PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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Table 5.10 - Micro-trigeneration system primary energy consumption and system efficiencyScenarioBuilding fabricScenario descriptionMicro-trigeneration system primaryenergy consumptionShoulder/Heating/Cooling/AnnualPE μTRIGEN(kWh)Micro-trigeneration system efficiencyShoulder/Heating/Cooling/Annualƞ μTRIGEN(%)1 Low1 High2 Low2 High3 High4 High5 High3 Household building with low efficiency building fabric;Basic plant configuration (0.3m 3 hot water tank)3 Household building with high efficiency building fabric;Basic plant configuration (0.3m 3 hot water tank)6 Household building with low efficiency building fabric;Basic plant configuration (0.5m 3 hot water tank)6 Household building with high efficiency building fabric;Basic plant configuration (0.5m 3 hot water tank)6 Household building with high efficiency building fabric;Basic plant configuration (0.5m 3 hot water tank) withadditional 0.3m 3 chilled water tank6 Household building with high efficiency building fabric;Basic plant configuration (0.5m 3 hot water tank) withadditional 2.5m 2 flat plate SWH6 Household building with high efficiency building fabric;Basic plant configuration (0.5m 3 hot water tank). Allelectricity is exported7,974 / 10,847 / 21,114 / 39,936 47.2 / 67.2 / 76.0 / 67.97,974 / 9,467 / 20,437 / 37,878 47.2 / 65.3 / 68.6 / 63.310,929 / 14,920 / 27,847 / 53,696 55.7 / 74.0 / 78.7 / 72.710,929 / 12,165 / 26,812 / 49,906 55.7 / 70.4 / 75.3 / 69.810,929 / 12,165 / 30,624 / 53,718 55.7 / 70.4 / 69.4 / 66.810,179 / 12,102 / 26,425 / 48,705 57.9 / 70.6 / 76.1 / 70.810,929 / 12,165 / 26,812 / 49,906 55.7 / 70.4 / 75.3 / 69.8190
Similarly to other operational characteristics, the primary energy consumption isdependent on the thermal demand of the building. In terms of primary energyconsumption, the results for each scenario are therefore identical for both the currentand high appliances’ electrical efficiency.An important conclusion which can be deduced from the table is that, there exists astrong correlation between the system efficiency and the operational load factor.Excluding the increase due to the parasitic load in the case of Scenario 3 High , (whichaccounts for the added chilled water storage tank) when the useful demand increases,the system efficiency increases. Annual system efficiencies for the differentscenarios varied between a low of 63.3% for the 3 household building with highefficiency fabric to 72.7% for the 6 household building with low efficiency fabric,indicating that the higher the operational load factor, the higher the system efficiency.For the same reasoning, on a seasonal basis, the proposed micro-trigeneration systemdisplayed the highest seasonal efficiency during the cooling season when theoperating load factor was highest and the lowest seasonal efficiency during theshoulder months when the operating load factor was lowest. In terms of operatingconditions effecting system efficiency, it can be concluded that, for a fixed plantsystem size increasing the thermal demand (e.g. by increasing the occupancy of thebuilding), increases the operating load factor which results in an increase in systemefficiency. In contrast for a fixed plant system size, changes aimed at reducing thethermal demand, such as improving the building fabric, will result in lower systemefficiencies.In terms of the different plant configurations, the plant configuration with the highestannual system efficiency (approx. 71%) was the one used in Scenario 4 High , whichincludes the use of a solar water heater working in tandem with the microtrigenerationsystem, whilst the lowest annual efficiency (66.8%) was the one used inScenario 3 High , which includes the additional chilled water storage tank. In Scenario4 High part of the primary energy consumption required was offset by the heatingenergy supplied by the solar water heater. This resulted in a lower micro-191
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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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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
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 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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Page 218 and 219: Table 5.11 - Micro-trigeneration pr
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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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Page 250 and 251: Minimum threshold viability of the
Page 252 and 253: Similarly to the PW and the IRR, it
Page 254 and 255: Table 5.13 - Summary of micro-trige
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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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