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Information Brochure Ph.D. 2007­2008 Indian Institute of Technology Bombay 1
  • library has now more than 3 lakhs books and volumes and subscribes to over  1500 current journals in science
  • in  engineering
  •  2007 june 8
  • indian institute of technology bombay powai
  • intelligent  systems
  • and  involves a minimum course credit requirement and research thesis
  • water  quality   management
  • research  assistantship
Published : Tuesday, March 27, 2012
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Origin : bwk.tue.nl
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Graduation project for the
Sustainable Energy
Technology Master Program
Department of the Built
Environment
Group of Building Physics and
Systems

Den Dolech 2, 5612 AZ
Eindhoven
P.O. Box 513, 5600 MB

Eindhoven
The Netherlands
www.tue.nl

Author Design concept for optimizing the renewable
ing. Jeroen van
Hellenberg Hubar micro generation technologies to supply an off-

Date grid community energy demand: A case study
December 20, 2011
with simulation model in the Netherlands.









st 1 Supervisor: Prof.dr.ir. Jan Hensen
nd 2 Supervisor: dr. Dipl. – ing. Marija Trcka
rd3 Supervisor: Bruno Lee, MSc Graduation project for the
Sustainable Energy
Technology Master Program
Department of the Built
Environment
Group of Building Physics and
Systems

Den Dolech 2, 5612 AZ
Eindhoven
P.O. Box 513, 5600 MB
Eindhoven
The Netherlands
www.tue.nl


Author
ing. Jeroen van
Hellenberg Hubar

Date
December 20, 2011
A generated Wordle: The size of the word is proportional to the appearance of the word in the abstract. Abstract
Our energy consumption is the main cause of climate change because of the carbon
dioxide emission generated during its production. Without technological improve-
ments and new policies, the International Energy Agency (IEA) predicts a rapid
growth of carbon dioxide in our atmosphere in the coming years. To avert this sce-
nario, energy efficient and sustainable energy technologies are being introduced in
various sectors. The building sector accounts for almost 30% to the global carbon
dioxide emissions. Since the buildings are generally connected to an energy grid, the
source of energy used in the is neither a choice nor concern of the build-
ing owner / designer. Consequently the possibility of reducing the carbon dioxide
emissions, generated by energy production, is limited. However, it will be a concern
to the building owner / designer when the building is located in a remote area that
is completely off the grid.
This research is aimed towards creating a design concept for an off-grid commu-
nity, which has an optimized energy system with 100% renewable micro-generation
technologies. The renewable technologies satisfy the electrical and thermal
energy demand. Meanwhile the comfort level of the inhabitants for an off-grid com-
munityisensured. Todemonstratethedesignconcept, acasestudyofahypothetical
campground located on the island of Texel in the Netherlands is performed.
First a literature study is conducted on campgrounds on the island of Texel and
the local norms in the Netherlands. Annual energy demand profiles with hourly
results are created and considered as input for the simulation model in TRNSYS. In
this simulation model the energy demand profiles are coupled to the modeled camp-
ground buildings. These demands, together with the energy technologies, balance
the electrical and thermal energy. The energy technologies are modified into deci-
sion variables, and defined in the optimization software modeFRONTIER. Next the
objective functions of minimizing the carbon dioxide emission and minimizing the
investment costs are added. The multi objective optimization in modeFRONTIER
results in 2000 renewable energy technology system configurations. After post pro-
cessing and considering the stakeholders perspectives, one configuration was proven
the most favorable.
The most optimized configurations (topmost 25% in the case study) present a trend,
regarding the objective functions. It shows a small installed capacity of solar collec-
torsandbatterystoragebutahighinstalledcapacityofbiomassCombinedHeatand
Power (CHP). In these configurations the CHP is a dominating energy technology
because it has low installation costs per installed kW, low life cycle carbon dioxide
iemissions, simultaneous production of electrical and thermal energy and high annual
production hours. These results are only valid for this case study. Because in ideal
decision making between technologies, one technology is independently evaluated to
the others. In the case study energy technologies in the simulation model became
interconnected, controlled and dependent on the specifications of each other. In
this way not a full energy system spectrum optimization with independent energy
technologies could be performed. Yet to demonstrate the design concept, only a pre
defined sub-system is optimized. Therefore the results of the sub-system optimiza-
tion are only valid for the energy system as designed in the case study with these
energy technologies in this specific configuration.
The design concept its applicability is demonstrated by the case study on the island
of Texel. The proposed concept is valid for each type of off-grid community and
energytechnologyconfiguration, sincethesecanbedefinedintheliteratureresearch.
While generating the energy profiles and modeling the simulation and optimization
model, the designer should keep all the possible energy technology configurations
open. In such a way no choices, even unaware, are made between energy system
configurations which bound the energy system optimization space. In this way a
full spectrum optimization with independent energy technologies can be achieved in
future research, and ideal decision making will be enhanced.
iiiiiNomenclature
oC Degree centigrade
A Ampère
AM Air mass
g Gram
h Hour
Hz Hertz
kJ Kilo Joule
km Kilometer
2km Square kilometer
kton Kiloton
kW Kilowatt
kW Kilowatt electricale
kW Kilowatt thermalth
kWh Kilowatt hour
m Meter
2m Square meter
3m Cubic meter
mm Millimeter
s Second
V Voltage
W Watt
ivAbbreviations
AC Alternating Current
ACSI Auto Camper Service International
BPS Building Performance Simulation
CHP Combined Heat and Power
COP Cooefficient Of Performance
DC Direct Current
DHW Domestic Hot Water
DoE Design of Experiments
ECBCS Energy Conservation in Buildings and Community Systems
ECN Energy Research Center of the Netherlands
EPBD Energy Performance of Building Directive
ETP Energy Technology Perspective
GA Genetic Algorithm
IEA International Energy Agency
IPCC Intergovernmental Panel on Climate Change
ISSO Dutch Knowledge Institute for the Installation Sector
MCDM Multi Criteria Decision Making
MODM Multi Objective Decision Making
MOGA Multi Objective Genetic Algorithm
MPP Maximum Power Point
OECD Organization for Economic Co-operation and Development
PV PhotoVoltaics
SHC Solar Heating and Cooling program
STC Standard Test Condition
TRNSYS TRaNsient SYstem Simulation
ULH Uniform Latin Hypercube
VEWIN Association of water companies in the Netherlands
vAcknowledgments
This thesis is the result of a year of work for my graduation project of the master
Sustainable Energy Technology with the specialization “Energy in the built Envi-
ronment” at the faculty of the Built Environment at the Eindhoven University of
Technology.
In the beginning of 2010 I had contact with dr.ir. Marcel Loomans and Prof.ir.
Paul Rutten. They told me about the possibilities to graduate within the faculty
of built environment and introduced me to prof.dr.ir Jan Hensen and Bruno Lee
MSc. After discussing the possibilities for graduation in the year 2010-2011 first a
research internship (SIP II) was performed in this research group to the “Electrical
energy balance analysis for an off-grid campground site”. The results of the research
internship where the starting point of this thesis project which actually started at
January 2011
I want to express my gratitude to Bruno Lee MSc, who was my daily contact within
the building performance simulation research group. The meetings with Bruno
where inspiring and he had always time for discussion. With his help I overcame
some problems in TRNSYS and modeFRONTIER. I also would like to thank my
othersupervisorsProf.dr.irJanHensenanddr.dipl.-ingMarijaTrckawhosupervised
me from a distance and challenged me with the right questions during the meeting
and/orprogresspresentations. Forthesechallengingandcommentsduring
the progress meetings I also want to thank the rest of the BPS research group and
the students. Special thanks go out to the students Sundaravelpandian Singaravel,
Bart van Pelt, Dennis van Goch, Bastiaan van Wijk, Tom Hissel, Onur Kaya and
Serdar Özen for supporting and joining me each day in the library of the TU/e.
Furthermore I would like to thank my friends and roommates at Gestelgroen for
listeningtomygraduationstoriesandbeingsupportivethroughoutthewholemaster
at the TU/e.
Finally, and definitely most of all, I would like to thank my parents, family and
Janine van Bergen, my girlfriend. Without their unconditional support throughout
my (pre-) masters this thesis would not have been possible.
ing. Jeroen van Hellenberg Hubar
Eindhoven, December 2011
viContents
Abstract i
Nomenclature iv
Acknowledgments vi
1. Introduction 1
1.1. Trias Energetica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2. Building Performance Simulation . . . . . . . . . . . . . . . . . . . . 4
1.3. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4. Report outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2. Methodology 6
2.1. Literature research . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.1. Off-grid community . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.2. Local comfort norms . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.3. Community buildings . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.4. Demand profiles . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.5. Energy technologies . . . . . . . . . . . . . . . . . . . . . . . 8
2.2. Modeling & simulation . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3. Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.1. Objective functions . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.2. Multi Objective optimization . . . . . . . . . . . . . . . . . . 10
2.3.3. Decision variables . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3.4. Post processing . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.4. Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3. Case study 13
3.1. Design input parameters . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.1.1. Geographical input . . . . . . . . . . . . . . . . . . . . . . . . 13
3.1.2. Types of campgrounds . . . . . . . . . . . . . . . . . . . . . . 14
3.1.3. Energy demand . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2. Energy demand generator . . . . . . . . . . . . . . . . . . . . . . . . 18
3.3. technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.4. Modeling & simulation . . . . . . . . . . . . . . . . . . . . . . . . . . 23
vii3.5. Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.5.1. Objective functions . . . . . . . . . . . . . . . . . . . . . . . 25
3.5.2. Design constraints . . . . . . . . . . . . . . . . . . . . . . . . 26
3.5.3. Decision variables . . . . . . . . . . . . . . . . . . . . . . . . 26
3.5.4. Optimization Algorithm . . . . . . . . . . . . . . . . . . . . . 27
4. Result and discussion 28
4.1. Results derived from the case study . . . . . . . . . . . . . . . . . . . 28
4.1.1. Design constraints . . . . . . . . . . . . . . . . . . . . . . . . 28
4.1.2. Pareto front . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.1.3. Energy technologies . . . . . . . . . . . . . . . . . . . . . . . 33
4.1.4. Most optimal solution . . . . . . . . . . . . . . . . . . . . . . 35
4.2. Results derived from the methodology . . . . . . . . . . . . . . . . . 37
4.2.1. Design concept derived from the methodology . . . . . . . . . 37
4.2.2. Protocol derived from the methodology . . . . . . . . . . . . . 39
4.2.3. Design concept applied on the case study . . . . . . . . . . . . 41
5. Conclusion 45
6. Future work 49
Bibliography 51
Appendix 56
A. ASCI campgrounds 57
B. Accomodations 59
C. List of facilities on campground 61
D. Short explanation of the facilities 63
E. Energy demand profiles 67
F. Heat loss calculation 69
G. Mock-up of the TRNSYS model 73
H. TRNSYS equipment explaination 75
I. Mock up of the modeFRONTIER model 81
viii

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