PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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CHAPTER 3MODELLINGMICRO-TRIGENERATIONFollowing on from the description of building modelling in Chapter 2, Chapter 3focuses on the micro-trigeneration plant, providing a detailed description of thesystem modelled and the associated control strategies; the control used to maintainadequate indoor temperatures in each of the individual apartments/floors and thecontrol strategy used to control the individual plant components. The chapter alsohighlights the main aspects of modelling plant systems in ESP-r along with thedevelopment of a new dynamic absorption chiller model for use in trigenerationsystem modelling. Finally, the chapter introduces a number of possible trigenerationsystem variants which are analysed in later chapters.90
3.1 Control strategies for the indoor air temperaturesChapter 2 explained that in order to ensure better temperature control of theindividual apartments, each apartment in the two buildings modelled (the 3 and the 6household building) was divided into two zones, a living area and a bedroom areazone. For each individual zone a different control strategy was adopted for both theheating and cooling season, based on whether that particular zone was occupied ornot. The temperature controlled periods during which the indoor temperature in eachzone was controlled, was based on the occupancy. Living area zones were assumedto be occupied between 7 in the morning and midnight (except when the occupancyprofile dictated that the apartment was vacant), whilst bedroom area zones wereconsidered to be occupied from midnight till 7 in the morning. This is typical of a‘working family’ profile in Malta [1].3.1.1 Heating season set control temperaturesThe thermally controlled time periods and (heating season) temperature limits for theindividual zones in the 3 household building were set as shown in Table 3.1. Theheating season was assumed to start on the 17 th of December and finish on the 19 th ofMarch, a 92 day period chosen on the basis of similar heating season durations usedfor other Mediterranean countries [2].Determining with exact precision when heating is required in residential buildings isdifficult given that, in their own domestic environment occupants tend to have muchbetter control of both the surrounding environment and the way they adjust to it,compared to being in public places [3]. Their adaptability is therefore much higher.For example, although people might be inside and according to comfort theory(Fanger [4]) heating may be required, heating may still not be used, as the occupantswould adjust (e.g. by changing clothes, drinking warm beverages etc.). Based on thefact that the daily mean temperatures tend to be lowest during the evening, in thisresearch it was assumed that heating was needed predominantly around this time ofthe day, with the start time being when the apartment would become occupied afterbeing left vacant during the day. Although as reported by Peeters et al. in [3], theWorld Health Organisation recommends a minimum bedroom temperature of 16°C,91
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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
Page 64 and 65: Table 2.4 - Main characteristics of
Page 66 and 67: esolution demand data for individua
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Page 70 and 71: the course of a year. The end resul
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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 82 and 83: Table 2.10 - Annual electrical ener
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
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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 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
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Page 130 and 131: arbitrary cycle configuration, usin
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
Page 138 and 139: general form of equation (3.16) [33
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 146 and 147: the imaginary boundary constituting
Page 148 and 149: the model was then compared to a se
Page 150 and 151: Fig. 3.9 - Modelled chilled water c
Page 152 and 153: standard deviation was calculated t
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
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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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