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Static and Dynamic Vehicle-to-Grid Potential with Electrified Roads
KTH, School of Electrical Engineering (EES), Electric Power Systems.
KTH, School of Electrical Engineering (EES), Electric Power Systems.ORCID iD: 0000-0002-8189-2420
2013 (English)In: 2013 IEEE Innovative Smart Grid Technologies - Asia, 2013Conference paper, Published paper (Refereed)
Abstract [en]

A large scale introduction of electric vehicles (EVs) enables for interesting opportunities such as meeting the need for power balancing in the electric system. With increased introduction of variable and renewable electricity production resources such as wind power and solar power, the need for power balancing also increases. If EV batteries can be used as individual and flexible storages performing vehicle-to-grid (V2G) services with or without the possibility to inject power to the grid, this increased need for power balancing could be met. This paper investigates the potential for individual and flexible EV batteries to be used for V2G services by introducing a new model. With the model it is possible to estimate the potential for V2G power consumption and power injection with a well-developed charging infrastructure including dynamic EVC at electrified roads (ERs) and static EVC at parking sites. The model includes models for time-dependent V2G potential, dynamic EVC at ERs, static EVC at parking sites, vehicle mobility and vehicle driving power demand. A case study shows the resulting V2G potential for power consumption and power injection under different conditions with a charging infrastructure including both dynamic and static EVC infrastructure.

Place, publisher, year, edition, pages
2013.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-152236DOI: 10.1109/ISGT-Asia.2013.6698782Scopus ID: 2-s2.0-84893297039ISBN: 978-1-4799-1346-6 (print)OAI: oai:DiVA.org:kth-152236DiVA: diva2:749476
Conference
IEEE Innovative Smart Grid Technologies Asia 2013, (ISGT Asia 2013)
Note

QC 20140924

Available from: 2014-09-24 Created: 2014-09-24 Last updated: 2014-09-24Bibliographically approved
In thesis
1. Electric Vehicle Charging Modeling
Open this publication in new window or tab >>Electric Vehicle Charging Modeling
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

With an electrified passenger transportation fleet, carbon dioxide emissions could be reduced significantly depending on the electric power production mix. Increased electric power consumption due to electric vehicle charging demands of electric vehicle fleets may be met by increased amount of renewable power production in the electrical systems. With electric vehicle fleets in the transportation system there is a need for establishing an electric vehicle charging infrastructure that distributes this power to the electric vehicles. Depending on the amount of electric vehicles in the system and the charging patterns, electric vehicle integration creates new quantities in the overall load profile that may increase the load peaks. The electric vehicle charging patterns are stochastic since they are affected by the travel behavior of the driver and the charging opportunities which implies that an electric vehicle introduction also will affect load variations. Increased load variation and load peaks may create a need for upgrades in the grid infrastructure to reduce losses, risks for overloads or damaging of components. However, with well-designed incentives for electric vehicle users and electric vehicle charging, the electric vehicles may be used as flexible loads that can help mitigate load variations and load peaks in the power system.

The aim with this doctoral thesis is to investigate and quantify the impact of electric vehicle charging on load profiles and load variations. Three key factors are identified when considering the impact of electric vehicle charging on load profiles and load variations. The key factors are: The charging moment, the charging need and the charging location. One of the conclusions in this thesis is that the level of details and the approach to model these key factors impact the estimations of the load profiles. The models that take into account a high level of mobility details will be able to create a realistic estimation of a future uncontrolled charging behavior, enabling for more accurate estimates of the impact on load profiles and the potential of individual charging strategies and external charging strategies. The thesis reviews and categorizes electric vehicle charging models in previous research, and furthermore, introduces new electric vehicle charging models to estimate the charging impact based on charging patterns induced by passenger car travel behavior. The models mainly consider EVC related to individual car travel behavior and induced charging needs for plug-in-hybrid electric vehicles. Moreover, the thesis comments on dynamic electric vehicle charging along electrified roads and also on individual charging strategies.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. viii, 88 p.
Series
TRITA-EE, ISSN 1653-5146 ; 2014:044
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-152237 (URN)978-91-7595-255-0 (ISBN)
Public defence
2014-10-13, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20140924

Available from: 2014-09-24 Created: 2014-09-24 Last updated: 2014-09-24Bibliographically approved

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Söder, Lennart

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