1. Introduction - Firenze University Press

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load by the time horizon of the TS. 2,000 kWh could have been covered by direct heat-transfer from solar thermal-energy and 1,140 kWh could have been covered from indirect heat-transfer using storage. This means that the demand 3,140 kWh could have been covered by solar thermal-energy, which is 42.2% of the overall heat demand. The rest of the demand, 4,295 kWh, should still been covered from the utility with constant availability. However, the dependency on fossil fuels should be decreased as much as possible, since this energy source has an impact on the environment. 5.5. Determination of storage size In order to estimate the storage size, the amount of the heat stored or used should be determined in each cTS separately e.g. the heat stored at the cTS1 is H = 220 kW6 h=1320 kWh (Table 2, storage column and Fig 13). These calculated amounts of heat are presented in the boxes of Fig 13. The cumulative amount of stored heat is represented by the numbers outside the boxes (Fig 13). Fig 13A presents the initial cumulative heat stored. As can be seen, in the last cTS12 the amount of stored heat is more than zero. This indicates that smaller storage would also be sufficient. The smallest storage, at which the heat recovery remains the same, would be when the cumulative amount stored at the last cTS is equal to zero (Fig 13B). The storage from this case study should be large enough to store 1,032.4 kWh of heat. The result was determined by the maximal amount of heat within the cascade. However, in order to obtain a proper trade-off besides the rate of heat recovery, also the investment of the storage should be analysed. Fig 13: Cascading the amount of heat in storage through different Time Slices at A) maximal storage and B) reduced storage 6. Conclusions and future work 309
In the presented paper a framework for the integration of solar thermal-energy with processes featuring varying demand was developed. By applying this framework, the amount of solar thermalenergy can be determined, which can be potentially used within the process. As part of the algorithm, the current work offers a systematic procedure capable of identifying Time Slices with an assumed constant solar thermal-energy supply. It is an important step because, to date, Time Slices have mostly been detected heuristically, usually with equal lengths. However, the solar irradiation varies unevenly and the inaccuracy in such a model is high. This current model enables the user to set the accuracy wanted at the stage of analysis. Higher accuracy will result in a larger number of TSs. The presented case study used utility demand as a base case. It illustrated that the demand for a utility with constant availability (usually a fossil fuel) can be reduced by up to 27 % by utilising solar thermal-energy directly, without any storage. A further decrease of up to 15 % (on the same basis) can be achieved by introducing thermal-energy storage. The combined reduction in hot utility resulting from these two steps is about 42 %. This is a significant decrease, which should be encouraging enough taking solar thermal-energy in consideration, during the designing of a utility system. The formulated algorithm offers a simple and fast approach with the accuracy openly available as a degree of freedom for the user. Another important step for achieving better solutions is the simultaneous evaluation of heat supply and demand. As future work, the computer-aided synthesis of the developed framework will be pursued. As a further methodological development, shifting process operations in time (rescheduling) should be considered, in order to achieve as high a usage of direct transfer from solar thermal-energy as possible. 7. Nomenclature HCU cold utility requirement, with constant availability, kW HDTE direct heat-transfer the solar thermal energy to process, kW HE excess of heat after heat recovery, kW HHU hot utility requirement, with constant availability, kW HSTE available solar thermal energy, kW HUR utility requirement after heat recovery, kW A0 initial overall amount of irradiation, kWh m -2 a1 solar collector thermal loss coefficients, W °C -1 m -2 a2 solar collector thermal loss coefficients, W °C -2 m -2 ASi approximated supply over time-interval i, W m -2 CP heat capacity flowrate, kW °C -1 cTS combined time slice EDi the positive and negative difference between the real and approximated supplies together over time-interval i, W m -2 G solar irradiation, W m -2 I set of time boundaries i time boundaries of time intervals INA overall inaccuracy, kWh INi inaccuracy within time-interval i, kWh 310
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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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Page 299 and 300: 1. Define the studied system (in th
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Page 305 and 306: Table 5. Key data for the four ener
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Page 335: cTSs demand TS solar TSs 0 2 4 6 8
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Page 343 and 344: district energy network simulation
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Page 361 and 362: 6. Extensions to core methodology 6
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Page 367 and 368: Abstract: PROCEEDINGS OF ECOS 2012
Page 369 and 370: gasification [15], hybrid biomass g
Page 371 and 372: the second reactor. In this unit, s
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1. Introduction - Firenze University Press

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