The DOI matches its Crossref record.
Optimal Offering Strategies for Generation Companies Operating in Electricity Spot Markets
Abstract
An unprecedented process of reforms has shaken the power industry during the last two decades. In order to sell the energy produced by their plants, many generation companies are now forced to prepare and submit daily offers to an electricity market under uncertainty about the offers submitted by their rivals. In this paper, we describe a methodology to prepare optimal offers for a generation company operating in a day-ahead market organized as a series of 24 hourly uniform-price multiunit double auctions. We explicitly consider the ability of the company to affect the price of electricity as well as the company's uncertainty about rivals' behavior.
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
Decision making under uncertainty in electricity markets
Barroso, L. A., & Conejo, A. J. (2006) · 2006 IEEE Power Engineering Society General Meeting · doi:10.1109/pes.2006.1709323 · Cited by 622
Offering Strategy Via Robust Optimization
Baringo, L., & Conejo, A. J. (2011) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2010.2092793 · Cited by 165
Metadata
- Authors
- Baillo, A., Ventosa, M., Rivier, M., & Ramos, A.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2004-05
- Volume
- 19
- Issue
- 2
- Pages
- 745-753
- ISSN
- 0885-8950 (ISSN-L)
- OpenAlex
- W2139303242
- Cited by
- 168
- References
- 0
- FWCI
- 7.85
- 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 Offering Strategies for Generation Companies Operating in Electricity Spot Markets. https://app.cochat.ai/papers/10.1109/tpwrs.2003.821429
- The paper
- Baillo, A., Ventosa, M., Rivier, M., & Ramos, A. (2004). Optimal Offering Strategies for Generation Companies Operating in Electricity Spot Markets. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2003.821429
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.