The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
A novel decentralized platform for peer-to-peer energy trading market with blockchain technology
Open accessAbstract
Peer-to-Peer (P2P) energy trading, which allows energy consumers/producers to directly trade with each other, is one of the new paradigms driven by the decarbonization, decentralization, and digitalization of the energy supply chain. Additionally, the rise of blockchain technology suggests unprecedented socio-economic benefits for energy systems, especially when coupled with P2P energy trading. Despite such future prospects in energy systems, three key challenges might hinder the full integration of P2P energy trading and blockchain. First, it is quite complicated to design a decentralized P2P market that keeps a fair balance between economic efficiency and information privacy. Secondly, with the proliferation of storage devices, new P2P market designs are needed to account for their inter-temporal dependencies. Thirdly, a practical implementation of blockchain technology for P2P trading is required, which can facilitate efficient trading in a secured and fraud-resilient way, while eliminating any intermediaries’ costs. In this paper, we develop a new decentralized P2P energy trading platform to address all the aforementioned challenges. Our platform consists of two key layers: market and blockchain. The market layer features a parallel and short-term pool-structured auction and is cleared using a novel decentralized Ant-Colony Optimization method. This market arrangement guarantees a near-optimally efficient market solution, preserves players’ privacy, and allows inter-temporal market products trading. The blockchain layer offers a high level of automation, security, and fast real-time settlements through smart contract implementation. Finally, using real-world data, we simulate the functionality of the platform regarding energy trading, market clearing, smart contract operations, and blockchain-based settlements.
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
Cites
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Bitcoin: A Peer-to-Peer Electronic Cash System
Wright, C. S. (2008) · SSRN Electronic Journal · doi:10.2139/ssrn.3440802 · Cited by 13,922
Boyd, S. (2010) · now publishers, Inc. eBooks · doi:10.1561/9781601984616 · Cited by 12,677
(2013) · Cited by 5,372
Hoos (2000) · doi:10.1016/s0167-739x(00)00043-1 · Cited by 2,737
Blockchain technology in the energy sector: a systematic review of challenges and opportunities
Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D., McCallum, P., & Peacock, A. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2018.10.014 · Cited by 2,426
Making Smart Contracts Smarter
Luu, L., Chu, D.-H., Olickel, H., Saxena, P., & Hobor, A. (2016) · Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/2976749.2978309 · Cited by 2,249
Ant colony optimization: a new meta-heuristic
Dorigo, M., & Di Caro, G. (2003) · Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406) · doi:10.1109/cec.1999.782657 · Cited by 2,137
Designing microgrid energy markets
Mengelkamp, E., Gärttner, J., Rock, K., Kessler, S., Orsini, L., & Weinhardt, C. (2018) · Applied Energy · doi:10.1016/j.apenergy.2017.06.054 · Cited by 1,578
Stoft, S. (2002) · Institute of Electrical and Electronics Engineers eBooks · doi:10.1109/9780470545584 · Cited by 1,160
Cited by
Exploratory literature review of blockchain in the construction industry
Scott, D. J., Broyd, T., & Ma, L. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103914 · Cited by 159
Metadata
- Authors
- Esmat, A., de Vos, M., Ghiassi-Farrokhfal, Y., Palensky, P., & Epema, D.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 282
- Pages
- 116123
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W3102744027
- Cited by
- 420
- References
- 59
- FWCI
- 51.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: A novel decentralized platform for peer-to-peer energy trading market with blockchain technology. https://app.cochat.ai/papers/10.1016/j.apenergy.2020.116123
- The paper
- Esmat, A., de Vos, M., Ghiassi-Farrokhfal, Y., Palensky, P., & Epema, D. (2021). A novel decentralized platform for peer-to-peer energy trading market with blockchain technology. Applied Energy. https://doi.org/10.1016/j.apenergy.2020.116123
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.