Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 161

The DOI matches its Crossref record.

Unbalanced Three-Phase Optimal Power Flow for Smart Grids

Bruno, S., Lamonaca, S., Rotondo, G., Stecchi, U., La Scala, M.·2011·IEEE Transactions on Industrial Electronics

Abstract

Advanced distribution management system (DMS), an evolution of supervisory control and data acquisition obtained by extending its working principles from transmission to distribution, is the brain of a smart grid. Advanced DMS assesses smart functions in the distribution system and is also responsible for assessing control functions such as reactive dispatch, voltage regulation, contingency analysis, capability maximization, or line switching. Optimal power flow (OPF)-based tools can be suitably adapted to the requirements of smart distribution network and be employed in an advanced DMS framework. In this paper, the authors present a methodology for unbalanced three-phase OPF (TOPF) for DMS in a smart grid. In the formulation of the TOPF, control variables of the optimization problem are actual active load demand and reactive power outputs of microgenerators. The TOPF is based on a quasi-Newton method and makes use of an open-source three-phase unbalanced distribution load flow. Test results are presented on the IEEE 123-bus Radial Distribution Feeder test case.

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/tie.2011.2106099

Cites

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

Cited by

See all 161

Metadata

Authors
Bruno, S., Lamonaca, S., Rotondo, G., Stecchi, U., & La Scala, M.
Venue
IEEE Transactions on Industrial Electronics
Published
2011-10
Volume
58
Issue
10
Pages
4504-4513
ISSN
  • 0278-0046 (ISSN-L)
  • 1557-9948
OpenAlex
W1963539491
Cited by
161
References
0
FWCI
9.36
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: Unbalanced Three-Phase Optimal Power Flow for Smart Grids. https://app.cochat.ai/papers/10.1109/tie.2011.2106099
The paper
Bruno, S., Lamonaca, S., Rotondo, G., Stecchi, U., & La Scala, M. (2011). Unbalanced Three-Phase Optimal Power Flow for Smart Grids. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2011.2106099

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.