process model-based decision support for multi-stakeholder water-food-energy-ecosystem network
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Process model based decision supportfor multi-stakeholder
water-food-energy-ecosystem networksHarmonization oflocalinterests
with global sustainability
Monika VargaResearchGroupon Process NetworkEngineering
Water-Food-Energy networks
Water Food
Energy
Source:Garcia andYou,2016.Computers andChemical Engineering,91:49–67.Further edited according to Fig.1ofthe above paper.
30%62%
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Challenges ofharmonization• Growing global population→needsmorewater,food andenergyfrom efficient use of renewablelocalresources;
• Globalproblems with climate change andecosystems →need sustainable andresilient designandcontrol oflocalwater/food/energy networks;
• Model based decisions on localpossibilities helpsto find compromise between localinterests andglobal sustainability.
• Longterm questions →Youth have adefiniteinterestandresponsibility for finding solutions!
Conclusion: we have to manage bottom-up themosaics ofthese apparently quite differentprocess networks.
How?
Quantitative decision supportmethods ofProcess SystemsEngineering help to find goodlocalpossibilities:
• to minimize trade-offs and• to maximize synergies.
What isProcess SystemsEngineering?
• It originates from chemical engineering;• It offersmodelingandsimulation tools for– design,operation,control,andoptimization ofprocess systems.
• Recently it encompassesabroad rangeofmultidisciplinary applications:– e.g.biotechnology,environmental engineering,agriculture and food industry,advancedmaterials,etc.
How do process modeling andsimulationsupport better decisions?
• Amodel isasimplifiedrepresentationoftheessential features ofaprocess topromoteunderstandingofits real,dynamic behavior;
• Model based simulation enables topercievethose causal interactionsthatwouldnototherwisebeobvious;
• Thesimulation based designandcontroldecisions can consider the balances.
Our method for modeling andsimulation:Direct ComputerMapping
• Automatic generation ofexecutable processmodels from:– Structure:network ofthe investigated problem;– Functionalities:programprototypes to calculatethe elementary processes
• Graphical interface for model expert• Case specific interfaces for users (webbased,MSExcel,etc.)
• Successful andongoing demand-ledapplications:modelers +field experts
Our recent partners (modeling &field experts)
• NationalPolytechnicInstituteofToulouse,France• CenterforProcessandEnvironmentalEngineering,UPC,Barcelona,Spain
• UniversityofPannonia,Veszprem,Hungary
• Ecological ResearchCenter,HungarianAcademyofSciences
• ChinaAgriculturalUniversity,Beijing,China• Fino-FoodLtd.,Hungary• GS1HungaryNon-profitLtd.• ResearchInstituteforFisheriesandAquaculture,NationalAgriculturalResearchandInnovationCentre
Recently studied demand-led examples(with the unified DCMmethodology)
• Complex environmentalprocess system:managementofasensitivewatershed
• Trans-sectorial agrifoodprocess system:quantitativetracing andtracking
• Process design:Recirculating AquacultureSystems
• Process operation:scheduling ofamulti-product dairy plant
Recently studied demand-led examples
• Complex environmentalprocess system:managementofasensitivewatershed [1,2]
• Trans-sectorial agrifoodprocess system:quantitativetracing andtracking
• Process design:Recirculating AquacultureSystems
• Process operation:scheduling ofamulti-product dairy plant
Studied environmental systemEurope
LakeBalatonarea
Hungary
GISbased interface
Detailed hydrologicalmodel withmeteorological data
CORINErepresentation ofland use
Water network andland use
User interface
What isit for?
• To study the effects of(extremly or slowlychanging)meteorological situations;
• To follow contaminants in the watershed;• To study the effects ofpossible land use;• To combine with the investigation ofwater-food-energy-ecosystem related studies.
Example:fictitious weather scenarios
Example:spreading ofcontaminant
Recently studied demand-led examples
• Complex environmentalprocess system:managementofasensitive watershed
• Trans-sectorial agrifoodprocess system:quantitativetracingandtracking[2,3,4,10]
• Process design:RecirculatingAquaculture Systems
• Process operation:schedulingofamulti-product dairy plant
Tracingandtrackingoffood products
Challenges
• Heterogeneous actors (plant cultivation,fodder production,animal breeding,foodprocessing,commerce,etc.)
• Dataservicevaries from the logbook offamily farms to the sophisticated ERPsystems;
• Need for trackingandtracingof(sometimessuddenly appearing)harmful andusefulcomponents.
Testsystems
• Family farm(plant cultivation,vegetables)• Meat chain (from plant cultivation to slaughtering)
Technical partner
• GS1HungaryNonprofit Ltd.
Example:webbased data supply
What isit for?
• Qualitative tracking• Qualitative tracing• Quantitative tracking• Quantitative tracing• Balance control• Value chain analysis (ongoing)
Example:tracking report
Recently studied demand-led examples
• Complex environmentalprocess system:managementofasensitivewatershed
• Trans-sectorial agrifoodprocess system:quantitativetracing andtracking
• Process design:RecirculatingAquacultureSystems [5,6,8]
• Process operation:scheduling ofamulti-product dairy plant
Recirculation Aquaculture System
Basicscheme ofRAS
Increasing volume ofmultiple tanks in RAS
Challenges
• Technical:– Fish growth,feeding strategy (quality,amount,scheduling)transporting fishes between stagesandwastewater treatment are highly interacting;
– Designandcontrol ofthis whole system hasanenormous complexity.
• Organizational:– Push:long-term contracts for buying fingerlings;– Pull:long-term contracts for selling products.
Example for the modeling interface
What isit for?
• To design anew system for:– optimal tankstructure ofthe subsequent stages(adapted to the fish speciesandto commercialstrategy);
– optimal waste water treatment unit.
• To control anexisting system for:– optimal operation (e.g.minimize fresh water use);– optimal transporting strategy between the stages.
Example:optimization in a„fictitious tank”
Example:considering diversification in weight
Recently studied demand-led examples
• Complex environmentalprocess system:managementofasensitivewatershed
• Trans-sectorial agrifoodprocess system:quantitativetracing andtracking
• Process design:Recirculating AquacultureSystems
• Process operation:scheduling ofamulti-product dairy plant [7,9]
Demand driven scheduling ofadairy plant
PLANNING–Monthly
••Target:Equilibrated material balance••Push feature:Yearly based contracts for raw milk••Pull feature:EXPECTEDselling with EMPIRICALESTIMATION
SCHEDULING–Weekly
••Target:100%serving rate••Pull feature:last week selling andproduction numbers +realorders (fixed+ad-hoc)
••Push feature:MUSTprocess the milk in lessthan 48hours
RESCHEDULING– Daily/Shift
••Target:100%serving rate with minimumnumber ofconversions••Pull features:••Orders ofthe coming 4days••Available stock
Planning,scheduling andre-scheduling
Example flowsheet ofdairy plant processes
Rawmilktakeover
Milk processing(pasteurisation,homogenization,
skimming)
Batches••Cheese••Yogurt••Processedcheese
Packaging
Ripening/Storing
Selling
What isit for?
Dynamic simulation based reasoning with theknowledge ofdemands andstocks supports:
• fast scheduling/rescheduling according to theactual consumers’demands;
• consideration ofmany operational constraints(e.g.cleaning periods,cooling times,changingmachine capacity,etc.).
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Changing stocks ofthree products(in linewith packaging andselling)
JoghurtAJoghurtB
Example for decision supporting results
ConclusionsWe can use unified modellingandsimulationmethods- for analysis,designandoperation- ofthe various sub-systems of water,food,energyandecosystem related processes.
This ought to becombined with utilization ofavailable big data to generate better models forthe actual andpossible solutions.
Outlook: In this way the interacting complexsystems can beoverviewed andevaluated for aquantitatively founded decision support.
Outlook
Outlook
Outlook
Outlook
R&Dfor necessary newtechnological alternatives forfood-water-energy processes
Process models,built from thevarious technological
alternatives
Multi-objective evaluations forvarious time horizons
Outlook
efita2017.org/
References1. Varga M, Balogh S, Csukás B. An extensible, generic environmental process modelling framework
with an example for a watershed of a shallow lake ENVIRONMENTAL MODELLING & SOFTWARE 75:pp. 243-262. (2016) IF: 4.42
2. Varga M, Csukás B. Simulation of Agro-environmental Processes by Direct Computer MappingLecture Notes in Engineering and Computer Science II: pp. 847-852. (2015) World Congress onEngineering and Computer Science 2015. San Francisco, USA. ISBN 978-988-14047-2-5
3. Varga M, Csukás B, Balogh S. Transparent Agrifood Interoperability, Based on a Simplified DynamicSimulation Model In: Mildorf T, Charvat K (szerk.) ICT for Agriculture, Rural Development andEnvironment: Where we are? Where we will go?. Prague: Czech Centre for Science and Society,2012. pp. 155-174. (ISBN: 978-80-905151-0-9)
4. András Tankovics, Sándor Balogh, Mónika Varga. Testing of a process model based Web interface forintegration of small family farms in sector spanning traceability. Agriculture Informatics 2013 - Thepast, present and future of agricultural informatics, 8-9. November 2013, Debrecen, Hungary.
5. Varga M, Balogh S, Wei Y, Li D, Csukas B Dynamic simulation based method for the reduction ofcomplexity in design and control of Recirculating Aquaculture Systems INFORMATION PROCESSINGIN AGRICULTURE 3:(3) pp. 146-156. (2016)
6. Varga Mónika, Balogh Sándor, Kucska Balázs, Yaoguang Wei, Daoliang Li, Csukás Béla Testing ofDirect Computer Mapping for dynamic simulation of a simplified Recirculating Aquaculture System.JOURNAL OF AGRICULTURAL INFORMATICS 6: (3) pp. 1-12. (2015)
7. Linda Egyed, Mónika Varga, Béla Csukás. First steps toward Direct Computer Mapping basedscheduling of dairy production. Agricultural Informatics 2014 - Future Internet and ICT Innovation,13-15 November 2014, Debrecen, Hungary.
8. Gergo Gyalog. Bio-economic optimization of fish producing technologies. Ongoing PhD thesis.9. Linda Egyed. Analysis and development of multiscale (sub)optimal scheduling in a dairy plant.
Ongoing PhD thesis.10. András Tankovics. Dynamic process modeling of a dairy farm. Ongoing PhD thesis.