The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Unit Commitment by an Enhanced Simulated Annealing Algorithm
Abstract
A new simulated annealing (SA) algorithm combined with a dynamic economic dispatch method has been developed for solving the short-term unit commitment (UC) problem. SA is used for the scheduling of the generating units, while a dynamic economic dispatch method is applied incorporating the ramp rate constraints in the solution of the UC problem. New rules concerning the tuning of the control parameters of the SA algorithm are proposed. Three alternative mechanisms for generating feasible trial solutions in the neighborhood of the current one, contributing to the reduction of the required CPU time, are also presented. The ramp rates are taken into account by performing either a backward or a forward sequence of conventional economic dispatches with modified limits on the generating units. The proposed algorithm is considerably fast and provides feasible near-optimal solutions. Numerical simulations have proved the effectiveness of the proposed algorithm in solving large UC problems within a reasonable execution time.
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
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Simulated annealing: theory and applications.
(1988) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(88)90023-7 · Cited by 2,966
Simulated Annealing: Theory and Applications
van Laarhoven, P. J. M., & Aarts, E. H. L. (1987) · Springer eBooks · doi:10.1007/978-94-015-7744-1 · Cited by 2,385
A genetic algorithm solution to the unit commitment problem
Kazarlis, S., Bakirtzis, A. G., & Petridis, V. (1996) · IEEE Transactions on Power Systems · doi:10.1109/59.485989 · Cited by 1,147
Genetic algorithm solution to unit commitment problem
Madraswala, H. S., & Deshpande, A. S. (2016) · 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) · doi:10.1109/icpeices.2016.7853075 · Cited by 963
Effects of ramp-rate limits on unit commitment and economic dispatch
Wang, C., & Shahidehpour, M. (1993) · IEEE Transactions on Power Systems · doi:10.1109/59.260859 · Cited by 387
Unit commitment by simulated annealing
Zhuang, F., & Galiana, F. D. (1990) · IEEE Transactions on Power Systems · doi:10.1109/59.49122 · Cited by 383
A simulated annealing algorithm for unit commitment
Mantawy, A. H., Abdel-Magid, Y. L., & Selim, S. Z. (1998) · IEEE Transactions on Power Systems · doi:10.1109/59.651636 · Cited by 295
Integrating genetic algorithms, tabu search, and simulated annealing for the unit commitment problem
Mantawy, A. H., Abdel-Magid, Y. L., & Selim, S. Z. (1999) · IEEE Transactions on Power Systems · doi:10.1109/59.780892 · Cited by 265
Metadata
- Authors
- Simopoulos, D. N., Kavatza, S. D., & Vournas, C. D.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2006-02
- Volume
- 21
- Issue
- 1
- Pages
- 68-76
- ISSN
- 0885-8950 (ISSN-L)
- OpenAlex
- W2162030618
- Cited by
- 331
- References
- 12
- FWCI
- 12.15
- 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: Unit Commitment by an Enhanced Simulated Annealing Algorithm. https://app.cochat.ai/papers/10.1109/tpwrs.2005.860922
- The paper
- Simopoulos, D. N., Kavatza, S. D., & Vournas, C. D. (2006). Unit Commitment by an Enhanced Simulated Annealing Algorithm. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2005.860922
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.
