Probabilistic modeling of electric vehicle charging load for probabilistic load flow

Seongbae Kong; Hyung Chul Cho; Jong Uk Lee; Sung Kwan Joo

doi:10.1109/VPPC.2012.6422755

Probabilistic modeling of electric vehicle charging load for probabilistic load flow

Seongbae Kong, Hyung Chul Cho, Jong Uk Lee, Sung Kwan Joo

School of Electrical Engineering

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

7 Citations (Scopus)

Abstract

With an increasing concern about environmental pollution and rising price of fossil fuels, electric vehicles (EVs) are becoming an important alternative energy source in a transportation sector. A rapid deployment of EVs may have significant impacts on demand for electricity in a power system. Also, a large-scale deployment of EVs can introduce greater uncertainty in EV charging patterns and loads. This paper presents a Stratified Latin Hypercube Sampling (SLHS)-based probabilistic load flow (PLF) method incorporating electric vehicle charging load. In this paper, probabilistic EV charging load is modeled by using the EV penetration level, hourly traffic patterns, and EV charging scenarios. The Monte Carlo Simulation (MCS)-based PLF requires a significant amount of computation time to obtain accurate results. In this paper, SLHS technique is also applied to reduce the computation time of the PLF. A numerical example is presented to show the performance of the proposed method.

Original language	English
Title of host publication	2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012
Pages	1010-1013
Number of pages	4
DOIs	https://doi.org/10.1109/VPPC.2012.6422755
Publication status	Published - 2012
Event	2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012 - Seoul, Korea, Republic of Duration: 2012 Oct 9 → 2012 Oct 12

Publication series

Name	2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012

Other

Other	2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012
Country	Korea, Republic of
City	Seoul
Period	12/10/9 → 12/10/12

ASJC Scopus subject areas

Automotive Engineering
Mechanical Engineering

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

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10.1109/VPPC.2012.6422755

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Probabilistic modeling of electric vehicle charging load for probabilistic load flow. / Kong, Seongbae; Cho, Hyung Chul; Lee, Jong Uk; Joo, Sung Kwan.

2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012. 2012. p. 1010-1013 6422755 (2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012).

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

Kong, S, Cho, HC, Lee, JU & Joo, SK 2012, Probabilistic modeling of electric vehicle charging load for probabilistic load flow. in 2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012., 6422755, 2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012, pp. 1010-1013, 2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012, Seoul, Korea, Republic of, 12/10/9. https://doi.org/10.1109/VPPC.2012.6422755

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abstract = "With an increasing concern about environmental pollution and rising price of fossil fuels, electric vehicles (EVs) are becoming an important alternative energy source in a transportation sector. A rapid deployment of EVs may have significant impacts on demand for electricity in a power system. Also, a large-scale deployment of EVs can introduce greater uncertainty in EV charging patterns and loads. This paper presents a Stratified Latin Hypercube Sampling (SLHS)-based probabilistic load flow (PLF) method incorporating electric vehicle charging load. In this paper, probabilistic EV charging load is modeled by using the EV penetration level, hourly traffic patterns, and EV charging scenarios. The Monte Carlo Simulation (MCS)-based PLF requires a significant amount of computation time to obtain accurate results. In this paper, SLHS technique is also applied to reduce the computation time of the PLF. A numerical example is presented to show the performance of the proposed method.",

author = "Seongbae Kong and Cho, {Hyung Chul} and Lee, {Jong Uk} and Joo, {Sung Kwan}",

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Probabilistic modeling of electric vehicle charging load for probabilistic load flow

Abstract

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ASJC Scopus subject areas

UN SDGs

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