PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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Table 2.10 - Annual electrical energy consumption for the households investigatedHousehold codeAnnual electricalconsumption (kWh)Annual electrical consumption perperson (kWh/person)1A 1,370 1,3701B 2,079 2,0792A 1,149 5752B 3,359 1,6803A 4,075 1,3583B 2,219 7404A 2,827 7074B 3,175 794The annual consumption of six out of eight households (75%) was between 2,000and 5,000 kWh per annum - a similar result to that obtained by another researchcampaign conducted in Italy, the MICENE project [52]. The MICENE projectreported that the electrical consumption of 80% of the households analysed during asimilar research had an annual electrical energy consumption of a similar magnitude.2.4.3.3 Aggregated loads frequency distributionOne final method used to verify the profiles created was to compare the statisticalfrequency distribution of the 1-minute temporal electrical load of the aggregated 8households created using the transformation process, with statistical frequencydistributions known to be followed by aggregated household load profiles.Individual domestic load profiles such as that shown in Figure 2.9 for household 4A(for a characteristics day in February), created using Stage 2 of the transformationprocess, do not follow any particular frequency distribution [24].Low voltage aggregated load profiles such as that shown in Figure 2.10 for all 8households for the same day in February however follow skewed statisticaldistributions such as Weibull or Beta distributions [53, 54]. Figure 2.11 shows the fitobtained when the 3 Probability Density Functions (PDF), namely Beta, Weibull andGamma, suggested in literature [53, 54] are superimposed on the demand frequencyhistogram created using the aggregated 1-minute resolution electrical demand of all 8households shown in Figure 2.10. The level of significance calculated using the58
Kolmogorof-Smirnov test exceeds the minimum accepted threshold of 0.05. InFigure 2.11 values are normalised using the highest daily occurring load.Fig. 2.9 - Electrical demand profile for household 4A for a day in FebruaryFig. 2.10 - Aggregated electrical demand profile for all 8 householdsFig. 2.11 - Demand frequency histogram with the PDF superimposed59
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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
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
Page 64 and 65: Table 2.4 - Main characteristics of
Page 66 and 67: esolution demand data for individua
Page 68 and 69: the original data (see equation 2.1
Page 70 and 71: the course of a year. The end resul
Page 72 and 73: specific appliance at a particular
Page 74 and 75: consumption during this period is e
Page 76 and 77: awarded on a random basis following
Page 78 and 79: Table 2.7 - Scaling factors for the
Page 80 and 81: NVF values for washing machines, el
Page 84 and 85: 2.4.4 Creating the profiles used in
Page 86 and 87: Fig. 2.16 - Electrical demand profi
Page 88 and 89: Fig. 2.19 - High efficiency electri
Page 90 and 91: 2.4.4.3 6 Household buildingAs ment
Page 92 and 93: 2.29 and Figure 2.30 show the resul
Page 94 and 95: period [11].In order to improve on
Page 96 and 97: (as discussed by Richardson et al.
Page 98 and 99: similar fashion to the modelling of
Page 100 and 101: observed measurements from a number
Page 102 and 103: Fig. 2.37 - Total internal heat gai
Page 104 and 105: comparing water consumption related
Page 106 and 107: various aspects which make up the h
Page 108 and 109: natural Resources" - (LN 238 of 200
Page 110 and 111: in Domestic Appliances and Lighting
Page 112 and 113: [49] DEFRA (2010). "Dishwashers Gov
Page 114 and 115: CHAPTER 3MODELLINGMICRO-TRIGENERATI
Page 116 and 117: the same research also suggests tha
Page 118 and 119: cooling device in conjunction with
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
Page 128 and 129: efrigerant, which in this case is w
Page 130 and 131: 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
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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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