Optimal EV scheduling and voltage security via an online bi-layer steady-state assessment method considering uncertainties
Open accessAbstract
Steady-state voltage security region (SVSR) is an important criterion that can intuitively and effectively evaluate the power system's operation security and overall safety margin. However, there is no literature on its application to electric vehicle (EV) proliferation. Since EV introduces dynamism and uncertainties to the grid, most existing indices cannot assess the grid accurately. Given this, we propose a load margin index (LMI) based on SVSR considering uncertainties. This is used to assess the impact of EV proliferation via a bi-layer optimal EV scheduling model. The upper layer of the model solves a dispatching plan for EV aggregators (EVA) by maximizing the LMI and minimizing the deviation between the upper and lower layer power schedules. The lower layer models each EV's charging/discharging strategy by minimizing the EV's operating cost, the EV user's target residual energy, and the deviation between the lower and upper layer schedules. We also employ a real-time scheduling plan to further adjust the day-ahead scheduling due to forecast errors. A case study based on the IEEE-33 node distribution network verifies the practicability and effectiveness of the proposed method.
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Centralized solutions that require the DNO to collect information from all EVAs are only suitable for small and medium-sized resources.
“However, these methods are centralized solutions that require the DNO to collect in formation from all EVAs and are therefore only suitable for small and medium-sized resources.”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [14]
Studies in Refs [11 -17,19 -22] do not introduce a proper flexibility quantification method to effectively exploit the flexibility of EVs.
“Furthermore, the studies in Refs. [11 -17,19 -22] do not introduce a proper flexibility quantification method to effectively exploit the flexibility of EVs”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [14]
Most mentioned studies overlook the potential benefits of an integrated DER environment, such as DERMS, where EVs could operate in coordination with other DERs to enhance overall grid stability and flexibility.
“Second, most studies overlook the potential benefits of an integrated DER environment, such as DERMS, where EVs could operate in coordination with other DERs to enhance overall grid stability and flexibility.”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [14]
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- Authors
- Jin, Y., Amoasi Acquah, M., Seo, M., Ghorbanpour, S., Han, S., & Jyung, T.
- Affiliations
- Kyungpook National University (KR)
- Corresponding author
- Han, Sekyung
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2023-10
- Volume
- 347
- Pages
- 121356
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W4380995042
- Cited by
- 38
- References
- 62
- Citations by year
- 2026: 10 · 2025: 14 · 2024: 13 · 2023: 1
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Applied Energy (publishedVersion, cc-by-nc)
- Funders
- Korea Agency for Infrastructure Technology Advancement
- Ministry of Land, Infrastructure and Transport (RS-2020-KA-157909)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- electric vehicle scheduling, voltage security, electric vehicle aggregators, power system uncertainty, EV charging and discharging, real-time scheduling, forecast error, distribution networks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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