1. Introduction - Firenze University Press

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whole pipeline network is canal pipes and 8.2 % overhead pipeline. Other pipelines are in tunnels and undergrounds. The diameter of main pipeline is up to 1200mm. The peak heat load of Tallinn district heating system was 640 MW (-22.6 C) in the 2010/2011 heating season while in the 2009/2010 heating season it had been higher reaching 695 MW (-23.4 C). The minimum heat load during the summer period is 55-65 MW [3]. The district heating systems of Tallinn were mostly constructed in 1960-1980 and their average age is 23 years as of 2012. The district heating systems of Tallinn consist of three connected districts of central heat supply where one of them is divided into two smaller districts, and 26 local boiler houses. Currently two cogeneration plants and three large-scale boiler houses supply heat to the districts of Tallinn. Almost the whole district heating network belongs to the Tallinna Küte company[18]. The Tallinn district heating network is shown in Fig. 1. Fig.1. Tallinn district heating network. Most of the pipelines were built during the rapid industrial growth of the city and thus the pipelines were oversized with a view of future development. After the collapse of Soviet Union many industries were closed. At the moment there are two main problems in the network: bad insulation and oversized pipelines; as a result, heath losses are high. According to the Tallinna Küte AS development plans, the relative heat loss should be reduced by 20%. 3.1. Heat distribution 3.1.1. Model description A model was created for the Tallinn district heating network. The model was designed for 9868 pipes, over 3658 consumers and 9800 nodes with the geographic information included. Different scenarios were simulated for the hydraulic and heat loss analyses: -current consumption and temperature schedule; -current consumption and maximum temperature decrease by 15 °C; - consumption reduced by 20% and current temperature schedule; - consumption reduced by 20% and maximum temperature decrease by 20 °C. In the fourth scenario the temperature is decreased by 20°C and due to the reduced consumption, the water flow can be increased further. For the heat loss analysis the average seasonal temperatures 317
were decreased by 10°C.All scenarios were calculated twice: for the maximum consumption at - 22°C to analyse the hydraulics and for the average seasonal parameters to analyse the heat loss. 3.1.2. Input data and assumptions All the data has been taken from the Tallinna Küte GIS and converted to fit the TERMIS model. Tallinna Küte has also a large statistical database on different parameters in the critical points and consumption of each household during the last ten years. The parameters in critical points are required for model tuning; the number of points depends on the network. The GIS data and other databases can easily be interconnected by using Model Manager. Depending on the model, the estimated or average seasonal consumption can be used while the average seasonal consumption is more justified in most cases. First simulation can be made when the plant parameters like water flow, pressure and temperature are given. After first simulation with the adjustment factors applied, the simulation results should be identical to the known parameters in critical points. Only in this case the input parameters can be changed and it can be assumed that the simulation result is correct. 3.1.3. Results The results of model simulation are shown in Tables 1 to 2. Table 1 shows the results at the maximum consumption and should be used for hydraulic parameters analysis, the Table 2 shows the seasonal average results and should be used for heat loss analysis. Table 1. Simulation results for the maximum consumption at -22°C Outdoor temp. -22°C today -15°C -20% -20°C /-20% Production, MW 678 670 558 546 Consumption, MW 600 600 480 480 Heat loss, MW 78 70 78 66 Heat loss, % 11.5% 10.4% 14.0% 12.1% Water flow, t/h 11180 14070 8920 11890 As it can be seen in Table 2,with changing the yearly average temperature by 10°C, it is possible to reduce the average relative heat loss for a heating season by 1.1% points that makes about 23.2GWh (for the 5800h heating season) or over 4200t/CO2 in case the consumption stays at the same level as today. In case the consumption will be reduced for 20% in the future, the relative heat loss can be reduced by 1.3% compared to the current temperature schedule. However, the relative loss would be higher compared with the present consumption. A possible solution in this case the temperature lowering could be higher, especially, as it can be seen, water flow is only 6,5%. Table 2. Simulation results for average seasonal parameters Season average today -10°C -20% -10°C /-20% Production, MW 324 320 267 263 Consumption, MW 279 279 223 223 Heat loss, MW 45 41 44 40 Heat loss, % 13.9% 12.8% 16.5% 15.2% Water flow, t/h 7280 9260 5800 7340 318
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Proceedings e report 90
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ECOS 2012 : the 25 th International
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Advisory Committee (Track Organizer
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The 25 th ECOS Conference 1987-2012
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VOLUME VI CONTENT VI. 1 CARBON CAPT
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-----------------------------------
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» Personal transportation energy c
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» Excess enthalpies of second gene
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VOLUME IV IV . 1 - FLUID DYNAMICS A
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» Exergy analysis and genetic algo
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» Optimal lighting control strateg
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» Stability and limit cycles in an
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PROCEEDINGS OF ECOS 2012 - THE 25 T
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Fig. 2. The exergy destruction of M
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ineffectiveness of the catalyst, in
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[ P EXmth EX SNG] ESR F where EXm
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Fuel inputkW 728221 203771 237719 3
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Not only at desined Rc (the ratio o
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4. DISCUSSION The graphic exergy an
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Figure 9(a) illustrates the energy
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Engineering Technical Conferences &
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generally there are four kinds of m
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However, even under the off-design
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Fig. 3. 600MW supercritical coal-fi
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CO2 rich loading(molCO2/molMEA) 0.4
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Net efficiency (%) 40.28 30.29 26.4
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Fig. 11. Schematic diagram of heat
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28.67%. In addition, through heat i
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Applied Thermal Engineering 2010;30
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Abstract: PROCEEDINGS OF ECOS 2012
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Fig. 1. Solution diagram of „four
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K ~ K 1 eK 1a p K 1a iK mK
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Oxygen recovery rate, % 105 95 85 7
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Calculated optimal compressor press
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The net amount of the flue gas leav
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Figure 3. Idea for lignite drying b
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Energy efficiency, % 34,00 33,00 32
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points efficiency increase related
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Figure A1b. Thermoflex flow sheet o
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Figure A3a. Thermoflex flow sheet o
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Figure A4. Thermoflex flow sheet of
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2.1. Life Cycle Assessment 2.1.1. G
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these factors. A sensitivity analys
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methane slip contributes to 13% of
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As can be seen in Fig. 5 the impact
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References [1] Eurobserv’er, The
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in which CO2 is separated from H2,
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dimensions of water droplets and wa
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Temperature (°C) 8 7 6 5 4 3 2 1 0
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4. Conclusions In the present paper
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penalty, but without separate captu
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0.5 - 0.7 kg/kg, resulting typicall
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3.3 - Utilising waste heat All exis
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4.5 - Suomusjärvi olivine deposits
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material will change from a few % t
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Fig. 5 Schematic diagram of the PFB
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8. Combined SO2 capture and CO2 min
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Fig. 10 Carbonate- (left) and sulph
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[13] Ekdahl, E., Idman, H. Statemen
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HEAT Fig. 1. Scheme and main reacti
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(raw) materials pre-heating and AS
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Fig 3- Aspen Plus® model 110
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Table 4. Elemental and XRD analysis
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the ÅA CSM route. The content of M
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moisture - 0,2237 ash - 0,0876 LHV
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2.2 CFB plant For the current momen
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The CO2 emission factor which indic
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The CO2 emission factor calculated
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Appendix A Fig A.1. Simulation mode
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(b) Fig. A.2. Simulation model of C
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Table A.1. Calculated parameters at
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References [1] Pfaff I., Oexmann J.
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with a CC installation could be avo
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2.3. Basic CHP plant indices. The b
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3. Off-design calculations The main
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Fig. 6. CHP plant efficiency Fig. 7
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amount of steam delivered to the he
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[5] Lukowicz H., Mroncz M.: Analysi
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water removal is feasible by coolin
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Figure 2. Sketch of the suggested P
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a b Figure 5. a) Exergy balance of
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The basis of comparison of each met
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Figure 7a. Impact of S/CATR on PCU
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However, more energy duty is requir
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3.1. JACOBIAN-ASPEN Interface ASPEN
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Fig. 3. Triple Pressure Bottoming S
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As seen from Table 1, the mass flow
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4. Conclusion Fig. 5. Partial Emiss
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[19] Yantovski E., Shokotov M., Sho
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investigation and the developing of
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University of L’Aquila and German
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hydrogen combustion technology at d
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eversibility of a pre-treated synth
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Fig. 1. TG curves collected for spe
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(see Fig 5). Carbon dioxide uptake
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period is reduced to the first 15 c
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CO2 capture capacity up to 150 th c
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the way for biogas utilisation is t
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projectand is described in the foll
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4. Pilot plant tests In order to de
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Concerning the absorption reaction,
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with Regeneration (AwR), consists i
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[25] Aspen Plus 2004.1. Cambridge,
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systems for fuel drying waste strea
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heated in a heat exchanger placed i
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Fig. 2. Lower heating value of fuel
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Acknowledgements The results presen
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large amount of CO2 [1,5-7]. APCr a
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N 1 i ( x x i n 1 m ) 2.3. Carbon
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DTA analysis of the untreated APCrs
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Table 4. Relative Error (%) of the
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CaO HCl CaCl H O 193kJ / mol (
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[1] M. Fernández Bertos, S.J.R. Si
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2. Process development 2.1. Backgro
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to dissolve the chloride salts prec
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The remaining 25% (5 ml/min) of the
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Table 6. Experimental conversions o
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p p 1 1. 5 p H 1 1. 5 2O p mi
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Calculating from the Aspen Plus mod
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[11] Mattila, H.-P., Experimental s
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Mg2SiO4(s) + 2CO2(g) →2MgCO3(s) +
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(Mg/Fe) of the mineral rock, Mg-sil
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Figure 2. Effect of Mg/Fe ratio of
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Figure 4 shows that an increase in
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Figure 5. Process flow diagram of M
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2. Only cold utility is needed belo
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extraction process at 400 °C (~ 62
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Table A2. Extraction equations and
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[13] Teir S, Kuusik R, Fogelholm CJ
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In the area of coal technologies al
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Tabel 1. Characteristics quantities
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N m eT 4a ~ T cp T4a 1 ( K
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Auxiliary power rate of ASU, % 40 4
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[8] Buhre B.J.P., Elliott L.K., She
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1.1 - Cement Manufacturing The ceme
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2. Numerical model The purpose of t
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Page 337 and 338: In the presented paper a framework
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Page 347 and 348: Site 3 Heat sources Heat load Site
Page 349 and 350: 3.2.2. Input data and assumptions A
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Page 353 and 354: [13] TERMIS Operation User Guide, 7
Page 355 and 356: Polygeneration is a term used to de
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Page 361 and 362: 6. Extensions to core methodology 6
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Page 369 and 370: gasification [15], hybrid biomass g
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1. Introduction - Firenze University Press

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