Post on 21-Feb-2017
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Practical Experiences With Smart Homes Modelling and Simulation
November 24-25, Dresden
November 24th
Wessam El-Baz, Christian Kandler, Patrick Wimmer, Mark Windeknecht, and Peter Tzscheutschler
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Agenda
• Smart Home Modelling
• Case Study #1: e-MOBILie Project
• Case Study #2: Micro-CHP in the Loop
• Case Study #3: SOFC Modelling and Simulation
• Outlook
2
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Note:
This presentation was published together with a technical paper. The full paper can be downloaded here.Paper Abstract Within the next years, more homes will be equipped with smart metering devices, intelligent devices and home energy management systems (HEMS). The EMS are designed to adapt Demand Side Management (DSM) to households. The goals behind the DSM can vary within the household. It can target shaving the load peaks, minimize CO2 emissions, or minimize the overall energy bill via controlling the in-house energy supply resources and intelligent consuming devices. Thus, the EMS represents the dominant ‘smart home’. Through this contribution, different practices of smart home modeling will be presented in which SimulationX has been integrated under different configurations, software and hardware integrations. The developed models represent the state-of-the art of the current, upcoming and futuristic smart homes. The incentives behind developing these models will be deliberated, along with the economic advantages in its applications within the smart grid. Moreover, the experience behind using SimulationX for evaluating such models will be presented.
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Smart Home Models
P
t
€
model
Occupants Activity
SimulationIrradiance
data
par
amet
ers
pro
cess
ing
ou
tpu
t
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Copyright © ESI Group, 2016. All rights reserved.
Agenda
• Smart Home Modelling
• Case Study #1: e-MOBILie Project
• Case Study #2: Micro-CHP in the Loop
• Case Study #3: SOFC Modelling and Simulation
• Outlook
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e-MOBILie
Project Background
Goals• Development and implementation
of hierarchical and distributedenergy management systems
• evaluation of the environmental benefits of a combination betweenan electric vehicle and local energygeneration
Main focus:• Implementation and operation of an
hardware-in-the-loop test bench forevaluating the integrated energymanagement concept (iEM)
• Demonstration of these concepts in a real residential building and a plus-energy parking garage
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Simulation model framework
e-MOBILie
MATLAB
Physical
Simulation
Building, electrical and
thermal components
SimulationX
[Modelica]
Optimization
Home Energy
Management System
GAMS
[CPLEX solver]
Rolling Horizon
© TUM IfE 69-056-L15
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Results
e-MOBILie
0%
5%
10%
15%
20%
25%
30%
DSM Devices Electric Vehicle Battery Storage Heatpump HEMS
An
nu
al
Co
sts
Savin
gs P
ote
nti
al
[%]
Components
© TUM IfE 69-064-L16
Building: EnEV2012+PV: 7 kWpBattery Storage: 10 kWhDriving Profile: CommuterElectricity Tariff: variable
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Agenda
• Smart Home Modelling
• Case Study #1: e-MOBILie Project
• Case Study #2: Micro-CHP in the Loop
• Case Study #3: SOFC Modelling and Simulation
• Outlook
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9
Test Bed
+ Accuracy
+ Micro CHP Dynamics
+ Operations Constrains
- Costs
- Time
- Lack of building dynamics
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Why HiL?
10
Test BedSimulations
• Building is Modelled
• Thermal Load Profile is generated
• Cooling circuit emulate thermal load via heat exchanger
• CHP cover the generated load
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Why HiL?
11
Test BedHardware in the loop (HiL)
Test BedSimulations
Feedback Loop
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Whispergen Testbed Hydraulic Schematic
12
Source:J. Lipp, F. Sänger, Potential of power shifting using micro–CHP units and heat storages, Microgen 2013, Naples, Italy, 2013
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SimulationX Model Layout
13
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Operation Strategy Overview
14
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Supply-Return Temperature Interaction
1
1
2 3
2
3
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Supply-Return Temperature Interaction
16
1 2 3
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Supply-Return Temperature Interaction
17
TRef= 48.5 °C
TAct= 43 °C
TReturn= 36 → 34 °C
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Agenda
• Smart Home Modelling
• Case Study #1: e-MOBILie Project
• Case Study #2: Micro-CHP in the Loop
• Case Study #3: SOFC Modelling and Simulation
• Outlook
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SOFC micro CHP
GreenBuilding modell with self-written SOFC CHP typ
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SOFC micro CHP
Characteristics of SOFC
0,0 kW
0,2 kW
0,4 kW
0,6 kW
0,8 kW
1,0 kW
1,2 kW
1,4 kW
1,6 kW
15°C 20°C 25°C 30°C 35°C 40°C 45°C 50°C 55°C 60°C 65°C
Thermal Power Heat Efficiency
Heat power and efficiency depending of the return temperature [1]
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SOFC micro CHP
Heat output of the SOFC over one year (reference case)
0,0 kW
0,1 kW
0,2 kW
0,3 kW
0,4 kW
0,5 kW
0,6 kW
0,7 kW
0,8 kW
0,9 kW
0 d
7 d
14
d2
2 d
29
d3
6 d
43
d5
0 d
57
d6
5 d
72
d7
9 d
86
d9
3 d
10
0 d
10
8 d
11
5 d
12
2 d
12
9 d
13
6 d
14
3 d
15
1 d
15
8 d
16
5 d
17
2 d
17
9 d
18
6 d
19
4 d
20
1 d
20
8 d
21
5 d
22
2 d
22
9 d
23
7 d
24
4 d
25
1 d
25
8 d
26
5 d
27
2 d
28
0 d
28
7 d
29
4 d
30
1 d
30
8 d
31
5 d
32
3 d
33
0 d
33
7 d
34
4 d
35
1 d
35
8 d
Heat Power Fuel Cell Reference Case
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SOFC micro CHP
Heat output of the SOFC over one year (35°C Case)
0,0 kW
0,1 kW
0,2 kW
0,3 kW
0,4 kW
0,5 kW
0,6 kW
0,7 kW
0,8 kW
0,9 kW
0 d
7 d
14
d2
2 d
29
d3
6 d
43
d5
0 d
57
d6
5 d
72
d7
9 d
86
d9
3 d
10
0 d
10
8 d
11
5 d
12
2 d
12
9 d
13
6 d
14
3 d
15
1 d
15
8 d
16
5 d
17
2 d
17
9 d
18
6 d
19
4 d
20
1 d
20
8 d
21
5 d
22
2 d
22
9 d
23
7 d
24
4 d
25
1 d
25
8 d
26
5 d
27
2 d
28
0 d
28
7 d
29
4 d
30
1 d
30
8 d
31
5 d
32
3 d
33
0 d
33
7 d
34
4 d
35
1 d
35
8 d
Heat Power Fuel Cell Reference Case Heat Power Fuel Cell 45°C Case Heat Power Fuel Cell 35°C Case
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Smart Heat- Electricity Micro-Grid
Outlook
23
CHP CHP HP CHP HPHPElectricity grid
DH Return
DH Supply
Electricity Heat
3
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Download the Paper
This presentation was published together with a technical paper. The full paper can be downloaded here.Paper Abstract Within the next years, more homes will be equipped with smart metering devices, intelligent devices and home energy management systems (HEMS). The EMS are designed to adapt Demand Side Management (DSM) to households. The goals behind the DSM can vary within the household. It can target shaving the load peaks, minimize CO2 emissions, or minimize the overall energy bill via controlling the in-house energy supply resources and intelligent consuming devices. Thus, the EMS represents the dominant ‘smart home’. Through this contribution, different practices of smart home modeling will be presented in which SimulationX has been integrated under different configurations, software and hardware integrations. The developed models represent the state-of-the art of the current, upcoming and futuristic smart homes. The incentives behind developing these models will be deliberated, along with the economic advantages in its applications within the smart grid. Moreover, the experience behind using SimulationX for evaluating such models will be presented.
24www.esi-group.com
Copyright © ESI Group, 2016. All rights reserved.
M.Sc.
Wessam
El-Baz
Lehrstuhl für Energiewirtschaft
und Anwendungstechnik
Technische Universität München
Fakultät für Elektrotechnik und
Informationstechnik
Arcisstraße 21
80333 München
Tel +49 89 289-28314
Fax +49 89 289-28313
wessam.elbaz@tum.de
Questions