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Validation of a lumped thermal parameter modelcoupled with an EnergyPlus model using BUBBLE data
Miguel Martin1 Afshin Afshari1 Peter Armstrong1
Leslie Norford2 Eberhard Parlow3 Roland Vogt3
1Department of Engineering Systems and ManagementMasdar Institute of Science and Technology, UAE
2Department of ArchitectureMassachusetts Institute of Technology, USA
3Department of Environmental SciencesUniversity of Basel, Switzerland
9th International Conference on Urban Climate, 2015
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 1 / 25
Agenda
Purpose of coupling an urban canopy model with EnergyPlus
Parameters considered by the urban microclimate model
Accuracy of urban temperature estimates in the Sperrstrasse
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 2 / 25
Agenda
Purpose of coupling an urban canopy model with EnergyPlus
Parameters considered by the urban microclimate model
Accuracy of urban temperature estimates in the Sperrstrasse
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 2 / 25
Agenda
Purpose of coupling an urban canopy model with EnergyPlus
Parameters considered by the urban microclimate model
Accuracy of urban temperature estimates in the Sperrstrasse
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 2 / 25
Detailed building energy model
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 3 / 25
Detailed building energy model
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 4 / 25
Detailed building energy model
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 5 / 25
Purpose
How boundary conditions of a building located in an urban area can bemore accurately evaluated to improve estimation of their impact on energyconsumption.
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 6 / 25
Urban temperature computation
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 7 / 25
Urban temperature computation
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 8 / 25
Urban temperature computation
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 9 / 25
Urban temperature computation
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 10 / 25
Urban temperature computation
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 11 / 25
Sensible heat gains
Waste releases: Qwaste = δwaste(1− η)Qc
Traffic: Qtraffic = ItrafficFtraffic (h)
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 12 / 25
Sensible heat gains
Waste releases: Qwaste = δwaste(1− η)Qc
Traffic: Qtraffic = ItrafficFtraffic (h)
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 12 / 25
Validation environment
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 13 / 25
Validation environment
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 14 / 25
Distances
Signal based distances:
I Root mean square errorI Mean bias error
Distribution based distances:
I Kolmogorov-Smirnov distanceI Root mean square of Hellinger distances for normal distributions
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 15 / 25
Distances
Signal based distances:I Root mean square error
I Mean bias error
Distribution based distances:
I Kolmogorov-Smirnov distanceI Root mean square of Hellinger distances for normal distributions
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 15 / 25
Distances
Signal based distances:I Root mean square errorI Mean bias error
Distribution based distances:
I Kolmogorov-Smirnov distanceI Root mean square of Hellinger distances for normal distributions
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 15 / 25
Distances
Signal based distances:I Root mean square errorI Mean bias error
Distribution based distances:
I Kolmogorov-Smirnov distanceI Root mean square of Hellinger distances for normal distributions
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 15 / 25
Distances
Signal based distances:I Root mean square errorI Mean bias error
Distribution based distances:I Kolmogorov-Smirnov distance
I Root mean square of Hellinger distances for normal distributions
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 15 / 25
Distances
Signal based distances:I Root mean square errorI Mean bias error
Distribution based distances:I Kolmogorov-Smirnov distanceI Root mean square of Hellinger distances for normal distributions
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 15 / 25
Distance of Hellinger
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 16 / 25
Root mean square of Hellinger
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 17 / 25
DNI estimation methods
DISC DISC+P DIRINT DIRINT+DP
RM
SE
[W
/m2 ]
0
50
100
150
Strasbourg
DISC DISC+P DIRINT DIRINT+DP
MB
E [
W/m
2 ]
-40-20
020406080
Strasbourg
DISC DISC+P DIRINT DIRINT+DP
RM
SE
[W
/m2 ]
100
200
300
400
Geneva
DISC DISC+P DIRINT DIRINT+DP
MB
E [
W/m
2 ]-100
0
100
200
300Geneva
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 18 / 25
DNI estimation methods
DISC DISC+P DIRINT DIRINT+DP
RM
SE
[K
]
0.5
1
1.5
2
2.5
3
3.5
4
4.5
DISC DISC+P DIRINT DIRINT+DPM
BE
[K
]
-4
-3
-2
-1
0
1
2
3
4
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 19 / 25
Winter temperature estimates
01/01 02/01 03/01
Tem
per
atu
re [
oC
]
-10
-5
0
5
10
15
20
25RMSE = 1.51 [K], MBE = -0.43 [K]
MeasurementsEstimates
Temperature [oC]-20 0 20 40
Fre
qu
ency
[%
]
0
1
2
3K-S = 8.47
LST5 10 15 20T
emp
erat
ure
[oC
]
-10
0
10
20RMSH = 0.04
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 20 / 25
Spring temperature estimates
04/01 05/01 06/01
Tem
per
atu
re [
oC
]
-5
0
5
10
15
20
25
30
35
40RMSE = 1.26 [K], MBE = 0.8 [K]
MeasurementsEstimates
Temperature [oC]-50 0 50
Fre
qu
ency
[%
]
0
1
2
3K-S = 11.03
LST5 10 15 20T
emp
erat
ure
[oC
]
0
10
20
30RMSH = 0.07
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 21 / 25
Conclusion
Urban canopy model coupled with a detailed building energy model
Validation protocol for mean urban temperature in the Sperrstrasse
Daily accuracy of temperature estimates using DISC or DIRINTmodels
Measurements are underestimated in winter and overestimated inspring
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 22 / 25
Conclusion
Urban canopy model coupled with a detailed building energy model
Validation protocol for mean urban temperature in the Sperrstrasse
Daily accuracy of temperature estimates using DISC or DIRINTmodels
Measurements are underestimated in winter and overestimated inspring
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 22 / 25
Conclusion
Urban canopy model coupled with a detailed building energy model
Validation protocol for mean urban temperature in the Sperrstrasse
Daily accuracy of temperature estimates using DISC or DIRINTmodels
Measurements are underestimated in winter and overestimated inspring
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 22 / 25
Conclusion
Urban canopy model coupled with a detailed building energy model
Validation protocol for mean urban temperature in the Sperrstrasse
Daily accuracy of temperature estimates using DISC or DIRINTmodels
Measurements are underestimated in winter and overestimated inspring
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 22 / 25
Thank you for your attention
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 23 / 25
Impact on energy consumption
5 10 15 203
4
5
6
7
8
9
Local time (hours)
Tem
per
atu
re [o
C]
5 10 15 203
4
5
6
7
8
9
10
11
12
Local time (hours)
Bo
iler
fuel
co
nsu
mp
tio
n [
kW]
CSIsolated
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 24 / 25
Winter night impact
+4% average temperature ⇒ -7.2% total fuel consumption
Miguel Martin (Masdar Institute) Coupled scheme validation in Basel July 20, 2015 25 / 25
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