PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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Table 4.1 - Scenarios investigatedScenarioBuilding fabric/ElectricalefficiencyType ofbuilding fabricscenarioElectricalefficiencyscenarioBuildingtype(Occupancy)Type of plantconfiguration1 Low/Current efficiency1 Low/High efficiency1 High/Current efficiency1 High/High efficiencyLow efficiencyfabric scenarioHigh efficiencyfabric scenarioCurrent efficiencyelectrical scenarioHigh efficiencyelectrical scenarioCurrent efficiencyelectrical scenarioHigh efficiencyelectrical scenario3 Householdbuilding(9 Persons)Basic plantconfiguration; Hot waterstorage tank size 0.3m 32 Low/Current efficiency2 Low/High efficiency2 High/Current efficiency2 High/High efficiencyLow efficiencyfabric scenarioHigh efficiencyfabric scenarioCurrent efficiencyelectrical scenarioHigh efficiencyelectrical scenarioCurrent efficiencyelectrical scenarioHigh efficiencyelectrical scenario6 Householdbuilding(18 Persons)Basic plantconfiguration; Hot waterstorage tank size 0.5m 33 High/Current efficiency3 High/High efficiencyHigh efficiencyfabric scenarioCurrent efficiencyelectrical scenarioHigh efficiencyelectrical scenario6 Householdbuilding(18 Persons)Basic plantconfiguration withadditional 0.3m 3 chilledwater tank; Hot waterstorage tank size 0.5m 34 High/Current efficiency4 High/High efficiencyHigh efficiencyfabric scenarioCurrent efficiencyelectrical scenarioHigh efficiencyelectrical scenario6 Householdbuilding(18 Persons)Basic plantconfiguration withadditional 2.5m 2 flatplate SWH; Hot waterstorage tank size 0.5m 35 High/Current efficiency5 High/High efficiencyHigh efficiencyfabric scenarioCurrent efficiencyelectrical scenarioHigh efficiencyelectrical scenario6 Householdbuilding(18 Persons)Basic plantconfiguration; Allcogenerated electricitywas exported to thegrid; Hot water storagetank size 0.5m 3The different cases in Scenario 1 were used to investigate the effect of improving thebuilding fabric and reducing the electrical demand on micro-trigeneration systemperformance. The building type used (including the associated occupancy and thethermal, electrical and DHW loads) was that of the 3 household building and theplant configuration used was the basic plant configuration shown in Figure 3.2.Scenario 2 had primarily the same scope as Scenario 1 that is, to study the impact ofimproving the building fabric and reducing the electrical demand on micro-140
trigeneration system performance. However, the building type used was the 6household building. Scenario 1 and 2 could be therefore compared to study the effectbuilding size and occupancy have on micro-trigeneration system performance.Whereas the first two scenarios investigated operating conditions which affect thedemand side, Scenarios 3 and 4, examined in detail the effect changes in the plantconfiguration have on the system performance. Scenario 3 was used to investigatethe use of a chilled water storage tank as a buffer between the absorption chiller andthe cooling coils as shown in Figure 3.12. Scenario 4 was used to study the use of flatplate SWH system working in tandem with the micro-trigeneration system as shownin Figure 3.13. Given that the building type and the building fabric used for thesescenarios were identical to the one used in Scenario 2 High (6 household building withhigh efficiency fabric), the individual cases in Scenario 2 High (2 High/Current efficiency and2 High/High efficiency ) served as the base case scenarios against which Scenarios 3 and 4were compared.Finally, Scenario 5 investigated the effect of exporting all the cogenerated electricityproduced by the system to the grid, rather than using it to satisfy the building’s ownelectrical demand and then exporting the excess to the grid, as done in all otherscenarios. In this context, it is important to clarify that currently the only Feed-inTariff (FIT) present in Malta is the one payable for photovoltaic produced electricitywhich is exported to the grid [1]. Any electricity used to satisfy own demand ismetered for records through a second separate meter, but is not paid for. This resultsin a situation where people can opt to sell all their electricity generated and importelectricity from the grid to cover for their own demand [2]. Depending on thedifference between the electricity tariff and the FIT, and the type of user (theelectricity tariff in Malta is based on tariff bands where the cost per unit of importedelectricity becomes increasingly higher with increasing consumption) it may makemore financial sense to sell the electricity produced rather than use it for ownconsumption. The FIT proposed in this research (and which is explained in muchmore detail in Section 4.2.3.1) works on a similar principle.141
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University of StrathclydeDepartment
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ACKNOWLEDGEMENTSIt has been a long
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ABSTRACTThe domestic sector account
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TABLE OF CONTENTSACKNOWLEDGEMENTSAB
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2.4.3.3 Aggregated loads frequency
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4.1.1.1 Factoring for electricity g
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5.5.1.2 Present worth assuming a va
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LIST OF FIGURESFig. 1.1 Separate ge
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Fig. 2.38 Aggregated DHW draw profi
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Fig. 5.23 PP for Scenarios 1 and 2
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uilding 95Table 3.5 Control scheme
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ACRONYMS & ABBREVATIONSBMS Building
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CHAPTER 1INTRODUCTIONChapter overvi
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uildings, and Directive 2006/32/EC
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Micro-cogeneration can make use of
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offer reasonable and adequate retur
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system in a residential building, i
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conditions have on the performance
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effective manner. The research in t
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investigate how a residential micro
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Table 1.1 also includes additional
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1.7 Chapter References[1] DG for En
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[18] Pehnt, M., Cames, M., Fischer,
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[39] Cardona, E. and Piacentino, A.
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[56] Shin, Y., Seo, J.A., Cho, H.C,
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2.1 Modelling residential demand -
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minute resolution data. The researc
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2.3.1 Example: specifying the build
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Table 2.1 - Dimensions of the model
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In this second enlarged building, t
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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
Page 114 and 115: CHAPTER 3MODELLINGMICRO-TRIGENERATI
Page 116 and 117: the same research also suggests tha
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Page 120 and 121: simulation tool ESP-r by explaining
Page 122 and 123: Fig 3.2 - Basic micro-trigeneration
Page 124 and 125: 3.2.3 Control strategies for the pl
Page 126 and 127: or decrease the flow rate of the co
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Page 132 and 133: coefficients for the future and pre
Page 134 and 135: Applying basic energy and mass cons
Page 136 and 137: CH Power , the chiller’s refriger
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Page 140 and 141: functions of hot water circuit inle
Page 142 and 143: circuit were obtained and how the p
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Page 148 and 149: the model was then compared to a se
Page 150 and 151: Fig. 3.9 - Modelled chilled water c
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Page 154 and 155: The selected tank size is based on
Page 156 and 157: 3.5 Summary of Chapter 3This chapte
Page 158 and 159: Conservation in Buildings and Commu
Page 160 and 161: uilding simulation." Doctoral Thesi
Page 162 and 163: CHAPTER 4SIMULATIONMETHODOLOGYANDAN
Page 166 and 167: The building fabric, building size
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Page 170 and 171: micro-trigeneration system are thos
Page 172 and 173: profile for that same time period (
Page 174 and 175: 4.2.1.3 Calculating the fuel consum
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Page 178 and 179: the present 1.088 kgCO 2 per kWh de
Page 180 and 181: Table 4.4 - Explanation of the cash
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Page 184 and 185: impact they have on the energetic,
Page 186 and 187: Conservation in Buildings and Commu
Page 188 and 189: CHAPTER 5RESULTSANDDISCUSSIONThis c
Page 190 and 191: increases so does energy-efficiency
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Page 194 and 195: Instances where the load duration c
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Page 198 and 199: Finally, and this will be the discu
Page 200 and 201: In the table, the low and high effi
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Page 204 and 205: Comparing Figure 5.3 and 5.4, respe
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Page 208 and 209: 5.3.3 Chiller’s performanceAs dis
Page 210 and 211: 5.3.4 Electrical performance of the
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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
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APPENDIX BElectrical demand profile
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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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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
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Fig. F.1 - IRR for scenarios with d
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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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