The DOI matches its Crossref record.
Direct Electricity Trading in Smart Grid: A Coalitional Game Analysis
Abstract
Integration of distributed generation based on renewable energy sources into the power system has gained popularity in recent years. Many small-scale electricity suppliers (SESs) have recently entered the electricity market, which has been traditionally dominated by a few large-scale electricity suppliers. The emergence of SESs enables direct trading (DT) of electricity between SESs and end-users (EUs), without going through retailers, and promotes the possibility of improving the benefits to both parties. In this paper, the cooperation between SESs and EUs in DT is analyzed based on coalitional game theory. In particular, an electricity pricing scheme that achieves a fair division of revenue between SESs and EUs is analytically derived by using the asymptotic Shapley value. The asymptotic Shapley value is shown to be in the core of the coalitional game such that no group of SESs and EUs has an incentive to abandon the coalition, which implies the stable operation of DT for the proposed pricing scheme. Unlike the existing pricing schemes that typically require multiple stages of calculations and real time information about each participant, the electricity price for the proposed scheme can be determined instantaneously based on the number of participants in DT and statistical information about electricity supply and demand. Therefore, the proposed pricing scheme is suitable for practical implementation. Using computer simulations, the price of electricity for the proposed DT scheme is examined in various environments, and the numerical results validate the asymptotic analysis. Moreover, the revenues of the SESs and EUs are evaluated for various types of SESs and different numbers of participants in DT. The optimal ratio of different types of SESs is also investigated.
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.
Integrity signals
Registry
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.
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
Energy-Sharing Model With Price-Based Demand Response for Microgrids of Peer-to-Peer Prosumers
Liu, N., Yu, X., Wang, C., Li, C., Ma, L., & Lei, J. (2017) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2017.2649558 · Cited by 855
Multiclass Energy Management for Peer-to-Peer Energy Trading Driven by Prosumer Preferences
Morstyn, T., & McCulloch, M. D. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2018.2834472 · Cited by 533
Energy Sharing Management for Microgrids With PV Prosumers: A Stackelberg Game Approach
Liu, N., Yu, X., Wang, C., & Wang, J. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2654302 · Cited by 425
A cooperative game approach for coordinating multi-microgrid operation within distribution systems
Du, Y., Wang, Z., Liu, G., Chen, X., Yuan, H., Wei, Y., & Li, F. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.03.086 · Cited by 205
Metadata
- Authors
- Lee, W., Xiang, L., Schober, R., & Wong, V. W. S.
- Venue
- IEEE Journal on Selected Areas in Communications
- Published
- 2014-07
- Volume
- 32
- Issue
- 7
- Pages
- 1398-1411
- ISSN
- 0733-8716 (ISSN-L)
- OpenAlex
- W2042101093
- Cited by
- 199
- References
- 0
- FWCI
- 5.48
- 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: Direct Electricity Trading in Smart Grid: A Coalitional Game Analysis. https://app.cochat.ai/papers/10.1109/jsac.2014.2332112
- The paper
- Lee, W., Xiang, L., Schober, R., & Wong, V. W. S. (2014). Direct Electricity Trading in Smart Grid: A Coalitional Game Analysis. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/jsac.2014.2332112
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.