PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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1.4.2 The methodology adopted - An overview 161.4.2.1 Selecting the operating conditions to beinvestigated 171.5 Summary of Chapter 1 181.6 Subsequent chapters 191.7 Chapter References 202. MODELLING OF HEAT AND POWER DEMANDS 272.1 Modelling residential demand - Characterisation of abuilding through its energy requirements 282.2 The building simulation tool ESP-r 282.2.1 A quick user guide to modelling combined building andplant systems using ESP-r 282.3 Modelling the building 312.3.1 Example: specifying the building geometrical featuresfor a typical Maltese multi-family residence 322.3.2 Enlarged three storey building to represent 6 householdbuilding 342.3.3 Building fabric 362.3.3.1 Modelling the low efficiency fabric scenario 372.3.3.2 Modelling the high efficiency fabric scenario 382.3.4 Use of the building models developed 402.4 Modelling the electrical demand 412.4.1 Method of profile generation - Overview 412.4.2 Explaining the methodology - A three stage-process 432.4.2.1 Stage 1 - Introducing monthly variation 442.4.2.2 Stage 2 - Converting to 1-min time resolution 492.4.2.3 Stage 3 - Accounting for improvements inenergy-efficiency 522.4.3 Verification of the electrical demand modelling process 542.4.3.1 Normalised verification factor 542.4.3.2 Comparison with other end-measurementcampaigns and research 56vi
2.4.3.3 Aggregated loads frequency distribution 582.4.4 Creating the profiles used in the simulation 602.4.4.1 3 Household building - Seasonal electricalprofiles 602.4.4.2 3 Household building - Current efficiency vs.high efficiency electrical demand scenarios 632.4.4.3 6 Household building 662.5 Modelling the internal heat gains 692.5.1 Internal heat gains - An overview 692.5.2 Internal heat gains due to occupancy 702.5.3 Internal heat gains due to appliances 732.5.3.1 Electrical appliances 732.5.3.2 Non-electrical appliances 752.5.3.3 Aggregated internal heat gains due toappliances 772.5.4 Aggregated internal heat gains and use in simulations 772.6 Domestic Hot Water (DHW) demand 782.6.1 Modelling the DHW demand in Mediterranean climates 782.7 Summary of Chapter 2 812.8 Chapter References 833. MODELLING MICRO-TRIGENERATION 903.1 Control strategies for the indoor air temperatures 913.1.1 Heating season set control temperatures 913.1.2 Cooling season set control temperatures 933.1.3 Intermediate season 953.2 Satisfying the energy demand - The micro-trigenerationplant configuration 953.2.1 Modelling a plant network in ESP-r 963.2.2 Basic plant configuration 973.2.3 Control strategies for the plant 1003.3 The absorption chiller model 1033.3.1 The absorption chiller cycle 103vii
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: TABLE OF CONTENTSACKNOWLEDGEMENTSAB
Page 11 and 12: 4.1.1.1 Factoring for electricity g
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
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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
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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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Page 278 and 279:
Page 280 and 281:
Page 282 and 283:
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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Page 292 and 293:
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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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