Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 707

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Optimal Scheduling of Vehicle-to-Grid Energy and Ancillary Services

Sortomme, Eric, El-Sharkawi, Mohamed A.·2012·IEEE Transactions on Smart Grid

Abstract

Vehicle-to-grid (V2G), the provision of energy and ancillary services from an electric vehicle (EV) to the grid, has the potential to offer financial benefits to EV owners and system benefits to utilities. In this work a V2G algorithm is developed to optimize energy and ancillary services scheduling. The ancillary services considered are load regulation and spinning reserves. The algorithm is developed to be used by an aggregator, which may be a utility or a third party. This algorithm maximizes profits to the aggregator while providing additional system flexibility and peak load shaving to the utility and low costs of EV charging to the customer. The formulation also takes into account unplanned EV departures during the contract periods and compensates accordingly. Simulations using a hypothetical group of 10 000 commuter EVs in the ERCOT system using different battery replacement costs demonstrate these significant benefits.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tsg.2011.2164099

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 707

Metadata

Authors
Sortomme, E., & El-Sharkawi, M. A.
Venue
IEEE Transactions on Smart Grid
Published
2012-03
Volume
3
Issue
1
Pages
351-359
ISSN
  • 1949-3053 (ISSN-L)
  • 1949-3061
OpenAlex
W2040611596
Cited by
707
References
2
FWCI
24.96
Type
journal article
Language
en
Open access
closed

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 ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Optimal Scheduling of Vehicle-to-Grid Energy and Ancillary Services. https://app.cochat.ai/papers/10.1109/tsg.2011.2164099
The paper
Sortomme, E., & El-Sharkawi, M. A. (2012). Optimal Scheduling of Vehicle-to-Grid Energy and Ancillary Services. IEEE Transactions on Smart Grid. https://doi.org/10.1109/tsg.2011.2164099

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.