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Research at MDH

Research at MDH. Focus is on Automation and Efficiency improvment as well as Sustainability Four strong research profiles: MRTC, Mälardalen Real Time Center PRO, Process och Resource Optimization ISS, Integrated Sensor Systems PRC, Product Realization Center

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Research at MDH

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  1. Research at MDH • Focus is on Automation and Efficiency improvment as well as Sustainability • Four strong research profiles: • MRTC, Mälardalen Real Time Center • PRO, Process och Resource Optimization • ISS, Integrated Sensor Systems • PRC, Product Realization Center • 110 researchers and 140 PhD students within this area, out of 250 PhD students at MDH • ca 15000 students from which 1/3 in NT area

  2. PRO, Process and Resource Optimization • Covers Energy, environmental and building engineering • 43 PhD students and 20 researchers from which 8 professors • Major research groups (number of researchers + PhD students): • Process efficiency improvements (29) • Process development (15) • Energy and load management (10) • Environmental management and communications (9)

  3. Process efficiency improvemnet • Uses mathematical models as a common tool. Combine physical and statistical models with good process knowledge. • Uses the models for multiple purposes: • High up-time, maintenance and performance monitoring : • Diagnostics and ”early warnings” • Maintenance on demand • Decision support • Process- and sensor performance monitoring . Datareconciliation • Optimization: • Modelbased, multivariable control • Production planning and process optimization

  4. Examples of projects Production optimization and production planning • DOTS, Dynamic Optimization of Papermills, 5 MEuro (EU). MDH responsible for optimization and link to simulators • Production planning Stockholm district heating,where uncertainty in prognosise and dynamics are included • Energioptimization of pulp mill (Södra, Mörrum) with CTH. MDH on-line, CTH design. • Production planning and optimization at Eskilstuna Energi och Miljö • MPC on BFB with moisture measurement at Eskilstuna Energi och miljö (with ABB)

  5. Diagnostics Examples projects • ”Early warning” system for recovery boiler at Vallvik ( physical models connected to BN) • Datareconciliation at ENA Energi • Steam turbine diagnostics at ENA Energi (ST) with LTH (ANN) and Siemens Turbine • GTdiagnostics with Siemens Turbine in Finspong (GT) – maintenance on demand. • Decision support of coal mills at Nordjyllandsverket resp CFB at Mälarenergi with FosterWheeler (BN). • Dynamic datareconciliation at Mälarenergi with VTT • Maintenance on demand at Sala-Heby EnergiAB • Diagnostics and modelbased control of digester at Korsnäs and Vallvik with (Kvaerner) Metso • The English butler with SICS and ABB. Mälarenergi and Avesta Polarit • Diagnostics and production optimization, cold roll mill- Surahammars Bruk ( starting up )

  6. MDH PRO research profile • Combining physical and statistical process modelling with deep process knowledge • Cooperates with specialists on different subjects • BN and decision support, Aalborg University, DK • MPC UCSB in the USA and Manchester Univ i UK • Process simulation EU-net COST E36 (Erik D WGB chairman). 14 countries. Book published February • Diagnostics – several , like Purdue, LTH,Tampere • Processoptimization – UCSB (US), Tampere (FI), SJTU (CN) • MVDA Telemark Univ, Porsgrunn (NO), North Carolina Univ (US)

  7. Diagnostics, early warnings and decision support • Recovery boiler at Vallvik – steam explosion 1998. Astrong wish to avoid a new explosion! • Energy balance over the recovery boiler using the measurements from the process together with a physical process model. This balance is update frequently. • Trending the deviation between measured data and predictions from the physical model. Complement with other information like bed camera and lab measurements. • When the deviation passes a predefined level, an ”early warning” is sent to the operator displays • Decision support on probable cause of problems is given through a Bayesian net. E.g.: • Tube leakage in furnace part of boiler 65% probability • Sensor fault black liquor flow meter 43 % • Tube leakage in ECO part 24 % • etc

  8. Process Section Diagnostics Leak Detection: Trend the mass balance error in a recovery boiler Use simulator models for calculation of balances and prediction of future scenarios due to different actions In Out DCS In Out Calculated Difference =(Inflow -Outflow) = tube leakage around 1 m3/h= "Soft Sensor"

  9. MPC Forskning kring pannstyrning med on-line fukthaltsmätning på biobränsle

  10. Styrstrategi Mål 2: Håll ångflöde konstant på högre nivå- ger mer el Ångdom med bra stabilitet i ångtryck kan man höja medelvärdet och således höja uteffekten Styr matning utifrån NIR. FF. Ger stabilt ångflöde Mål 3: Håll CO & NOx under gräns Fukthalt och O2 i rökgas Justera luftflöde utifrån O2 halt. FB. CO får inte gå över viss gräns Mål 1: Håll temp konstant Ånga/vatten NIR-mätare Luft Justera ångflöde utifrån fukthalt i bränslet (NIR). FF. Att utvärdera: Mät NOx, CO, O2 i rökgas, stabilitet/nivå ånga, temperaturstabilitet i pannan. Beräkna verkningsgrad bränsle-nyttiggörande.

  11. Påverkan av ökad bränslefukt på bäddtemperatur och fukthalten på rökgasen

  12. Dymola modellen implementerad i Simulink med hjälp av ”Dymola block”

  13. Dymola modellen kopplad mot OPC server

  14. Biomass combustion in CFB plant - DDR Specifications Boiler 5 Total heat Output : 157 MWth Steam Flow : 55.5/48 kg/s Steam Pressure : 170/37 bar Steam Temperatur : 540/540 oC

  15. Dynamic data reconsiliation at Mälarenergi

  16. Dynamic data reconciliation at Malarenergy - Avvikelse mellan mätt och predikterat värde på fukthalt i rökgas

  17. Diff (simulering –mätdata) Mätvärden Jämför tid Process Simulator SimData Orsaksamband - beslutsstöd

  18. Värmevärde biobränsle Sintrings tendens Luft reglering Flödes givare Bränsle matning Bäddtemp panna Ångdom reglering Intrexbädd Nivå/temp U-värde Temp Givare intrex Temp Givare ånga Varians ångtemp Effekt minskning Fjv produktion Turbin problem

  19. Värmevärde biobränsle Sintrings tendens Luft reglering Flödes givare Troligaste felorsaker kopplade till varning Bäddtemp panna Ångdom reglering Temp Givare intrex Intrexbädd Nivå/temp U-värde Temp Givare ånga Varians ångtemp Effekt minskning Fjärrvärme produktion Turbin problem

  20. Optimization of district heating production and distribution • There are many production units and a huge distribution net • Important to handle dynamics in the net as well as uncertainties in weather fore casts and performance of equipments for a reliable optimization of the operations • This has been performed in cooperation with Fortum heat (Stockholm) and Eskilstuna Energy and Environment

  21. Optimization of fiber line – diagnostics and Model based control

  22. Optimization fiber line • Modelica model handles varying temperatures, chemical dosages, production rate and wood quality • Tuning the reaction constant for different wood components, how fast lignin, cellulose and hemicellulose are dissolved, and chemicals consumed • Measure NIR on line on ingoing wood chips. Predict the dissolution. • Use the NIR signal on wood composition in for diagnostics- hang ups, channeling etc and for Model based , multivariable control • Korsnäs, Rottneros vallvik, Metso(Kvaerner pulping), SAPPI i sydafrika • Parallel optimization project at Södra, Mörrum

  23. Vinst med optimering (produktionsplanering, modellbaserad styrning, diagnostik och beslutsstöd) • Beräkning på fiberlinje – öka produktion med 2 %. Säljpris (600 $/ton – marginalkostnad 200 $/ton)* 600 000 tpy= 4.8 M$/y eller 34 MSEK/år. • Pannorna: Kan vi öka effekten på panna 5 vid Mälarenergi med 1 MW i snitt 2000 h/år motsvarar detta 1 MSEK/år. Tror vi är lågt räknat. • Fjärrvärmesystem: Minska förluster och ge jämnare temperatur i fastigheterna. Debitera rätt – diagnosticera flöden för att åstadkomma detta • Pappersmaskinerna – optimering av produktion genom att minska pappersbrott – sparade RAPP i Indonesien 7 M$/år.

  24. Optimization of biogas production Växtkraft • Membrane filtration removes organics from centrifuge filtrate water. No ballast. • Better distribution of gas for mixing • Improving mass transfer with electric field • Better measurement and control when we have learnt how to operate i best possible way • Recirculate sludge to farm land

  25. Moisture content measurement in biomass • Delivery control of biomass for right pricing • RF is a bulk method developed by MDH together with Eskilstuna Energy and Environment • The method has been tested for moisture content between 33 and 63% • The method is tested for most type of fuels used in cogeneration plants.

  26. b φ L r0 D0 Ø D φ H β X XL Ventilation of fire gases in underground installations like tunnels • Cooperation with SP,LKAB, fire brigades in several cities, SL, Banverket, Fortifikationsverket, LTH,HiD • Full scale experiments and Modelling of fires using CFD and other tools • Development of strategies for ventilation to minimize risks for humans during fire fighting in underground installations. Development of diagnostics and decision support

  27. Water treatment technology • Optimization of water treatment systems • Removal of NO3 in water using constructed wet land ponds • Active sludge process optimization- New project starting February 2008. • Fermentation – press water (membranfiltration) • Development of adsorption systems from natural materials

  28. Energy and load management • Automatic energy meter reading systems for interactive information to house holds • Signle houses in Västerås, Götlunda, Smedjebacken, Södra Sandby, Sala-Heby. • Apartments in Eskilstuna och Västerås • Questionairs, measurements, web information etc • Energy optimization and conservation in buildings and industries • Climate control in offices (e.g. at MDH) • Optimization of complete systems from production over distribution to consumption in households and industries • ”Polygenerering” where biomass is used in an optimal way from a system perspective for heat, powercooling and fuels for vehicles • Overall optimization of production, distribution and consumption

  29. kW (el power) Sum heat and electricity Electricity compensated for sun and wind Household electricity = the difference Time Energy and load control • Monitoring power, heat and temperature in houses and apartments individually • Presentation of consumption shown on displays in the kitchen and on your own web-page • Information and different price models for energy conservation.

  30. Energy and environmental balance for a complete region • Monitor consumption of energy in different forms. Follow key figures. • Investigate possible resources in the region together with the farmers • Evaluate and develop techniques for reaching a sustainable balance between consumption and available resources.

  31. Energibesparing i tillverkningsindustrin • Energianalys vid Seco Tools, TPC, • Västanfors, LEAX, Sjölander, • Components i Virsbo • Många el-maskiner som ger värme, • som bara ventileras bort • Samtidigt köper man fjärrvärme – återvinn! • Lysrör kan ersättas av lysdiodrör på sikt. Återbetalningstid ca 2- 2,5 år. Håller 20-30 år!

  32. Process Development • CO2-free power production with thermal power technology • Separation from exhaust gases • In cooperation with several Chinese universities supported by SIDA + VR (5 PhD students). • Measurement technology – moisture content and biofuel properties with RF and NIR • Energy system with low emissions of fossil CO2 • Fermentation (biological CH4-production) • Black liquor gasification (CH4 +DME + gas combi) • Other fuels like ethanol, rape seed oil etc • CFD- modelling of combustion processes and heat transfer • Fire gas control in closed rooms. Cooperation with SP and others • Water treatment. Cooperation with several plants and Örebro univ.

  33. Energitinget 10-årsjubileum • Arrangör – Energimyndigheten + MDH (+ E-a kommun) • Förra året fick vi börja vara på Älvsjömässan då så stort - 2400 besökare varav 300 utställare • Blir nog ännu större i år. Relativt liten utställning i förhållande till antalet besökare (positivt – du syns!) • Besökare från alla energibolag, många beslutsfattare (politiker), myndigheter, leverantörer, alla högskolor,…. • 12-13 mars 2008 vid Älvsjö • Hemsida: http://www.sverigesenergiting.se/

  34. Cooperation with Industry • Industry cooperation: Mälarenergi, EEoM, ENA, SHEAB, Fortum, Korsnas, ABB, Siemens Turbine, Kvaerner pulp (now Metso), Vallvik Rottneros, Södra Mörrum, Surahammars bruk, Kanthal, Billerud Skarblacka, Nammo, VAFAB, SRV, First Control, Gasilage, Växtkraft, Bombardier, Westinghouse, Cesium, Nammo, • Institutes: STFI, SICS, KCL, PTS, CTP, Interactive Institute

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