Cited by 46Electric Vehicles and InfrastructureSmart Grid Energy ManagementOptimal Power Flow Distribution

A framework for stochastic estimation of electric vehicle charging behavior for risk assessment of distribution networks

Habib, Salman, Khan, Muhammad Mansoor, Abbas, Farukh, Numan, Muhammad, Ali, Yaqoob, Tang, Houjun, Yan, Xuhui·2020·Frontiers in Energy

Integrity signals

Registry

Crossref · 10.1007/s11708-019-0648-5

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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Recomputing p-values needs the paper’s full text.

Claims the paper makes

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Cited by

Authors
Habib, S., Khan, M. M., Abbas, F., Numan, M., Ali, Y., Tang, H., & Yan, X.
Affiliations
  • University of Engineering and Technology Lahore (PK)
  • Shanghai Jiao Tong University (CN)
  • State Grid Corporation of China (China) (CN)
Corresponding author
Habib, Salman
Venue
Frontiers in Energy
Published
2019-11-30
Volume
14
Issue
2
Pages
298-317
ISSN
  • 2095-1698 (ISSN-L)
  • 2095-1701
OpenAlex
W2990306434
Cited by
46
References
1
Citations by year
2026: 9 · 2025: 10 · 2024: 8 · 2023: 6 · 2022: 8 · 2021: 5
FWCI
1.17
Type
journal article
Language
en
Open access
closed
Locations
Frontiers in Energy (publishedVersion)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
Keywords
EV charging behavior, residential distribution networks, voltage unbalance, EV penetration, power quality, transformer overload, feeder losses, electric vehicle charging demand, risk assessment

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