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dc.contributor.author
Waraich, Rashid A.
dc.contributor.supervisor
Arentze, Theo A.
dc.contributor.supervisor
Axhausen, Kay W.
dc.date.accessioned
2017-10-13T11:38:06Z
dc.date.available
2017-06-11T05:49:18Z
dc.date.available
2017-10-13T11:38:06Z
dc.date.issued
2013
dc.identifier.uri
http://hdl.handle.net/20.500.11850/81317
dc.identifier.doi
10.3929/ethz-a-010111112
dc.description.abstract
Major global concerns for today’s world are the implications of climate change and future energy security. The transportation sector plays an important role within this context, as it currently heavily relies on fossil fuels. In order to break this dependence, electric vehicles could play a key role, especially due to their greater energy conversion efficiency compared with conventional vehicles. Furthermore, by using electricity these vehicles can play an important role in the energy system of the future, where energy generation is envisioned to be more sustainable, incorporating a higher share of renewable energy resources. However, as many of these energy sources are intermittent and require energy storage capacities, the batteries of electric vehicles could take up this role; by exchanging information between electricity demand and supply stakeholders in real-time (“smart grid”), an electric vehicle would charge at times of electricity oversupply and stop charging or even supply energy back to the grid for short periods in times of electricity generation shortage, in order to stabilize the electricity network (“vehicle to grid”).</br>But there are also concerns that the electricity grid, which has not been designed with dynamic demands in time and space in mind, could suffer from the large scale integration of electric vehicles. This could manifest itself in powerline and transformer overloads on lower levels of the electricity network distribution infrastructure. This security and stability of the gird is further at risk due to increased distributed energy generation (including alternative energy) and the liberalization of electricity markets. In this case electricity is traded beyond national borders, leading to possible congestion at powerlines. In order to support the analysis and future design of such complex systems including electric vehicles, integrated modeling of energy demand and supply is needed. This dissertation proposes a framework for such modeling, with particular focus on electricity demand modeling for electric vehicles.</br>As many problems within this context require disaggregated models in time and space, e.g. to uncover bottlenecks in the electricity grid, an existing agent-based travel demand simulation called MATSim is used, which allows the modeling of individual preferences. In order to prepare MATSim for simulation of large scale disaggregated electric vehicle scenarios, a new traffic micro-simulation model is implemented together with other performance enhancements to the framework, making use of parallel computation. Additionally, the current parking model in MATSim is rexi placed by a new parking model, which takes parking supply constraints into account and also supports special parking for electric vehicles with integrated electricity charging facilities. The parking choice model has been developed further towards an initial parking search model in the course of this dissertation.</br>Based on this work, a framework has been developed that integrates various models, including a vehicle fleet definition, vehicle energy consumption models and electricity charging models. In addition, various types of charging infrastructure are modeled including stationary infrastructure with plugs and inductive charging along roads. Furthermore, several types of charging schemes are available including smart charging, where an intelligent central entity in the smart grid is assumed which controls the charging of vehicles.</br>During the course of this dissertation it became evident that there is a lack of integrated and detailed electricity demand and supply models, which hampers interdisciplinary work in the field. Therefore, the framework is being generalized and published as open source under the name “Transportation Energy Simulation Framework”. For many models only basic implementations and interfaces are provided. The idea is that other researchers who are experts within their fields can build on top of it, for example models for “vehicle to grid” applications.</br>A case study for the city of Zurich is presented in this dissertation, which highlights the capabilities of the framework to uncover possible bottlenecks in the electricity network. Furthermore, the case study also highlights the ability of the models to support policy design. To the best of the author’s knowledge such integrated modeling is the first of its kind, in terms of methodology, spatial and temporal resolution and scenario size.
en_US
dc.format
application/pdf
dc.language.iso
en
en_US
dc.publisher
ETH-Zürich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
VEHICLES WITH ELECTRIC TRACTION (VEHICLE ENGINEERING)
en_US
dc.subject
NETWORK STABILITY + VOLTAGE STABILITY (ELECTRICAL DISTRIBUTION NETWORKS)
en_US
dc.subject
NETZSTABILITÄT + SPANNUNGSTABILITÄT (ELEKTRISCHE VERTEILNETZE)
en_US
dc.subject
ENERGY SUPPLY NETWORKS + ELECTRIC DISTRIBUTION NETWORKS (ELECTRICAL DISTRIBUTION NETWORKS)
en_US
dc.subject
ELECTRICAL ENERGY DEMAND + ELECTRICAL POWER CONSUMPTION
en_US
dc.subject
FAHRZEUGE MIT ELEKTROANTRIEB (FAHRZEUGTECHNIK)
en_US
dc.subject
ENERGIEVERSORGUNGSNETZE + ELEKTRISCHE VERTEILUNGSNETZE (ELEKTRISCHE VERTEILNETZE)
en_US
dc.subject
STROMBEDARF + ELEKTRIZITÄTSNACHFRAGE (ELEKTROTECHNIK)
en_US
dc.title
Agent-based simulation of electric vehicles
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2014
ethz.title.subtitle
Design and implementation of a framework
en_US
ethz.size
164 p.
en_US
ethz.code.ddc
DDC - DDC::6 - Technology, medicine and applied sciences::620 - Engineering & allied operations
en_US
ethz.code.ddc
DDC - DDC::6 - Technology, medicine and applied sciences::621.3 - Electric engineering
en_US
ethz.identifier.diss
21633
en_US
ethz.identifier.nebis
010111112
ethz.publication.place
Zürich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::03521 - Axhausen, Kay W. / Axhausen, Kay W.
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt und Landschaft D-ARCH::02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
*
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt und Landschaft D-ARCH
*
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::03521 - Axhausen, Kay W. / Axhausen, Kay W.
ethz.date.deposited
2017-06-11T05:52:40Z
ethz.source
ECOL
ethz.source
ECIT
ethz.identifier.importid
imp593651b14c4e917464
ethz.identifier.importid
imp59366b57c415346962
ethz.ecolpid
eth:8387
ethz.ecitpid
pub:127970
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-13T15:10:12Z
ethz.rosetta.lastUpdated
2021-02-14T19:20:03Z
ethz.rosetta.versionExported
true
ethz.COinS
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