PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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3.3.2 Steady-state vs. dynamic modelling 1053.3.2.1 Existing dynamic models 1053.3.3 Requirement for a new dynamic model 1063.3.4 Development of the proposed model 1063.3.4.1 The control volume concept 1063.3.4.2 The control volume concept used to model thethermal transients inside the chiller 1083.3.4.3 Finding the state points within the chiller 1113.3.5 Model calibration 1153.3.5.1 Calibration stage 1: Obtaining the cycle highand low pressures in terms of the hot watercircuit inlet temperature 1173.3.5.2 Calibration stage 2: Obtaining the chiller’srefrigerating power output as a function ofwater circuits’ inlet temperatures 1193.3.5.3 Calibration stage 3: Obtaining the total massand the mass weighted average specific heatcapacity of each individual node 1213.3.6 Verification of the proposed model 1233.3.6.1 Inter-model comparison 1243.3.6.2 Comparison with experimental data 1243.3.7 Use in plant networks 1283.4 Variants in plant configuration 1283.4.1 Use of chilled water storage tank 1283.4.2 Use of a SWH system in tandem with microtrigeneration1303.5 Summary of Chapter 3 1323.6 Chapter References 1334. SIMULATION METHODOLOGY AND ANALYSISMETRICS 1384.1 Simulation methodology 1394.1.1 Scenarios investigated 139viii
4.1.1.1 Factoring for electricity grid improvements 1424.1.1.2 Factoring for varying LPG prices andelectricity tariffs 1424.1.2 Weekly, monthly, seasonal and annual analysis 1434.2 Analysis metrics 1444.2.1 Energetic performance metrics 1454.2.1.1 Supplied thermal energy 1464.2.1.2 Calculating the electrical performance of thesystem 1474.2.1.3 Calculating the fuel consumption and theprimary energy consumption 1504.2.1.4 Overall micro-trigeneration system efficiency 1504.2.1.5 Comparison with separate generation – thegrid network efficiency 1504.2.2 Environmental performance metrics 1524.2.2.1 Calculating the carbon footprint of the microtrigenerationsystem 1524.2.2.2 Comparison with separate generation – thegrid network emission factor 1534.2.3 Economic performance metrics 1544.2.3.1 Financial parameters used in modelling 1544.2.3.2 Net present value - Present worth 1584.2.3.3 Internal rate of return 1594.2.3.4 Payback period 1594.3 Summary of Chapter 4 1594.4 Chapter References 1615. RESULTS AND DISCUSSION 1645.1 Effect on thermal demand of improving the building fabric 1655.1.1 Analysis of space conditioning energy requirements –Heating period 1655.1.2 Analysis of space conditioning energy requirements –Cooling season 167ix
Page 1 and 2: University of StrathclydeDepartment
Page 3 and 4: ACKNOWLEDGEMENTSIt has been a long
Page 5 and 6: ABSTRACTThe domestic sector account
Page 7 and 8: TABLE OF CONTENTSACKNOWLEDGEMENTSAB
Page 9: 2.4.3.3 Aggregated loads frequency
Page 13 and 14: 5.5.1.2 Present worth assuming a va
Page 15 and 16: LIST OF FIGURESFig. 1.1 Separate ge
Page 17 and 18: Fig. 2.38 Aggregated DHW draw profi
Page 19 and 20: Fig. 5.23 PP for Scenarios 1 and 2
Page 21 and 22: uilding 95Table 3.5 Control scheme
Page 23 and 24: ACRONYMS & ABBREVATIONSBMS Building
Page 25 and 26: CHAPTER 1INTRODUCTIONChapter overvi
Page 27 and 28: uildings, and Directive 2006/32/EC
Page 29 and 30: Micro-cogeneration can make use of
Page 32 and 33: offer reasonable and adequate retur
Page 34 and 35: system in a residential building, i
Page 36 and 37: conditions have on the performance
Page 38 and 39: effective manner. The research in t
Page 40 and 41: investigate how a residential micro
Page 42 and 43: Table 1.1 also includes additional
Page 44 and 45: 1.7 Chapter References[1] DG for En
Page 46 and 47: [18] Pehnt, M., Cames, M., Fischer,
Page 48 and 49: [39] Cardona, E. and Piacentino, A.
Page 50 and 51: [56] Shin, Y., Seo, J.A., Cho, H.C,
Page 52 and 53: 2.1 Modelling residential demand -
Page 54 and 55: minute resolution data. The researc
Page 56 and 57: 2.3.1 Example: specifying the build
Page 58 and 59: Table 2.1 - Dimensions of the model
Page 60 and 61:
In this second enlarged building, t
Page 62 and 63:
Table 2.3 - Main characteristics of
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Table 2.4 - Main characteristics of
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esolution demand data for individua
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the original data (see equation 2.1
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the course of a year. The end resul
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specific appliance at a particular
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consumption during this period is e
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awarded on a random basis following
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Table 2.7 - Scaling factors for the
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NVF values for washing machines, el
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Table 2.10 - Annual electrical ener
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2.4.4 Creating the profiles used in
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Fig. 2.16 - Electrical demand profi
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Fig. 2.19 - High efficiency electri
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2.4.4.3 6 Household buildingAs ment
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2.29 and Figure 2.30 show the resul
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period [11].In order to improve on
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(as discussed by Richardson et al.
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similar fashion to the modelling of
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observed measurements from a number
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Fig. 2.37 - Total internal heat gai
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comparing water consumption related
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various aspects which make up the h
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natural Resources" - (LN 238 of 200
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in Domestic Appliances and Lighting
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[49] DEFRA (2010). "Dishwashers Gov
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CHAPTER 3MODELLINGMICRO-TRIGENERATI
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the same research also suggests tha
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cooling device in conjunction with
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simulation tool ESP-r by explaining
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Fig 3.2 - Basic micro-trigeneration
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3.2.3 Control strategies for the pl
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or decrease the flow rate of the co
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efrigerant, which in this case is w
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arbitrary cycle configuration, usin
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coefficients for the future and pre
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Applying basic energy and mass cons
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CH Power , the chiller’s refriger
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general form of equation (3.16) [33
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functions of hot water circuit inle
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circuit were obtained and how the p
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the internal high and low pressures
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the imaginary boundary constituting
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the model was then compared to a se
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Fig. 3.9 - Modelled chilled water c
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standard deviation was calculated t
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The selected tank size is based on
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3.5 Summary of Chapter 3This chapte
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Conservation in Buildings and Commu
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uilding simulation." Doctoral Thesi
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CHAPTER 4SIMULATIONMETHODOLOGYANDAN
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Table 4.1 - Scenarios investigatedS
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The building fabric, building size
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analysis in the case of the interme
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micro-trigeneration system are thos
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profile for that same time period (
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4.2.1.3 Calculating the fuel consum
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cogeneration technologies [16].- (4
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the present 1.088 kgCO 2 per kWh de
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Table 4.4 - Explanation of the cash
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FIT and considering the cost involv
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impact they have on the energetic,
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Conservation in Buildings and Commu
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CHAPTER 5RESULTSANDDISCUSSIONThis c
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increases so does energy-efficiency
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the building fabric is most effecti
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Instances where the load duration c
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households, GF refers to the ground
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Finally, and this will be the discu
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In the table, the low and high effi
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The scenario with the lowest number
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Comparing Figure 5.3 and 5.4, respe
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number of cycles during the cooling
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5.3.3 Chiller’s performanceAs dis
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5.3.4 Electrical performance of the
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decrease in net imports and net dem
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Table 5.10 - Micro-trigeneration sy
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trigeneration system primary energy
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Table 5.11 - Micro-trigeneration pr
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The PES obtained for the different
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Difference inprimary energybetween
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Similar results are obtained for al
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2 High/High efficiency3 High/Curren
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Fig. 5.8 - Sensitivity of Emissions
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Similarly to the effect on PE SEPAR
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5.5 Micro-trigeneration system econ
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As electricity costs increase (rela
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ii.In the latter case the magnitude
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Resultingdifference incash flowDiff
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Multiple of current electricity tar
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of the system diminishes with incre
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Fig. 5.17 - CF and CF component ter
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shows that exporting all the cogene
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LPG price level when the micro-trig
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Minimum threshold viability of the
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Similarly to the PW and the IRR, it
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Table 5.13 - Summary of micro-trige
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performance of the micro-trigenerat
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directly affect the system’s ener
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micro-trigeneration system. Convers
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CHAPTER 6CONCLUSION:OUTCOMESANDFUTU
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and power demands of the building.
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circuits associated with the absorp
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the subject. More work therefore ne
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plant models using the building sim
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APPENDIX AEquation factors for sele
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Factors for use in equation (2.1) f
Page 276 and 277:
Page 278 and 279:
Page 280 and 281:
Page 282 and 283:
APPENDIX BElectrical demand profile
Page 284 and 285:
Fig. B4 - Current efficiency electr
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Fig. B10 - High efficiency electric
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Fig. B16 - Current efficiency elect
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Page 292 and 293:
Page 294 and 295:
Component ESP-r Database: Annex 42
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0.0000 #88 Performance map: Thermal
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99.999 #1 Evaporator Total Mass (Fl
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100.00 #13 Boiling temperature of f
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One way to solve a partial differen
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The ‘self coupling term’ is def
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C ******************** CMP73C *****
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&COMMON/PCOND/CONVAR(MPCON,MCONVR),
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C and the inlet point into the solu
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IF(CSVF(INOD1,1).LE.BDATA(IPCOMP,17
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C Calculate T1 (DegC): T1 = ((T16-T
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XST=4010 DST=-(9.133128) + (0.94396
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& + 2500.559)*1000C Refrigerating p
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End IfC Calculate h3 (J/kg): h3=h2+
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&&ElseEnd IfActPow=0ActPow = PCONDR
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C Node 1, thermal mass effected by
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WRITE(ITU,*) ' Connection(s) ',ICON
Page 328 and 329:
Fig. F.1 - IRR for scenarios with d
Page 330 and 331:
Fig. F.5 - PP for scenarios with di
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PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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