Examining the potential impact of plug-in electric vehicles on residential sector power demand

Brandon J. Johnson; Michael R. Starke; Aleksandar D. Dimitrovski

doi:10.1109/PESGM.2015.7286044

Examining the potential impact of plug-in electric vehicles on residential sector power demand

Brandon J. Johnson, Michael R. Starke, Aleksandar D. Dimitrovski

Grid Systems Architecture

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

This paper presents a dynamic simulation tool for examining the future impact of plug-in electric vehicles (PEVs) on residential sector power demand. First, the modeling approach used during the development of this tool is described. Markov chain based occupant behavior models developed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with models of the most common residential loads to estimate residential demand on a one-minute time scale. Next, a detailed explanation of the methodology used to model PEV use and charging is given. Simulation results showing the differences in residential power demand, both with and without PEVs present in the system, are shown. Finally, future work will involve using these simulation results to conduct various probabilistic load flow studies.

Original language	English
Title of host publication	2015 IEEE Power and Energy Society General Meeting, PESGM 2015
Publisher	IEEE Computer Society
ISBN (Electronic)	9781467380409
DOIs	https://doi.org/10.1109/PESGM.2015.7286044
State	Published - Sep 30 2015
Event	IEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States Duration: Jul 26 2015 → Jul 30 2015

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2015-September
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	IEEE Power and Energy Society General Meeting, PESGM 2015
Country/Territory	United States
City	Denver
Period	07/26/15 → 07/30/15

Keywords

Markov chains
Occupant behavior modeling
Plug-in electric vehicle modeling
Residential power demand

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/PESGM.2015.7286044

Cite this

Johnson, B. J., Starke, M. R., & Dimitrovski, A. D. (2015). Examining the potential impact of plug-in electric vehicles on residential sector power demand. In 2015 IEEE Power and Energy Society General Meeting, PESGM 2015 Article 7286044 (IEEE Power and Energy Society General Meeting; Vol. 2015-September). IEEE Computer Society. https://doi.org/10.1109/PESGM.2015.7286044

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title = "Examining the potential impact of plug-in electric vehicles on residential sector power demand",

abstract = "This paper presents a dynamic simulation tool for examining the future impact of plug-in electric vehicles (PEVs) on residential sector power demand. First, the modeling approach used during the development of this tool is described. Markov chain based occupant behavior models developed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with models of the most common residential loads to estimate residential demand on a one-minute time scale. Next, a detailed explanation of the methodology used to model PEV use and charging is given. Simulation results showing the differences in residential power demand, both with and without PEVs present in the system, are shown. Finally, future work will involve using these simulation results to conduct various probabilistic load flow studies.",

keywords = "Markov chains, Occupant behavior modeling, Plug-in electric vehicle modeling, Residential power demand",

author = "Johnson, {Brandon J.} and Starke, {Michael R.} and Dimitrovski, {Aleksandar D.}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Power and Energy Society General Meeting, PESGM 2015 ; Conference date: 26-07-2015 Through 30-07-2015",

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Johnson, BJ, Starke, MR & Dimitrovski, AD 2015, Examining the potential impact of plug-in electric vehicles on residential sector power demand. in 2015 IEEE Power and Energy Society General Meeting, PESGM 2015., 7286044, IEEE Power and Energy Society General Meeting, vol. 2015-September, IEEE Computer Society, IEEE Power and Energy Society General Meeting, PESGM 2015, Denver, United States, 07/26/15. https://doi.org/10.1109/PESGM.2015.7286044

Examining the potential impact of plug-in electric vehicles on residential sector power demand. / Johnson, Brandon J.; Starke, Michael R.; Dimitrovski, Aleksandar D.
2015 IEEE Power and Energy Society General Meeting, PESGM 2015. IEEE Computer Society, 2015. 7286044 (IEEE Power and Energy Society General Meeting; Vol. 2015-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Examining the potential impact of plug-in electric vehicles on residential sector power demand

AU - Johnson, Brandon J.

AU - Starke, Michael R.

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N2 - This paper presents a dynamic simulation tool for examining the future impact of plug-in electric vehicles (PEVs) on residential sector power demand. First, the modeling approach used during the development of this tool is described. Markov chain based occupant behavior models developed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with models of the most common residential loads to estimate residential demand on a one-minute time scale. Next, a detailed explanation of the methodology used to model PEV use and charging is given. Simulation results showing the differences in residential power demand, both with and without PEVs present in the system, are shown. Finally, future work will involve using these simulation results to conduct various probabilistic load flow studies.

AB - This paper presents a dynamic simulation tool for examining the future impact of plug-in electric vehicles (PEVs) on residential sector power demand. First, the modeling approach used during the development of this tool is described. Markov chain based occupant behavior models developed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with models of the most common residential loads to estimate residential demand on a one-minute time scale. Next, a detailed explanation of the methodology used to model PEV use and charging is given. Simulation results showing the differences in residential power demand, both with and without PEVs present in the system, are shown. Finally, future work will involve using these simulation results to conduct various probabilistic load flow studies.

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KW - Occupant behavior modeling

KW - Plug-in electric vehicle modeling

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M3 - Conference contribution

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Examining the potential impact of plug-in electric vehicles on residential sector power demand

Abstract

Publication series

Conference

Keywords

UN SDGs

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