PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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Comparing Figure 5.3 and 5.4, respectively showing a typical CHP unit switchingdaily profile for the 6 household building with low efficiency fabric (Scenario 2 Low )and the 6 household building with high efficiency fabric (Scenario 2 High ) for a day inFebruary, it can be observed that for the same control scheme, a lower heatingdemand resulting from an improved building fabric requires the CHP unit to work forless hours, but with a slightly more intermittent behaviour.Fig. 5.3 - ‘On’/‘Off’ Cycling during the heating season for the 6 household buildingwith low efficiency fabricFig. 5.4 - ‘On’/‘Off’ Cycling during the heating season for the 6 household buildingwith high efficiency fabricAfter 16.00 Hours when the heating demand was at its maximum, the heat suppliedby the CHP unit in the low efficiency fabric building closely matched the demand,with the hot water return temperature to the tank being continuously lower than the180
set switching ‘On’ signal (65ºC) for the CHP. This resulted in the CHP operatingcontinuously till 24.00 Hours. In the high efficiency fabric building intermittencyvery slightly increased. The difference in this case was of one single ‘On’/‘Off’ cycleover a period of 24 hours; this trend was observed over the entirety of the simulationsdone for the heating season, resulting in a general reduction in the number of cycles,which is most evident in the percentage difference between Scenario 2 High andScenario 2 Low .During the cooling season the CHP unit was controlled in a similar fashion. It washowever observed that during the cooling season improving the building fabricresulted in a marginal decrease in the number of CHP unit switching cycles. This wasnot observed for the entire simulations performed and as shown in Table 5.6 thedifference in number of cycles between the low and high efficiency fabric cases forboth the 3 and the 6 household building was marginal. One reason could be the factthat the lower number of operating hours experienced by the trigeneration feedingthe high efficiency fabric buildings combined with a warmer outside temperatureresulted in a situation where the hot water storage tank experienced less storage heatlosses. Reducing the cooling demand effectively resulted in the CHP unit operatingfor fewer hours but with a more stable load behaviour.The resulting overall effect of improving the building fabric on an annual basis wasthat the number of ‘On’/‘Off’ cycles in the 3 household building (Scenario 1)marginally decreased whilst the number of cycles in the 6 household building(Scenario 2) marginally increased, therefore although the heating/cooling loadchanges significantly for the trigeneration system, the greater stability intemperatures in the improved fabric cases results in cycling remaining almost thesame. Effect of using different plant configurationsChanging the plant configuration had a far more profound effect on cycling thanlowering the thermal demand through improved fabric insulation. Compared toScenario 2 High the addition of a chilled water storage tank in Scenario 3 reduced the181
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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
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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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Page 162 and 163: CHAPTER 4SIMULATIONMETHODOLOGYANDAN
Page 164 and 165: Table 4.1 - Scenarios investigatedS
Page 166 and 167: The building fabric, building size
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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 188 and 189: CHAPTER 5RESULTSANDDISCUSSIONThis c
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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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Page 214 and 215: Table 5.10 - Micro-trigeneration sy
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Page 218 and 219: Table 5.11 - Micro-trigeneration pr
Page 220 and 221: The PES obtained for the different
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Page 224 and 225: Similar results are obtained for al
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Page 228 and 229: Fig. 5.8 - Sensitivity of Emissions
Page 230 and 231: Similarly to the effect on PE SEPAR
Page 232 and 233: 5.5 Micro-trigeneration system econ
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Page 244 and 245: Fig. 5.17 - CF and CF component ter
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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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