The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system
Open accessAbstract
This paper presents the design and performance analysis of Differential Evolution (DE) algorithm based Proportional-Integral (PI) controller for Automatic Generation Control (AGC) of an interconnected power system. A two area non-reheat thermal system equipped with PI controllers which is widely used in literature is considered for the design and analysis purpose. The design problem is formulated as an optimization problem control and DE is employed to search for optimal controller parameters. Three different objective functions using Integral Time multiply Absolute Error (ITAE), damping ratio of dominant eigenvalues and settling time with appropriate weight coefficients are derived in order to increase the performance of the controller. The superiority of the proposed DE optimized PI controller has been shown by comparing the results with some recently published modern heuristic optimization techniques such as Bacteria Foraging Optimization Algorithm (BFOA) and Genetic Algorithm (GA) based PI controller for the same interconnected power system.
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
Storn, R., & Price, K. (1997) · Journal of Global Optimization · doi:10.1023/a:1008202821328 · Cited by 29,569
Ogata, K., & Brewer, J. W. (1971) · Journal of Dynamic Systems, Measurement, and Control · doi:10.1115/1.3426465 · Cited by 6,358
Price, K. V. (2004) · Cited by 3,344
Electric Energy Systems Theory: An Introduction
Elgerd, O. I., & Happ, H. H. (1972) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1972.4309116 · Cited by 1,045
尾形, 克. (1990) · Prentice Hall eBooks · Cited by 633
Ali, E. S., & Elazim, S. M. A. (2011) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2010.12.022 · Cited by 486
Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design
Panda, S., & Padhy, N. P. (2008) · Applied Soft Computing · doi:10.1016/j.asoc.2007.10.009 · Cited by 435
Self-citationNanda, J., Mishra, S., & Saikia, L. C. (2009) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2016588 · Cited by 411
Adaptive fuzzy gain scheduling for load frequency control
Talaq, J., & Al-Basri, F. (1999) · IEEE Transactions on Power Systems · doi:10.1109/59.744505 · Cited by 370
Load frequency control of a realistic power system with multi-source power generation
Parmar, K. P. S., Majhi, S., & Kothari, D. P. (2012) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2012.04.040 · Cited by 364
Cited by
Alhelou, H. H., Hamedani-Golshan, M.-E., Zamani, R., Heydarian-Forushani, E., & Siano, P. (2018) · Energies · doi:10.3390/en11102497 · Cited by 349
Sahu, B. K., Pati, S., Mohanty, P. K., & Panda, S. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2014.11.027 · Cited by 261
Self-citationAlhamrouni, I., Abdul Kahar, N. H., Salem, M., Swadi, M., Zahroui, Y., Kadhim, D. J., Mohamed, F. A., & Alhuyi Nazari, M. (2024) · Applied Sciences · doi:10.3390/app14146214 · Cited by 217
Metadata
- Authors
- Rout, U. K., Sahu, R. K., & Panda, S.
- Venue
- Ain Shams Engineering Journal
- Publisher
- Elsevier BV
- Published
- 2013-09
- Volume
- 4
- Issue
- 3
- Pages
- 409-421
- ISSN
- 2090-4479 (ISSN-L)
- OpenAlex
- W2001762124
- Cited by
- 314
- References
- 14
- FWCI
- 8.55
- Type
- journal article
- Language
- en
- Open access
- gold
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: Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. https://app.cochat.ai/papers/10.1016/j.asej.2012.10.010
- The paper
- Rout, U. K., Sahu, R. K., & Panda, S. (2013). Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Engineering Journal. https://doi.org/10.1016/j.asej.2012.10.010
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.
