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Application of Linear Matrix Inequalities for Load Frequency Control With Communication Delays
Abstract
Load frequency control has been used for decades in power systems. Traditionally, this has been a centralized control by area with communication over a dedicated and closed network. New regulatory guidelines allow for competitive markets to supply this load frequency control. In order to allow an effective market operation, an open communication infrastructure is needed to support an increasing complex system of controls. While such a system has great advantage in terms of cost and reliability, the possibility of communication signal delays and other problems must be carefully analyzed. This paper presents a load frequency control method based on linear matrix inequalities. The primary aim is to find a robust controller that can ensure good performance despite indeterminate delays and other problems in the communication network.
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Cited by
Networked control system: a brief survey
Yang, T. C. (2006) · IEE Proceedings - Control Theory and Applications · doi:10.1049/ip-cta:20050178 · Cited by 698
Pandey, S. K., Mohanty, S. R., & Kishor, N. (2013) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2013.04.029 · Cited by 561
Alhelou, H. H., Hamedani-Golshan, M.-E., Zamani, R., Heydarian-Forushani, E., & Siano, P. (2018) · Energies · doi:10.3390/en11102497 · Cited by 349
Metadata
- Authors
- Yu, X., & Tomsovic, K.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2004-08
- Volume
- 19
- Issue
- 3
- Pages
- 1508-1515
- ISSN
- 0885-8950 (ISSN-L)
- OpenAlex
- W2112150746
- Cited by
- 333
- References
- 0
- FWCI
- 8.83
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yu, X., & Tomsovic, K. (2004). Application of Linear Matrix Inequalities for Load Frequency Control With Communication Delays. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2004.831670
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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.
