Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 533

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

Multiclass Energy Management for Peer-to-Peer Energy Trading Driven by Prosumer Preferences

Morstyn, Thomas, McCulloch, Malcolm D.·2019·IEEE Transactions on Power Systems

Abstract

This paper proposes a peer-to-peer energy market platform based on the new concept of multiclass energy management, to coordinate trading between prosumers with heterogeneous (i.e., beyond purely financial) preferences. Power networks are undergoing a fundamental transition, with traditionally passive distribution network consumers becoming “prosumers”; proactive consumers that actively manage their production and consumption of energy. The paper introduces the new concept of energy classes, allowing energy to be treated as a heterogeneous product, based on attributes of its source, which are perceived by prosumers to have value. Examples include generation technology, location in the network and owner's reputation. The proposed peer-to-peer energy market platform coordinates trading between subscribed prosumers and the wholesale electricity market, to minimize costs associated with losses and battery depreciation, while providing added value by accounting for the prosumers' individual preferences for the source/destination of the energy they consume/produce. The decomposable structure of the multiclass energy management problem is exploited to devise a distributed price-directed optimization mechanism, providing scalability and prosumer data privacy. Receding horizon model predictive control allows the prosumers to adjust their planned power flows based on the wholesale energy price, and up-to-date renewable generation and load predictions.

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/tpwrs.2018.2834472

Cites

37 of 37 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 37 references

Cited by

See all 533

Metadata

Authors
Morstyn, T., & McCulloch, M. D.
Venue
IEEE Transactions on Power Systems
Published
2019-09
Volume
34
Issue
5
Pages
4005-4014
ISSN
  • 0885-8950 (ISSN-L)
  • 1558-0679
OpenAlex
W2801389981
Cited by
533
References
37
FWCI
19.10
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: Multiclass Energy Management for Peer-to-Peer Energy Trading Driven by Prosumer Preferences. https://app.cochat.ai/papers/10.1109/tpwrs.2018.2834472
The paper
Morstyn, T., & McCulloch, M. D. (2019). Multiclass Energy Management for Peer-to-Peer Energy Trading Driven by Prosumer Preferences. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2018.2834472

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.