PhD Thesis - Energy Systems Research Unit - University of Strathclyde

More documents

Recommendations

Info

the model was then compared to a separate set of experimental results fromthat used for calibration purposes.3.3.6.1 Inter-model comparisonKohlenbach and Ziegler in [22, 25] performed a dynamic test on their modelwhereby it was first run at steady-state conditions at rated inlet temperatures andmass flow rates and then subjected to a 10°C step increase in hot water circuit inlettemperature. The results obtained in this experiment indicated that it took around 10-minutes for the hot water temperature to stabilise at the new state, and approximately15-minutes for the remaining chiller parameters to reach steady-state, depending onthe thermal mass involved in each internal component. Replicating this test using thedynamic model, the chiller was supplied at steady, rated conditions (hot water circuitinlet temperature of 75°C with a mass flow rate of 0.4 kg/s, chilled water circuit inlettemperature of 18°C with a mass flow rate of 0.8 kg/s and the cooling water circuitinlet temperature of 27°C with a mass flow rate of 0.7 kg/s). A step increase of 10°Cwas then applied to the hot water circuit inlet temperature. The simulation was run ata resolution of 1 second. The results obtained for the proposed model are very closeto those reported by Kohlenbach and Ziegler, with the simulated hot water circuitoutlet temperature modelled stabilising in 620 seconds. The Kohlenbach and Zieglermodel reached a stable state at around 600 seconds; this is a difference of around 3%.3.3.6.2 Comparison with experimental dataThe chiller model was supplied with minute by minute inlet temperaturemeasurements of the three water circuits entering the chiller from an empirical dataset. The model’s output was then compared to the measured data. Figure 3.8 showshow the results obtained for the chilled water outlet temperature data modelled at 1-minute time resolution compare with the measured chilled water outlet temperaturedata.The modelled data closely follows the measured data with identical time responsepatterns, yielding a maximum and mean error of 0.35°C and 0.09°C between themodelled and measured datasets, respectively. The standard deviation is 0.10°C.124
Fig. 3.8 - Measured vs. modelled chilled water dataFigure 3.9 shows how the modelled data (both the raw and smoothed data) comparesto a theoretical ideal fit. The resulting correlation coefficient value between themodelled data and the ideal fit is of 0.995. It can be observed that the modelleddataset is most accurate for a specific range of working temperatures, and that at theextreme end of the modelled temperature range (where the least number of datapoints was available for calibration) a number of outliers are visible.The accuracy of the model lies in its calibration process which is highly susceptibleto the number (and range) of data points used to calibrate the model. The higher thenumber of data points used to calibrate the model the more accurate is the calibrationprocess. Also, having a consistent number of data points over the whole range ofworking and non-working temperatures (including during specific time-periods suchas cold-starts) aides in improving the accuracy of the calibration process. Onelimitation of this model is that the number of data points used for calibration wasrelatively limited and the model’s accuracy therefore suffers from this fact. This doeshowever not prevent the model from producing a reliable representation of the outputof the absorption chiller.125
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 and 8:
TABLE OF CONTENTSACKNOWLEDGEMENTSAB
Page 9 and 10:
2.4.3.3 Aggregated loads frequency
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
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 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
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
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
Page 144 and 145: the internal high and low pressures
Page 146 and 147: the imaginary boundary constituting
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
Page 164 and 165: Table 4.1 - Scenarios investigatedS
Page 166 and 167: The building fabric, building size
Page 168 and 169: analysis in the case of the interme
Page 170 and 171: micro-trigeneration system are thos
Page 172 and 173: profile for that same time period (
Page 174 and 175: 4.2.1.3 Calculating the fuel consum
Page 176 and 177: cogeneration technologies [16].- (4
Page 178 and 179: the present 1.088 kgCO 2 per kWh de
Page 180 and 181: Table 4.4 - Explanation of the cash
Page 182 and 183: FIT and considering the cost involv
Page 184 and 185: impact they have on the energetic,
Page 186 and 187: Conservation in Buildings and Commu
Page 188 and 189: CHAPTER 5RESULTSANDDISCUSSIONThis c
Page 190 and 191: increases so does energy-efficiency
Page 192 and 193: the building fabric is most effecti
Page 194 and 195: Instances where the load duration c
Page 196 and 197: households, GF refers to the ground
Page 198 and 199:
Finally, and this will be the discu
Page 200 and 201:
In the table, the low and high effi
Page 202 and 203:
The scenario with the lowest number
Page 204 and 205:
Comparing Figure 5.3 and 5.4, respe
Page 206 and 207:
number of cycles during the cooling
Page 208 and 209:
5.3.3 Chiller’s performanceAs dis
Page 210 and 211:
5.3.4 Electrical performance of the
Page 212 and 213:
decrease in net imports and net dem
Page 214 and 215:
Table 5.10 - Micro-trigeneration sy
Page 216 and 217:
trigeneration system primary energy
Page 218 and 219:
Table 5.11 - Micro-trigeneration pr
Page 220 and 221:
The PES obtained for the different
Page 222 and 223:
Difference inprimary energybetween
Page 224 and 225:
Similar results are obtained for al
Page 226 and 227:
2 High/High efficiency3 High/Curren
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
Page 234 and 235:
As electricity costs increase (rela
Page 236 and 237:
ii.In the latter case the magnitude
Page 238 and 239:
Resultingdifference incash flowDiff
Page 240 and 241:
Multiple of current electricity tar
Page 242 and 243:
of the system diminishes with incre
Page 244 and 245:
Fig. 5.17 - CF and CF component ter
Page 246 and 247:
shows that exporting all the cogene
Page 248 and 249:
LPG price level when the micro-trig
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
Page 256 and 257:
performance of the micro-trigenerat
Page 258 and 259:
directly affect the system’s ener
Page 260 and 261:
micro-trigeneration system. Convers
Page 262 and 263:
CHAPTER 6CONCLUSION:OUTCOMESANDFUTU
Page 264 and 265:
and power demands of the building.
Page 266 and 267:
circuits associated with the absorp
Page 268 and 269:
the subject. More work therefore ne
Page 270 and 271:
plant models using the building sim
Page 272 and 273:
APPENDIX AEquation factors for sele
Page 274 and 275:
Factors for use in equation (2.1) f
Page 276 and 277:
Page 278 and 279:
Page 280 and 281:
Page 282 and 283:
APPENDIX BElectrical demand profile
Page 284 and 285:
Fig. B4 - Current efficiency electr
Page 286 and 287:
Fig. B10 - High efficiency electric
Page 288 and 289:
Fig. B16 - Current efficiency elect
Page 290 and 291:
Page 292 and 293:
Page 294 and 295:
Component ESP-r Database: Annex 42
Page 296 and 297:
0.0000 #88 Performance map: Thermal
Page 298 and 299:
99.999 #1 Evaporator Total Mass (Fl
Page 300 and 301:
100.00 #13 Boiling temperature of f
Page 302 and 303:
One way to solve a partial differen
Page 304 and 305:
The ‘self coupling term’ is def
Page 306 and 307:
C ******************** CMP73C *****
Page 308 and 309:
&COMMON/PCOND/CONVAR(MPCON,MCONVR),
Page 310 and 311:
C and the inlet point into the solu
Page 312 and 313:
IF(CSVF(INOD1,1).LE.BDATA(IPCOMP,17
Page 314 and 315:
C Calculate T1 (DegC): T1 = ((T16-T
Page 316 and 317:
XST=4010 DST=-(9.133128) + (0.94396
Page 318 and 319:
& + 2500.559)*1000C Refrigerating p
Page 320 and 321:
End IfC Calculate h3 (J/kg): h3=h2+
Page 322 and 323:
&&ElseEnd IfActPow=0ActPow = PCONDR
Page 324 and 325:
C Node 1, thermal mass effected by
Page 326 and 327:
WRITE(ITU,*) ' Connection(s) ',ICON
Page 328 and 329:
Fig. F.1 - IRR for scenarios with d
Page 330 and 331:
Fig. F.5 - PP for scenarios with di
show all

PhD Thesis - Energy Systems Research Unit - University of Strathclyde

Create successful ePaper yourself

Delete template?

Save as template?