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A method for evaluating the impact of electric vehicle charging on transformer hotspot temperature
KTH, School of Electrical Engineering (EES), Electric Power Systems.
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0002-5138-0272
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0002-2964-7233
KTH, School of Electrical Engineering (EES), Electric Power Systems.
Show others and affiliations
2011 (English)In: 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), 2011Conference paper, Published paper (Refereed)
Abstract [en]

The expected increasing market share of electric vehicles is a response to the combination of new technological developments, governmental financial control, and an attitude shift of residents to a more environmentally friendly lifestyle. The expected capacity required for charging, imposes changes in the load to the already existing components in the electric power grid. In order to continue managing these existing assets efficiently during this load change, it is important to evaluate the impact imposed by the battery charging.

Place, publisher, year, edition, pages
2011.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-91293DOI: 10.1109/ISGTEurope.2011.6162755Scopus ID: 2-s2.0-84860751696OAI: oai:DiVA.org:kth-91293DiVA: diva2:509177
Conference
2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), 2011. Manchester, UK . Dec 5 – 7, 2011
Note
QC 20120329Available from: 2012-03-12 Created: 2012-03-12 Last updated: 2014-09-24Bibliographically approved
In thesis
1. Lifetime modeling and management of transformers
Open this publication in new window or tab >>Lifetime modeling and management of transformers
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This work have studied and developed lifetime estimation methods for the power transformer and how these could be used for asset management purposes. It is researchperformed in the intersection of the fields of reliability theory, statistical analysis, and stochastic process theory applied to lifetime estimations and management of transformers.

The chosen approaches are the following. The thesis assess the effect of thermal stresses on the lifetime of the transformer. The effect of hotspot temperature is assessed with a loss of life measure. Within this study, improvements to the thermal model have been made.

The thesis moves on to an alternative method for lifetime estimation in which diagnostic measurements are forecasted using a stochastic process and iterative realizations of this stochastic process is used to estimate a probability distribution for the transformer.

The thesis moves on to study the loss of life measure from a system perspective by calculating the loss of life estimate from the load profiles of cold load pickup, increased electric vehicle penetration, and normal operation. These are applied in such a way that they can be used for asset management purposes.

Then, the thesis uses estimates of failure times with the aim to reach a probabilistic, dynamic capacity rating selection method which use a failure rate which is conditioned on the time-dependent load level.

Abstract [sv]

Det här arbetet har studerat och utvecklat metoder för estimering av transformatorlivslängden och hur dessa skulle kunna användas för hantering av tillgångar1. Detta är forskning framförd inom skärningspunkten mellan fälten: tillförlitlighetsteori, statistiskanalys och statistisk process teori. Detta har sedan blivit applicerat på hantering av transformatorer som tillgång.

En beskrivning av de valda ansatserna följer. Den här avandlingen skattar effekten av termisk påfrestning på livslängden av en transformator. Effekten av hotspot temperaturenestimeras med ett mått som skattar livslängdsförlusten för given drift. Inom den här studien så har förbättringar påden termiska modellen gjorts.

Avhandlingen går vidare till att utveckla en alternativ metod för livslängds estimering som nyttjar diagnostiska mätningar genom att prognosticera dessa med hjälp av en stokastisk process och genom iterativa realisationer av dessa, estimera sannolikhetsfördelningen för transformatorns livslängd.

Avhandlingen går vidare till att positionera livslängsförlustsmåttet i ett system genom att beräkna livslängdsförlusten under de olika driftförhållandena: kallastpåslag, ökad penetration av elektriska fordon, och normal drift. Dessa implementeras så att de kan användas med syftet att hantera tillgångar.

Slutligen så går avhandlingen vidare till att estimera feltider med syftet att välja en probabilistisk, dynamisk kapacitet som använder en felintensitet som är betingad på en tidsberoende belastningsnivå.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. xiii, 60 p.
Series
Trita-EE, ISSN 1653-5146 ; 2013:037
Keyword
transformers, lifetime modeling, asset management, thermal modeling, lifetime estimation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-129971 (URN)978-91-7501-883-6 (ISBN)
Public defence
2013-10-21, F3, Lindstedtsvägen 26 (Entreplan), KTH, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20131007

Available from: 2013-10-07 Created: 2013-10-07 Last updated: 2013-10-07Bibliographically approved
2. 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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Rosenlind, JohannaSöder, Lennart

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