproaches. Thestudyof
thisgoalisrelevantinboththesingleATADanddualconfiguration;thelattercanincludeasecond
aerobicoranaerobicstage[17].
To carry out any control strategy, the digester temperature is practically the only robust
on-line measurable variable that provides relevant information regarding the digestion status.
Theregulationofthetemperaturetoarequiredset-pointmostlyusesaerationflow,whichprovides
majorcontrollability[10]. Inaddition,thesludgeflowcanalsobemanipulated. Inthebatchoperation,
thesolid-retention-timeispreferredtodescribethesludge-flowmanipulationandcanbeachieved
bychangingeitherthebatchtimeorthesludgevolumetreatedperbatch. Nájeraetal.[16]discussed
theinfluenceofbothcontrolvariables(air-flowandsolid-retention-time)inthedigestertemperature,
andeventuallyinthequalityofthetreated-sludge,intheoperation-costandrateoftreated-sludge
(production-rate).
Theuseofmultiplemanipulatedinputsiswidelyusedinprocesscontrol[18–21].Theinvolvement
oftwocontrolvariablesinsidethefeedbackcontrolstructuresallowstheachievementoftwocontrol
objectives. Inthiswork,onecontrolobjectivewastemperatureregulationtoaspecifiedset-pointthat
wasconvenientlyselectedtoensuretherequiredsludgequality. Theothercontrolobjectivewasthe
regulationofair-flowtoaspecifiedset-pointthatwasselectedtoachievedifferentgoals. Theobvious
goalwastosaveaeration-costsbyreducingtheaerationset-point. Ontheotherhand,higheraeration
set-pointsforthesamedigestertemperaturewouldreducethesolid-retention-time. Next,asecond
goalwastoincreasetheproduction-ratebyincreasingtheaerationset-point. Theindirectregulationof
theproduction-ratewouldbeusefultoadaptthedigestersludge-flowtocircumstancesupstreamor
downstream(e.g.,possiblepre-holdingtanklevelnearitslimits).Assmallerdigestertemperaturessave
aerationcosts,thetemperatureset-pointwasfixedtotheminimumvaluetomeettheUSEPA(orEU)
recommendation for pasteurization [8,9]. The result of low thermophilic digestion temperatures
is poor stabilization. Anaerobic digestion [22] would complete the treatment at a second stage.
Nevertheless,largertemperatureset-pointsfavorsludgestabilization(volatilesolidsreduction),butdo
notnecessarilyassuretheregulation[4,8]fulfilment.
From a dynamic point of view, both the aeration-flow and the solid-retention-time cooperate
in the digester temperature regulation. This temperature is disturbed by the variability of air
and sludge temperatures, or by the variability of the organic content of the inlet sludge, amongst
others. Thus,robustcontrollersweredesignedbasedonquantitativefeedbacktheoryprinciples[23].
Theirparticularitiesfortwo-inputone-outputstructuresaredetailedinRico-Azagraetal.[24].
AnATADbenchmarksimulationmodel[13,25]wasusedforthestudyofthedigesterbehavior,
forthevalidationofthecontrolstructure,andforevaluationsandcomparisons.
Theremainderofthepaperisorganizedasfollows. Section2studiestheinfluenceofair-flow
andsolid-retention-timeonthedigestertemperature,andthecontrolstrategiesaredefined,asisthe
dual-controlstructureusedtoachievethem. AppendixAthoroughlydescribesthemethodusedto
Water 2017, 9, 426 3 of 15
The remainder of the paper is organized as follows. Section 2 studies the influence of air-flow
Water2017,9,426 3of15
and solid-retention-time on the digester temperature, and the control strategies are defined, as is the
dual-control structure used to achieve them. Appendix A thoroughly describes the method used to
ddeessiiggnn tthheer orobbuuststc ocnotnrotrlolelrles.rsS.e Scteicotnio3ne v3 aeluvaatleusatthese ethxpe eecxtepdecpteerdf oprmerafonrcmeoanfcthe eodf utahle-c odnutarol-lcwonhterroel
qwuhaelritey ,qcuoastl,itayn, dcopsrto, dauncdti opnriondduecxteiosna rienedveaxleusa taerde toevsahlouwatethde tiom pshroovwe mtheen tsimveprrsouvsesminegnltes- cvoenrtsruosl
asinndglme-acnounatrloclo anntrdo ml.aInnuSaecl tcioonnt4ro,lt.h Ienm Seacintiocnon 4c, ltuhseio mnsaianr ecopnrcelsuesnitoends. are presented.
2. MaterialsandMethods
2. Materials and Methods
2.1. Steady-StateAnalysisoftheATAD
2.1. Steady-State Analysis of the ATAD
Currentbenchmarksimulationmodels(BSMs)[26]wereextendedtoATADtechnologythrough
Current benchmark simulation models (BSMs) [26] were extended to ATAD technology
thebenchmarksimulationmodelAT_BSM[13,25]. ThiswasusedinthisworkfortheATADanalysis,
through the benchmark simulation model AT_BSM [13,25]. This was used in this work for the ATAD
andforthesimulationandvalidationoftheproposedcontrolstrategies.
analysis, and for the simulation and validation of the proposed control strategies.
In AT_BSM, the digester (Figure 1a) was modeled as a tank with two completely-stirred
In AT_BSM, the digester (Figure 1a) was modeled as a tank with two completely-stirred
volumes(liquidandgaseousphases). Biologicalreactionsandenergybalanceswereconsidered[27].
volumes (liquid and gaseous phases). Biological reactions and energy balances were considered [27].
Thebiochemicalmodel(Figure1b)wasbasedonthestandardASM1withslightmodificationstomake
The biochemical model (Figure 1b) was based on the standard ASM1 with slight modifications to
itconsistentwithobservationsfromtheATADreactors(acid-basereactionsandliquid-gastransfers).
make it consistent with observations from the ATAD reactors (acid-base reactions and liquid-gas
Temperatureevolutionwasobtainedthroughthesystemenergybalance,whichconsideredseveral
transfers). Temperature evolution was obtained through the system energy balance, which
heatfluxesinvolvedintheprocess: influentandeffluentheatenergy,heatfluxesthroughwallsand
considered several heat fluxes involved in the process: influent and effluent heat energy, heat fluxes
gas-liquid surface, and heat transfer from the mixing equipment. A total number of 24 dynamic
through walls and gas-liquid surface, and heat transfer from the mixing equipment. A total number
variableswereincludedinastate-spacemodel[13]. A24h(1day)cyclesequencewasestablished
of 24 dynamic variables were included in a state-space model [13]. A 24 h (1 day) cycle sequence was
inAT_BSM:0.5hforsewagefeeding;23hforreaction(aeratedreactionphase);and0.5hforsludge
established in AT_BSM: 0.5 h for sewage feeding; 23 h for reaction (aerated reaction phase); and 0.5 h
withdrawal. Duringeachcycle(batch),aportionofthetotalreactorvolume(V =2350m3)was
for sludge withdrawal. During each cycle (batch), a portion of the total reactor vAoTAluDme (VATAD = 2350
drainedandfilled. Next,thesolidsretentiontime(SRT)isgivenby:
m3) was drained and filled. Next, the solids retention time (SRT) is given by:
SRSTRT==VVQAATTAADD (1(1) )
Qraw
raw
where Q isthemeaninfluentflowperbatch. Themeaneffluentflowperbatch Q isequalto
where Qrraaww is the mean influent flow per batch. The mean effluent flow per batch Qout iso uetqual to Qraw
Q minus the evaporation shrinkages. For a stable operation of the digester, SRT can be moved
mrianwus the evaporation shrinkages. For a stable operation of the digester, SRT can be moved over
over 10–15d(day). The ability to change SRT involves the existence of a pre-holding tank [13] to
10–15 d (day). The ability to change SRT involves the existence of a pre-holding tank [13] to regulate
regulatetheinfluentflowandtoabsorbfluctuationsoftheoutletflow. Theinfluentdefinitionconsists
the influent flow and to absorb fluctuations of the outlet flow. The influent definition consists of: (i) a
of: (i)aconstantcompositiongivenbysimulationsofthebenchmarksimulationmodelNo.2(BSM2)
constant composition given by simulations of the benchmark simulation model No.2 (BSM2)
evaluatedbyVreckoetal.[28];and(ii)asignificantvariabilityofthebiodegradablecontent. Departing
evaluated by Vrecko et al. [28]; and (ii) a significant variability of the biodegradable content.
from an exhaustive analysis of the raw sludge in the BSM2, 2/3 parts of the mixed raw sludge
Departing from an exhaustive analysis of the raw sludge in the BSM2, 2/3 parts of the mixed raw
were due to the slowly biodegradable substrate (X ) [13]. For simplicity, X was used as the
sludge were due to the slowly biodegradable substratse,in (Xs,in) [13]. For simplicity, sX,ins,in was used as the
principalindicatortoquantifythebiodegradableorganicmattercontentintherawsludge. Thesludge
principal indicator to quantify the biodegradable organic matter content in the raw sludge. The
temperatureT andtheairtemperatureT consideredlong-termandshort-termvariations[13].
sludge tempesrlaudtugere Tsludge and the air temaiprerature Tair considered long-term and short-term
ThemeanaerationflowperbatchQ wasratedupto65,000m3/d.
variations [13]. The mean aeration flaow per batch Qa was rated up to 65,000 m3/d.

(a) (b)
FFiigguurree 11..A Autuottohtehremrmalatlh ethrmerompohpilhicilaice roabericobdiicg edstiigoenst(iAonTA (DA)T(Aa)DS)c h(eam) eScohfetmheep orof cethsse apnrdovceasrsia balneds;
avnadria(bbl)eMs; aainndb (iboc) hMemainic abliorechacetmioincas.l SreRaTc:tisoonlisd. sSRreTte: nsotiloidnst irmetee.ntion time.
WWaatteerr 22001177,, 99,, 442266 44 ooff 1155
Regulation tasks on AT_BSM were performed on the batch average temperature Tavg.
RegulationtasksonAT_BSMwereperformedonthebatchaveragetemperatureT .Manipulated
Manipulated variables SRT and Qa remained constant for the 1-day batch time, and wavegre updated by
variablesSRTandQ remainedconstantforthe1-daybatchtime,andwereupdatedbythecontrol
the control law batcha after batch. Therefore, constant manipulated inputs were considered for the
law batch after batch. Therefore, constant manipulated inputs were considered for the present
present steady-steady analysis. Tavg was on-line computed as the mean value of Ni = 1,440 records of
steady-steady analysis. T was on-line computed as the mean value of N = 1440 records of
instantaneous temperaturea vTgi. These were captured during the 1-day treatmenit evolution (one Ti
instantaneous temperature T. These were captured during the 1-day treatment evolution (one T
sample was taken every minuite). For proper pasteurization, the USEPA [8] establishes a minimumi
samplewastakeneveryminute). Forproperpasteurization,theUSEPA[8]establishesaminimum
time D (d) as a function of the sludge temperature Ti (°C), which is expressed by:
timeD(d)asafunctionofthesludgetemperatureT (◦C),whichisexpressedby:
i
50,070,000
D= (2)
501,0007.104T,i000
D = (2)
100.14Ti
In contrast, the European Commission [9] recommends that the temperature inside the reactor
shoulIdn bcoe notvraers t5,5th °eCE fuorr oapt eleaansCt 2o0m hm wisitshioonut[ 9a]drmecioxmtumree onrd wsitthhadtrtahweatle mdupreinragt utrreeaitnmseidnet. tFhuecrhesa actnodr
Fshuocuhsld [2b9e] oavsseerr5te5d◦ Cthfaot rsautffliecaiestn2t 0bahtcwhi-tthimouet aatd am teixmtupreeraotruwrei tbhedtrwaeweanl 5d0u arinndg 7t0re °aCtm asesnut.reFdu crhelsiaabnlde
dFuiscinhfse[c2t9io]na.s Asefrtteerd stehvaetrasul sffiimciuenlattiboantcsh o-nti mAeT_aBtSaMte,m wpee aradtoupretebde Ttwavge esent-5p0oainntds 7a0ro◦uCnads s5u5r °eCd troe lmiaebelet
tdhiesi pnfaesctteiuorni.zaAtfiotenr rseegvuerlaatliosinms.u l ationsonAT_BSM,weadoptedTavgset-pointsaround55◦Ctomeet
thepAasst einu rNizáajteiroan erte gaul. l[a1ti6o]n, os.ur analysis studied the steady-state temperature Tavg reached after 50
days Aast icnonNsátajenrta ceotnadl.it[i1o6n]s, oouf rmaannailpyusilsatsetdu diinepdutths,e asitre aadnyd- stsalutedgteem tpeemrapteurraetuTraevsg, raenadch iendflaufetnert
c5o0mdpaoyssitaiotnc.o Fnisgtuanret 2c osnhodwitiso tnhse orfesmulatns iapruoluantedd thine pteumtsp,eariartaunred osfl uindtgereestet mTapvge =r a5t5u °rCes. ,Aa nwdidien flraunegnet
ocof mmpanoispituiolant.edF iignupruets2, Qsha oawnds SthReT,r ewseurlets aanraolyuznedd.t hAe rteelmatpiveerlayt uhrigeho ofrignatenriecs mt Tatatvegr= co5n5te◦nCt. XAs,inw widaes
friaxnegde toof m30a nkigp/umla3 teind itnhpeu atsn,aQlyasaisn dsoS RthTa,tw tehree arneqaulyizreedd .tAemrepleartaivtuerlye hcioguhldo rgbea npicromvaidtteedr cboyn ttehnet
mXsa,inniwpualsatfiioxned otfo b3o0thk gQ/ma a3nidn tShReTa noavleyrs itshseoirt hreastpthecetirveeq uriarnegdetse. mCpoenrsaitduerreincgo utlhdatb eQpa riosv didireedctblyy
pthreopmoartnioipnualla ttioo ntohfeb oatehraQtiaoann dcoSsRt Taonvde rSthReTir ries spinecvteivrseelrya ngperos.pCorotniosnidale ritnog tthhae tQslaudisgde ireflcotwly
(pprroopdourtcitoinonal-rtaotteh),e oapeeraratitoinngc opsotianntsd oSfR “Tmisiniinmveurmse lcyosptr”o apnodrt i“omnaalxtiomtuhmes plurdodgeucfltoiown”(p arroed huicgtiholnig-rhatteed),
ionp eFrigatuinreg 2p o(sinomtseo fc“umrviensi mhauvme cboesetn” aenxcdlu“dmeadx iimn uFmiguprreo d2bu cstiinocne” tahreeirh iSgRhTli gvhatleudesin wFeirgeu roeu2t (osfo tmhee
rcaunrgvee sohvaevr e10b–e1e5n de)x.c ludedinFigure2bsincetheirSRTvalueswereoutoftherangeover10–15d).
(a) (b)
FFiigguurree 22.. ((aa)) TTaavvgg vvss.. QQaa foforr SSRRTT oovveerr 1100––1155 dd ((XXss,i,nin == 3300 kkgg/m/m3, 3T,aTir a=ir 1=5 1°5C◦, Can,dan TdsluTdgselu =d g1e5= °1C5);◦ aCn)d;a (nbd)
T(bav)g Tvasv.g SvRsT. SfoRrT Qfoa rovQear o1v2e,0r0102–,2080,00–0208 m,003/0dm (X3/s,idn =( X30s, ikng=/m303,k Tga/ir m= 13,5T °aCir, =an1d5 T◦Cslu,dgae n=d 1T5 s°luCd)g.e =15◦C).
TThhee rraattiioo QQa//QQraw rerperperseesnentst sththe eaaerearatitoionn ccoosst tinin aa fafairireerr wwaayy ffoorr aannaallyyssiiss.. IItt iinnddiiccaatteess tthhee aammoouunntt
a raw
of air required per unit of treated sludge. Figure 3 evaluates that ratio for several production rates
ofairrequiredperunitoftreatedsludge. Figure3evaluatesthatratioforseveralproductionrates
from 157 m3/d to 235 m3/d, which corresponded to the SRT from 15 d to 10 d, respectively, as per
from157m3/dto235m3/d,whichcorrespondedtotheSRTfrom15dto10d,respectively,asper
Equation (1). The bar diagram (Figure 3) shows the trade-off between reducing the aeration cost and
Equation (1). The bar diagram (Figure 3) shows the trade-off between reducing the aeration cost
increasing the production-rate. Results are shown for several temperatures. They reveal the
and increasing the production-rate. Results are shown for several temperatures. They reveal the
importance of achieving the strictly required pasteurization temperature to save aeration costs for
importanceofachievingthestrictlyrequiredpasteurizationtemperaturetosaveaerationcostsfor
tthhee ssaammee pprroodduucctitoionn raratet.e T. eTmempepreartuatruer TemTax,st meamnes athnastt thhaet mthaeximmauxmim aucmhieavcahbileev taebmlepetermatupreer a(t6u1r.4e
max,st
°(6C1,. 461◦.C1 ,°6C1,. 160◦.C6 ,°6C0,. 660◦.C45, 6°0C.4, 560◦.C1 ,°6C0,. 159◦.C7, °5C9).7 fo◦rC e)afochr eSaRcTh S(fRroTm(f r1o5m d 1t5o d10t od1, 0reds,preecstpiveecltyiv)e alyn)da fnodr
Xfosr,inX = 20= k2g0/mkg3;/ tmhu3;s,t hTumsa,x,Tst involivnevdo ltvheed btheestb aetsttaainttaabinlea bslteasbtialibzialitzioatnio lnevleevl,e wl,whihcihc hwwasa sddififffeerreenntt ffoorr
s,in max,st
eeaacchh SSRRTT aannddQ Qa (s(seeeeN Náájejrearae teat la.l[.1 [61]6f]o rfofru rftuhretrhedre tdaeiltsa)i.lsT)h. eThaeer aateiroant-iocons-tcosastv isnagvsinwgesr ewaerroeu anrdou3n0%d
a
30% if pasteurization was solely achieved, and was out of scope for this work if this decision
ifpasteurizationwassolelyachieved,andwasoutofscopeforthisworkifthisdecisioncompensated
caopmopste-ntrseaattemd enat foprotsht-etrreeaqtumireendt slfuodr gethseta brileiqzuatiiroend. Tslud=ge5 5◦sCtabainlidzaTtion=. 5T6a.v8g ◦C= d5is5t in°gCu isahnedd
avg avg
Tthaveg m= in5i6m.8u m°Cr edqiustiirnegdutiesmhepde rathtuer emtionmimeuetmth reeUquSiErPeAd atenmdpEeUraptuasrtee utori zmateioent cthriete rUiaS,ErPesAp eacntidv eElyU.
pasteurization criteria, respectively.
Water2017,9,426 5of15
Water 2017, 9, 426 5 of 15
Water 2017, 9, 426 5 of 15

FFiFigigugurureree3 3 .3.A .A Aeereraratatitoiiononnc c ocosoststrt r aratatitoioiov v svs.s.p .p prrorododduuucctctitoiionon-n-r-raratateteef fo fororrs s esevevevereraralalt lte tememmppepereraratautturureresessa a nandnddX X Xs,si,nin == = 22 2000 kk kggg///mmm333. ..
s,in
2.2. Dual-Control System of the ATAD
2.2. Dual-Control System of the ATAD
2.2. Dual-ControlSystemoftheATAD
Two control strategies were attempted to achieve pasteurization temperatures (Table 1): MISO
Two control strategies were attempted to achieve pasteurization temperatures (Table 1): MISO
Twocontrolstrategieswereattemptedtoachievepasteurizationtemperatures(Table1): MISO
COST, which yielded the lowest aeration cost; and MISO PROD, which yielded the highest
COST, which yielded the lowest aeration cost; and MISO PROD, which yielded the highest
COST, which yielded the lowest aeration cost; and MISO PROD, which yielded the highest
production rate. The feedback control structure to accomplish them is shown in Figure 4. One
production rate. The feedback control structure to accomplish them is shown in Figure 4. One
productionrate. ThefeedbackcontrolstructuretoaccomplishthemisshowninFigure4. Onestrategy
ssttrraatteeggyy oorr tthhee ootthheerr wwaass sseelleecctteedd bbyy cchhaannggiinngg tthhee a aeerraattiioonn s seett--ppooiinntt QQaa,r,erfe.f . OOvveerraallll, ,s smmaalllleerr vvaalluueess o off
ortheotherwasselectedbychangingtheaerationset-pointQ . Overall,smallervaluesofQ
QQaa,r,erfe f ssaavvee aaeerraattiioonn ccoossttss, , bbuutt iinnddiirreeccttllyy lleeaadd ttoo hhiigghheerr SSRRTT vvaalluueaes,sr,e ,f wwhhiicchh iinnvvoollvveess lloowweerr pprroodduuccttiaio,ornenf
saveaerationcosts,butindirectlyleadtohigherSRTvalues,whichinvolveslowerproductionrates.
rraatteess. . OOnn tthhee ootthheerr hhaanndd, , hhiigghheerr vvaalluueess ooff QQaa,r,erfe f iinnccrreeaassee tthhee aaeerraattiioonn lleevveellss ttoo eevveennttuuaallllyy ttrreeaatt mmoorree
Ontheotherhand,highervaluesofQ increasetheaerationlevelstoeventuallytreatmoresludge
sslluuddggee ((SSRRTT ddeeccrreeaasseess)). . FFuurrtthheerrmmoorreea,, ,r eQfQaa,r,erfe f ccaann bbee rraatteedd ttoo aaddaapptt tthhee eefffflluueenntt ffllooww ttoo aa sseeccoonndd
(SRT decreases). Furthermore, Q can be rated to adapt the effluent flow to a second treatment
treatment stage, which, for examap,rleef, would consist of an anaerobic digestion for full stabilization.
treatment stage, which, for example, would consist of an anaerobic digestion for full stabilization.
stage,which,forexample,wouldconsistofananaerobicdigestionforfullstabilization. Forthesame
For the same digester temperature, shrinkages by evaporation are larger when solid-retention-times
For the same digester temperature, shrinkages by evaporation are larger when solid-retention-times
digester temperature, shrinkages by evaporation are larger when solid-retention-times are larger.
aarree llaarrggeerr. . TThhuuss, , tthhee ssttrraatteeggyy tthhaatt mmiinniimmiizzeess aaeerraattiioonn ccoossttss ((lleessss QQaa)) aallssoo mmiinniimmiizzeess ttrraannssppoorrtt ccoossttss
Thus,thestrategythatminimizesaerationcosts(lessQ )alsominimizestransportcosts(lessQ ).
((lleessss Q Qoouut)t). . a out
Table1.Controlstrategies.MISO:multipleinputsingleoutput.
Table 1. Control strategies. MISO: multiple input single output.
Table 1. Control strategies. MISO: multiple input single output.
StrictlyQpuaQsQatlueiuutayarlliizittyayt i on CCCoonoHnntitrtAgrorhooelell rAS raSAStt(etitrSerorraiaHraandtHtatteeeitiCegggiioeggooyhyfnhyfsn ee t eCr cCr to ) o sstt PHroPiPgdrHhruoHoecRdiRsdtgiuiatghouat(chnGteecteesti oRsi otoat an l nt) e RUUUReSREgSSeEuUeEEgPlgP:PuaAuTACtAlCeala::ovda :toTTg nteT,Vanreadtevvaadftrggv Sror,,=gV rro,ieVetrlaffer5 al f=ubS =a 6r=S cl.rti5 85ettira55u5srau◦b5u rbIC◦c° lenc°CCtle,Ctue(ssQ,,uFis r ,QdQiI ra egQI,neear naue,( s,rafFr(Fers,eirF=fefeeidi f=e=dig 24e=gd ue6)22 ubF2 ,2r21Far2ee,,05eec5, e0254k e2d442)md4C) b4m b3mo am/a3nc/3dckt/3krdd/ od l MIMLSMLLaOIaabISbbSPeOeeORlll O D
SStrtricictlt(ylGy p (op(GaaGalso)sotaetaelu)lu) r rizizaatitoionn Lowe((SsStiLdi(LdGoeoew owe aefelffes)festect c t )t ) LowerL((L(GSoGoiowdowaeealer)elr) f f e ct) UUUESEESSUEUUEEP:P: P:TA TATAaa::vav :gvTTg ,gTr,a,rearevfvea ffggv= ,,=g=rr ,ee5r ffe55 f6= =66=. .8.5 8585 55° ◦5° CC◦° C°CC,,C ,QQ, ,Q ,QQ aaQ,,aarra,ee,r,raffer e,fe=r=f fe= f == 2 1=2 6711 61,,5551,5,1,0000,005005305 m3m 3mm 3m 3m/3/3/3dd//3ddd/ d MPMIPMSRROIOISOSCODODO ST
((GGooaal)l) ((SSididee e effffeecct)t) EEUU: :T Tavagv,gr,erfe f= = 5 566.8.8 ° °CC, ,Q Qa,ar,erfe f= = 1 177,5,50000 m m3/3d/d CCOOSSTT

Figure 4. Block diagram of the control structure. ZOH: zero-order-hold.
FFiigguurree 44.. BBlloocckk ddiiaaggrraamm ooff tthhee ccoonnttrrooll ssttrruuccttuurree.. ZZOOHH:: zzeerroo--oorrddeerr--hhoolldd..
TTThhheee f ffeeeeeedddbbbaaaccckkk c ccooonnntttrrrooolll s sstttrrruuuccctttuuurrreee a aassssssuuurrreeeddd t ththhaaatt tt ththheee b bbaaattctchchh a avavveereraragagege et teetmemmppepereraartatuutrureer eT TaTavvgg w wawass ar resegrgueugllauatteleaddt et tdoo
atao sasppesepccieifficieiedfid e dsseestt-e-ptp-oopiinontit n TtTaTavvgg,r,erfe f ddeedsspepisitpteei t ecchhcahannaggneegsse siinni n tteteemmmpppeereraraattutuurrereses s TTTaairi,r , ,TTTslsuluddgge,e , ,aanandnd d vvavavaagrririaiaabbbiilililititytyy ooofff ttthhheee
bbbiiiooodddeeegggrrraaadddaaabbbllelee o roogrraggnaaincniimcc amtmatveaagrt,ttrcteeeforrn tceconontntitenennttht eiinrna wtthhseel u rdragawew X sslluu.ddWggeeh eXXnse,si,nvin.a e.i rrWWthhhseeluepndnageeesvvteeerur r ittzhhaeet i oppnaasrsetteqeuuuriririzezamattieioonnnt
rwreeaqqsuumiirreeemtm,aeesnnstt mw waaalsls am msepetot, ,sa asssi bs smlmeavalalll la uases sp pfooosrsssTiibbllee v vaawlluueeerses f sfooerlr e TTcatavevgsg,d,r,iernfe, fw swineercreee ss smeelleaeclclteteerddt,e ,s msiinnpcceeer as smtmuaraelllsleerrre t dteeummcpepeaereraratatutuiroreenss
rcreoedsdtuusccfeoe raaetehrraeattisioaonmn cecoopssrttsos d ffouorcr t tithohene srsaaamtme.ee A ppcrrcooodadrvudguc,ircntetifgioolnyn , rrtahatteee.T . AAccccoorrwddiainnsggcllyhy,o , tsthehene TaTsaavvg5g,r5,erfe f◦ wwCaaoss r cc5hh6oo.s8see◦nnC aafsos r555U5 °S°CEC P oAorr
56.8 °C for USEPA or EU recommendations, respectivavegl,yre f(Table 1).
56.8 °C for USEPA or EU recommendations, respectively (Table 1).
orEUrecommendations,respectively(Table1).
IIff t thhee i innppuutt e enneerrggyy t thhaatt X Xs,si,nin c caarrrriieedd i inn w waass n noott s suuffffiicciieenntt t too m maaiinnttaaiinn t thhee T Taavvgg,r,erfe,f ,t thhiiss s seett--ppooiinntt w waass
reduced for stable operation [14]. This situation was observed through a sharp decrease in the slope
reduced for stable operation [14]. This situation was observed through a sharp decrease in the slope
ooff t thhee b baattcchh T Ti–i–tteemmppeerraattuurree p prrooffiillee. .A Ann a allggoorriitthhmm f foorr i ittss d deetteeccttiioonn i iss d deessccrriibbeedd i inn Z Zaammbbrraannoo [ [1133]] a anndd
Water2017,9,426 6of15
IftheinputenergythatX carriedinwasnotsufficienttomaintaintheT ,thisset-pointwas
s,in avg,ref
reducedforstableoperation[14]. Thissituationwasobservedthroughasharpdecreaseintheslopeof
thebatchT–temperatureprofile. AnalgorithmforitsdetectionisdescribedinZambrano[13]and
i
Zambranoetal.[25]. Here,itwasimplementedundertheblock“bending-pointdetector”ofFigure4.
Consequently,Nájeraetal.[14]presentedafuzzylogicalgorithmtoprovidethecorrections∆T .
avg,ref
Thistaskwasincludedintheblock“set-pointcorrector”ofFigure4.
Themainnoveltyinfeedbackcontrolwastheuseoftwomanipulatedinputs—Q andSRT—to
a
regulate the digester temperature. The fastest input Q quickly reacted to any T temperature
a avg
deviation, and progressively gave way to the participation of the slowest input SRT. In this way,
Q recovered its steady state Q to meet steady-state control strategies. SRT deviated from its
a a,ref
biaspointwheneveranydisturbancepersisted. Thedynamiccollaborationbetweenthetwoinputs
was tailored by a proper design of controllers C and C based on a robust methodology in
Qa SRT
Rico-Azagraetal.[24] in the framework of quantitative feedback theory (QFT) with the following
maincharacteristicssummarized. AppendixAprovidesdetailsonthedesignofthecontrollersfrom
amoretechnicalpointofviewforrobustcontrolpractitioners. Thedual-controldesignfirstrequired
dynamicmodelingoftheprocess. Thus,dynamicalmodelswereidentifiedfromthetwomanipulated
inputs(SRT,Q )totheoutput(T ),andfromthedisturbanceinputs(T ,T )totheoutput(T ).
a avg air sludge avg
Severaloperatingpointswereconsidered,assummarizedinTable2. Thisyieldeddynamicalmodels
withknownparameteruncertainty(seeAppendixA).Athoroughstudyofthedynamicproperties
oftheprocessmodelshelpedtoallocatethefrequencybandbetweenthetwomanipulatedinputs:
Q wasplannedtoworkathigherfrequenciesthanSRT toachieveabettertransientperformance.
a
Thefrequencyof20rad/swasthefrontierbetweeninputcontributions. Thecontrolspecifications
wereguaranteedforthewholesetofmodels. Hence,theterminologyofrobustcontrolisused. For
robuststability,aphasemarginof45◦ wasselected. Asperformancespecifications,itwasdecidedthat
sharpvariationsinT andT upto±5◦Cbetweentwoconsecutivebatchesshouldnotdeviate
air sludge
T morethan±0.6◦Cfromitsset-pointT . Furthermore,thisset-pointshouldberecoveredatno
avg avg,ref
longerthansevendays. Thus,therobustcontrollersweredesignedbasedontheprocessmodelsand
thecontrolspecifications(seeAppendixA).Thecontrollerswere:
0.4z2
C (z) = (3)
SRT (z−1)(z−0.71)
7274.703(z−0.652)
C (z) = (4)
Qa z−0.7625
wherethevariablezisintroducedbytheZ-transform,whichisamethodforthedesignofsampled-data
controlsystems[30].Here,thesample-timeequaledthebatchtime(i.e.,1day).InFigure4,eachsample
wasdistinguishedbytheindexn. The“zoh”blockperformedazero-order-holdofthecomputed
controlactuationsduringthe1-daytreatment. The“mean-value-function”computedT eachdayas
avg
themeanvalueof1440recordsofinstantaneoustemperatureT. AT samplewastakeneveryminute
i i
(t =1min). Additionally,thesampleroftheoutputtoupdatethecontrollawwaslabelledt =1d.
s1 s2
Table2.Setofequilibriumpoints.T =T =15◦C.
air sludge
SRT(d) 11 12 13 14
Qa(m3/d)(Tavg,ref=55◦C) 22,524 20,025 17,426 15,053
Qa(m3/d)(Tavg,ref=56.8◦C) 26,100 23,000 20,000 17,500
Note:Xs,inwasconsideredabove30kg/m3duringtheexperiments.
Astep-changeintheQ set-pointwoulddeviateT fromitsset-point,whichwouldbeproperly
a avg
correctedbyEquations(3)and(4)inasimilarway,asT deviationsduetostep-changesinT and
avg air
T werecompensated. However,thatstep-changeinQ set-pointwasdrivenstraightawaytothe
sludge a
Water2017,9,426 7of15
Water 2017, 9, 426 7 of 15
actuationQ atthesteptime. Apre-filter(F inFigure4)couldconvenientlysmooththepeakatthe
a Qa
0.0239761z4
beginningofthetransientresponseofQaF. In(oz)u=rcase,asuitab lepre-filterwas: (5)
Qa (z−0.6065)4
0.0239761z4
To point out the benefits of usinFgQ taw(zo) =con(tzro−l 0in.6p0u65ts),4 MISO (Multiple Input Single Outpu(5t))
control strategies in Table 1 were compared with SISO (Single Input Single Output) control, which
uses Tao spionignlteo cuotnthtreobl einnepfiutts. oIfnu sthinisg tlwasot ccoansetr,o olninlpy utths,eM aIeSrOati(oMnu flltoipwle (IQnpa)u tcoSuinldgl epOrouvtipduet )tchoen tTraovgl
sretrgautelagtiieosni ncTaapbaleci1tyw erreeqcuoimrepda rebdy wtihthe ScISoOnt(rSoiln gslpeeIcnipfiuctatSiionngsl efOour tpruotb)ucsotn tdroisl,tuwrhbiacnhcues erseajescitniognle.
cAocnctorrodliinngpluyt, .thIne tdheissilgansetdca csoen,tornollyletrh weaase:r a tionflow(Q )couldprovidetheT regulationcapacity
a avg
required by the control specifications for rob7u0s7t9.d7i5stzu(zr−ba0n.6c9e52re)jection. Accordingly, the designed
controllerwas: CQSIaSO(z)= (z−1)(z−0.1081) (6)
7079.75z (z−0.6952)
CSISO(z) = (6)
Qa (z−1)(z−0.1081)
In the SISO strategy, SRT takes a fixed value (i.e., this input does not participate in the
closeIdn-ltohoepS ISdOynstarmatiecg y,reSgRuTlatatikoens).a fiExqeudavtiaolun e((i6.e) .,pthriosvinidpeudt dtohees neoxtppeacrtteicdi pactleosinedth-leooclpo secdo-nlotroopl
dspyencaifmiciactiroengsu lfaotri oann)y. ESqRuTa tvioanlu(e6 )inp rToavbildee 2d. tAhen eexvpeenc tseidmcplloesre cdo-nlotoropl cmonetthroolds pweocuifildca mtioannsufaollrya nfiyx
SbRotThv tahleu Qeian anTdab SleR2T.; Athnues,v tehneysi mwpoulelrdc noontt rpoalrmticeitphaotde wino tuhled dmyannaumailcly Tfiavxg rbeogtuhlathtieonQ.a Waned dSenRoTt;et hthuiss,
tmhoeydew aosu OldLn (ootppenar-ltoicoippa).t einthedynamicT regulation. WedenotethismodeasOL(open-loop).
avg
33.. RReessuullttss aanndd DDiissccuussssiioonn
TThhiiss sseeccttiioonn sshhoowwss sseevveerraall ttiimmee--ddoommaaiinn ssiimmuullaattiioonnss tthhaatt wweerree rruunn oonn tthhee AATT__BBSSMM iinnssiiddee tthhee
ccoonnttrrooll sscchheemmee ooff FFiigguurree 44..
FFiigguurree 55 sshhoowwss tthhee ttiimmee eevvoolluuttiioonn ooff tthhee mmaainin vvaarriaiabbleless inina afi frisrtste xexppereirmimeennt.t. XXs,si,nin rreemmaaiinneedd
ccoonnssttaanntt aatt 3300 kkgg//mm33, ,aanndd ssuuddddeenn cchhaannggeess ooff Δ∆TTsslluuddgeg =e =−3− °3C◦ aCndan ΔdT∆airT =a i−r5= °−C5 to◦oCkt opolakcpe laatc te =a t50t =d 5a0ndd
at n=d 7t0= d7, 0reds,preecstpivecetliyv.e Mly.aMxiamxuimmu dmevdieavtiiaotnios nosf oTfaTvga v(0g.(309.3 °9C◦ Canadn d0.02.72 7°C◦C) )wwereere bbeeloloww tthhee mmaaxxiimmuumm
ppeerrmmiitttteedd ooff 00.6.6◦ °CCf oforra a5 5◦ C°Cd idstisutrubrabnacnecset espte,pa,n adntdh ethseet tsleinttgli-ntigm-teimtoer teoc orveecrovtheer 5th5e◦ C55s e°Ct-p soeitn-ptowianst
awraosu anrdousenvde nsedvaeyns daasyesx apse ecxtepde.ctIendt.h Ienfi thrset fmirostm menomtseanfttes raaftneyr adnisyt udribstaunrcbea,nQcae,q Quia cqkulyicakslysu amsseudmtehde
rthege urlaetgiuonlattaiosnk ,atansdk,p raongdr espsriovgerlyesSsRivTelbye cSaRmTe mbeocraemreel emvaonrte. Trehleevstaenatd. yTshtaet estoefatdhyo ssetmatea noipf utlhaotesde
imnpanuitpsuwlaatserde ainchpeudtsb wefoasre r2e0acdhaeyds baesfporrees c2r0i bdeady.sI nass tpearedsyc-rsitbaetde,. tIhne sStReaTdnye-scteastsea,r itlhyer SeaRcTh endecdeisffsearreinlyt
ereqaucihliebdri adtioffecroemntp eenqsuaitleibtrhiae dtois tcuormbapnecnessa.tHe othwee vdeisr,tuQrabaalnwceasy.s Hreocwoveevreerd, tQhae aslewt-apyosi nrteQcoa,vreef.reInd tthhies
wseat-yp,oQina,tr eQf wa,reaf.s Icno nthvies nwieanyt,l yQsa,erelf ewctaesd cboansveednioennttlhye sdeleescitreedd bstarsaetde goyn: mthien idmesuirmeda esrtraattieognyc: omstin(MimIuSmO
CaeOraStTio)nf ocrotst< (M90ISdO,o CrOmSaTx)i mfourm t <p r9o0d udc, toiorn mraatxeim(MumIS OprPoRduOcDtio)nfo rratte> (9M0IdS.OF PocRuOsDin)g foonr tt h>e 9Q0a ,dref.
cFhoacnugsientgh aotnt otohke pQlaa,rcefe cahtatn=g9e0 tdha,itt tcoooukl dpclahceec katt ht e=e 9x0p edc,t eitd cpoeurlfdo rcmheacnkc ethine tehxepTeacvtgesde tp-perofionrtmreacnocvee riny
athned Tthavge ssemt-opootihntt rraencosivtieorny oanfdm tahnei psumlaotoetdh itnrapnustistiSoRnT oaf nmdaQniap.ulated inputs SRT and Qa.
FFiigguurree 55.. TTiimmee ddoommaaiinn ppeerrffoorrmmaannccee..
A second experiment considered variability in Xs,in, Tair, and Tsludge (see Figure 6a). Figure 6b
AsecondexperimentconsideredvariabilityinX ,T ,andT (seeFigure6a). Figure6b
depicts the evolution of the main variables involved ins ,ain MIaSirO COSTs lfuedegedback control strategy. The
depicts the evolution of the main variables involved in a MISO COST feedback control strategy.
digester temperature Tavg was conveniently regulated to 55 ± 0.2 °C thanks to a fast actuation Qa
(around Qa,ref of minimum cost), which compensated the fastest disturbance dynamics, and to a slow
actuation SRT, which mainly compensated the midterm variability of air and sludge temperatures.
Water2017,9,426 8of15
ThedigestertemperatureT wasconvenientlyregulatedto55±0.2◦CthankstoafastactuationQ
avg a
(aroundQ ofminimumcost),whichcompensatedthefastestdisturbancedynamics,andtoaslow
a,ref
Water 2017, 9, 426 8 of 15
actuationSRT,whichmainlycompensatedthemidtermvariabilityofairandsludgetemperatures.
Water 2017, 9, 426 8 of 15
Ontheotherhand,Figure7adepictstheevolutionofthedigestertemperatureT formanualcontrol,
On the other hand, Figure 7a depicts the evolution of the digester temperatuavrge Tavg for manual
wchOoennrte rtoQhle,a w=oth1he8er,re7 5hQ0aan m=d 31, /8Fd,i7g5au0nr dme S37/Rad T dan=epd1i c2St.Rs5 Tdt h=.e T 1eh2v.e5o aldub.st iTeohnnec eoafob fstehfneeec edd ibogafe csfketeeirdn bftoeamrcmkp aientrifaootnurmriema tTpioaevngd fiemodrp amesdauenidtua aabl l e
resgcuouintlaatbrtioloeln, rweoghfuetlhraeet iQotenam =o pf1 e8thr,7ae5t ut0e rmme,p3w/edrh aaitncuhdre dS, eRwvThi ai=ct eh1d 2d.f5er vodima. tTethdhe ef radobemsse intrheceed dovfea sflieureeedddb vuaacelkut oein tdfhoueremv taaort itiohanbe ivilmiatrypiaeobdfieliidnty pa u t
coosnfu diinittapiboulnet s croe(Fgniudgliuatitroieonns6 ao(F)f. itghFueirg etue 6mraep).7e Fbraigstuhurroeew, 7wsbh tshihcehov wdaser vitaihabetl eevdsa rffrioaorbmlae tsSh fIeoS drO eas fiSerIeeSddOb v afacelkeudecb odanuctker otcolo nsthttrreao vtl easgrtriyaabtweilghityey r e
SRwoTfh =einr1ep2 uS.5Rt cTdo .=nT 1dh2ite.i5od dni.sg T e(hFsteieg druitrgeeem s6tape)er. rtFaeimtguuprreeerT a7atbvu grsewh oTawasvgsc w othnaesv cevonanirevianebtnllyieesnr fetolgyru ralea gSteIuSdlOatt oefde5e t5do±b 5a5c0 k±.2 0c◦.o2Cn °tCtrho talh nsatknrsakttseo tgotyh e
sintwhgehl eesraienc tSguRleaT ti ao=c n1tu2o.af5t iQdo.an .T Thoehf edQiagab.e sseTtenhrce et eoambfpsaeesnreaccteuo rnoedf Tcaavo gn swteracoosl nlceodrn tvcooehnnaiternondltllleyer r SeRtgoTu lhiamatenpdde ltdeo e 5dS5Rt ±hT e0 .ia2mc °hpCie etdvheeadmn ketshn teto o f
aastechhceoi ensvdienmggoleean lta bocyft uama steeioacnno nsodof f gaoQnaal.e bxTythr mae seaeabtn-sspe oonficn eat n.o efx tar a sseecto-pnodi nct.o ntroller to handle SRT impeded the
achievement of a second goal by means of an extra set-point.
(a) (b)
(a) (b)
Figure 6. Validation experiment: (a) disturbance inputs; and (b) control variables and controlled
Figure 6. Validation experiment: (a) disturbance inputs; and (b) control variables and controlled
vFairgiaubrele 6fo. rV MalIiSdOat iCoOn SeTx psterraimtegenyt. : (a) disturbance inputs; and (b) control variables and controlled
variableforMISOCOSTstrategy.
variable for MISO COST strategy.

(a) (b)
(a) (b)
Figure 7. Validation experiment: (a) controlled variable for open-loop (OL) strategy (SRT = 12.5 d and
QFai g=u 1r8e, 775. 0V amli3d/dat)i;o ann edx p(ber)i mcoennttr:o (la )v caorniatbrolell eadn dv acroianbtlreo lfloerd o pvaerni-alboloep f(oOr Ls)i nstgrlaet eignyp u(St RsTin =g 1le2 .o5u dt pauntd
Figure7.Validationexperiment:(a)controlledvariableforopen-loop(OL)strategy(SRT=12.5dand
(QSIaS =O 1) 8c,o7n5t0r oml (3S/dR)T; a=n 1d2 .5(b d) ).c ontrol variable and controlled variable for single input single output
Qa(S=IS18O,7) 5c0onmtr3o/ld (S);RaTn d= (1b2).5c don).t rolvariableandcontrolledvariableforsingleinputsingleoutput(SISO)
control(SRT=12.5d).
Finally, considering Xs,in, Tair, and Tsludge in Figure 6a, the AT_BSM simulations were separately
perforFmineadll yfo, rc othnes idcoemrinpga rXisso,inn, Toafir ,s eavnedr aTls lcudogen itnro Fl isgturartee g6aie, st.h Teh Ae Tfo_BlloSMwi nsigm euvlaaltuioantiso nw einred esxeepsa rwateerley
cpoemrFfpionuramtelldeyd ,u cfsooinnr gsti htdhee erc iodnmagtpaX afsro,iirns o,thTne ao isrf,a amsenevd eprTeasrlli uocdodgen oitnfr o1Fl0 is0gt ruda r(teNeg6 =iae ,1st.0 h0Te hbAea tTfco_hlBeloSsw)M. insgim euvalalutiaotniosnw inerdeexseeps awraetreel y
pecrofomrmpuetdedf oursitnhge tchoem dpaatar ifsoorn thoef ssaemveer palercioondt orof l1s0t0r adt e(Ngi e=s 1.0T0h beatfcohlleosw). ingevaluationindexeswere
co(mi) puPtaesdteuusriinzgattihone dUaStEaPfAor Itnhdeexsa −m IQePpUSeErPiAo (d%o) fq1u0a0ntdifi(eNs t=he1 0q0ubalaittych oefs p).asteurization as per USEPA
(i) gPuaisdteeluinriezsa [t4io,8n] :U SEPA Index − IQPUSEPA (%) quantifies the quality of pasteurization as per USEPA
guidelines [4,8]:
[ ]
N
I(j) Q(j) m[ 3d−1 ] [ ]
IIQQPUPUSESEPPAA==j=jN1=1jN=IQN1Q(QpQpja)ar(a(jQw)jr)[ar(m[awmjw)33mdd−3−11d]]−1110000,,wwhheerree IIQ(Q(pj)pja)a==iN=iN=1i1iDDtts(1si(1)id[)[dd[d]]] ((77))
raw
j=1
Water2017,9,426 9of15
(i) PasteurizationUSEPAIndex—emphI (%)quantifiesthequalityofpasteurizationasper
QPUSEPA
USEPAguidelines[4,8]:
∑N I(j) Q(j) (cid:104)m3d−1(cid:105)
I = j=1 Qpa raw 100, where I(j) = ∑Ni ts1[d] (7)
QPUSEPA ∑N Q(j) (cid:104)m3d−1(cid:105) Qpa i=1 D(i)[d]
raw
j=1
wheret =6.94×10−4disthesamplingtimeofintra-batchT–temperaturerecords,N =1440
s1 i i
isthenumberofT–samplesinabatch,andD(i) (Equation(2))istheminimumtimerequired
i
at T–temperature. An I index value equal to 100% meant strict agreement with the
i QPUSEPA
regulation. I greaterthan100%wassafer,butrevealedworthlessexpenses.
QPUSEPA
(ii) PasteurizationEUIndex—I (%)computedthepercentageoftreated-sludgethatmettheEU
QPEU
recommendation(55◦Cforatleast20h)[9]:
I = j∑=N1k(pja)ste Qr(aj)w(cid:104)m3d−1(cid:105) 100, where k(j) (cid:40) 0 if PTime(j) <20 h (8)
QPEU ∑N Q(j) (cid:104)m3d−1(cid:105) paste 1 if PTime(j) >20 h
raw
j=1
wherePTime(j) (h)representsthetotaltimeinwhichthesludgehasbeenatatemperaturegreater
than55◦Cduringtheaeratedreactionphaseofthej-thbatch. Onehundredpercentcorresponds
tothemaximumI valuethatwasattainable. I valuessmallerthan100%indicatedthat
QPEU QPEU
somebatchviolatedtheEUregulation.
(iii) CostIndex—I (%)considerstheaerationandpumpingenergiesemployedperunitoftreated
C
sludge volume. The index is normalized as a percentage of an average energy requirement
(E =12kWh/m3sludge)extractedfromUSEPA[8]:
ref

I = EQa[kWh]+Epump[kWh] 100, where  EQa =0.04j∑=N1Q(aj) tbatch (9)
C Eref[kWhm−3]j=∑N1Qr(aj)wtbatch[m3]  Epump =0.04j∑=N1(cid:16)Qr(aj)w tbatch+Q(oju)t tbatch(cid:17)
whereE istheaerationenergy;E isthepumpingenergy;andt isthebatch-time(1day).
Qa pump batch
(iv) Production Index − I (%) is expressed as a ratio between the treated sludge flow and the
P
maximumflowthatcouldbetreated:
∑N Q(j)(cid:104)m3d−1(cid:105)
out
I = j=1 100, where Q = VATAD (10)
P N ∑N Q(j) (cid:104)m3d−1(cid:105) rawmax SRTmin
rawmax
j=1
I isareliableindexonlyiftheATADisproperlyoperated(i.e.,thepasteurizationindexshould
P
alsoreachsuitablevalues). Forexample,anover-floweventinthepre-holdingtankorthedesireof
maximizingtheproductionratewouldinvolvethedigesterbeingoperatedatfull-capacity,giving
amaximumI . However,partoftherawsludgecouldnotbeproperlytreated.
P
The strategies compared are summarized in Table 3. The desired digester temperature was
chosentomeettheminimumlevelofpasteurizationrequiredbytheregulation. Thus,either55◦C
or 56.8 ◦C were chosen to meet the USEPA or EU criteria, respectively. Accordingly, the feedback
controlstrategiesadaptedtheirT . TheOLstrategylackedfeedbackcontrolloops. ItusedfixedQ
avg,ref a
andSRT,whichwereestimatedoff-line. First,ameanSRT=12.5dwasadopted. Then,Q =18,750
a
Water2017,9,426 10of15
m3/dwasestimatedtoachieveT =55◦C,consideringatheoreticalbehavior(meantemperatures
avg
T =T =15◦Candidealconstantcompositionoftheinfluent,withX =30kg/m3). Another
air sludge s,in
Q =21,500m3/dwassimilarlyestimatedtoachieveT =56.8◦C.TheSISOstrategyusedafeedback
a avg
controlstructure,whichregulatedT toT bymovingQ asthefeedbackcontroller(Equation(6))
avg avg,ref a
dictates; SRT was manually fixed to 12.5 d. All MISO strategies used the same control structure
(Figure 4) and control elements (Equations (3)–(5)). MISO COST and MISO PROD set-points are
detailedinTable1. AstandardMISOstrategy(MISOSTD)selectedQ valuesinbetweenthoseof
a,ref
MISOCOSTandMISOPRODstrategiesandavoidedextremebehaviorssincetheminimizationof
aerationcostsinvolvesminimumproductionrates,andthemaximizationofproductionratesinvolves
maximumaerationcosts.
Table3.Strategiesforcomparisons.
OL SISO MISOSTD MISOCOST MISOPROD
Feedbackregulatedto Feedback Feedback
18,750(USEPA) Freefeedback
Qa(m3/d) 21,500(EU) regulated Qa,ref=18,750(USEPA) regulatedto regulatedtoQa,ref
ortoQa,ref=21,500(EU) Qa,refinTable1 inTable1
Freefeedback Freefeedback
SRT(d) 12.5 12.5 Freefeedbackregulated
regulated regulated
TheevaluationindexesarepresentedinTable4.Sincetheset-pointtemperaturewaschosentostrictly
meeteithertheUSEPAorEUregulations,theyieldedqualityindexesfullyagreedwithit.Theyrevealed
howaless-detailedcriterion(EUregulation)ledtosaferqualitylevels,butinvolvedhighercostindexes.
Forthefollowingcomparisons,letustakeasthemeaningfulqualityindexI forT =55◦Cand
QPUSEPA avg,ref
I forT =56.8◦C.ComparingtheOLandSISOstrategies,bothyieldedthesameI sinceboth
QPEU avg,ref P
usedthesameSRT.AsmallerexpenseI forOLinvolvedinsufficientaeration,whichwasinconsonance
C
withapoorerqualityindex.Therefore,closed-loopcontrolwascompulsoryforcontinuoussupervision
andcorrectionofthedigestertemperatureinsuchawaythattherequiredqualitywasachieved,and
theSISOandMISOcontrolstrategiesprovedthis. TheaddedvalueofMISOvs. SISOstrategiesisthe
possibilityofattendingtoasecondobjectiveinMISOcontrol.Thus,theMISOCOSTstrategyreducedthe
aerationexpenses(smallerI )incomparisonwiththeSISOcontroltoachieveasimilarquality. Inthe
C
sameway,theMISOPRODstrategyimprovedtheproduction-rateincomparisonwiththeSISOcontrol
(seetheirI ).Figure3pointedoutthetrade-offbetweenminimizingtheaeration-costandmaximizing
P
theproduction-rate.Consequently,asmallerI intheMISOCOSTthanintheSISOwasthepricepaidfor
P
asmallerI intheformer.AlargerI intheMISOPRODthanintheSISOwasthepricepaidforalarger
C C
I intheformer.Nevertheless,theflexibilityoftheMISOcontrolensuresthattheplantoperatorhasfull
P
controlofthoseobjectivesthankstoaclosed-loopthatcanregulatethem.Asevidenceofthis,theMISO
STDyieldedsimilarindexestotheSISOcontrol.
Table4.Evaluationofstrategies.
Tavg=55◦C(USEPA) Tavg=56.8◦C(EU)
IQPUSEPA(%) IQPEU(%) IC(%) IP(%) IQPUSEPA(%) IQPEU(%) IC(%) IP(%)
OL 100.61 7.17 34.28 74.75 175.92 44.9 39.12 74.91
106.62 35.18 74.76 191.32 40.37 74.96
SISO 0 100
(5.97%) (2.63%) (0.01%) (8.75%) (3.20%) (0.07%)
MISO 106.42 34.83 73.66 190.99 39.89 73.53
0 100
STD (5.77%) (1.70%) (−1.46%) (8.57%) (1.97%) (−1.84%)
MISO 105.08 32.32 63.93 188.55 37.18 64.39
0 100
COST (4.44%) (−5.72%) (−14.47%) (7.18%) (−4.96%) (−14.04%)
MISO 107.81 37.04 82.93 193.9 42.54 83.42
0 100
PROD (7.16%) (8.05%) (10.94%) (10.22%) (8.74%) (11.36%)
Note:InbracketstheindexesareexpressedasapercentageoftheOLindexes.