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State estimation for electric power distribution systems in quasi real-time conditions
Abstract
This paper proposes a new method for the state estimation of electric power distribution system conditions oriented towards working with minimum number of remote measurements available in the network. This approach will require information concerning the network reconfiguration, remote measurements of voltages, real and reactive power as well as feeder currents in distribution substations. All kinds of statistical information pertaining to distribution transformer loads are used together with real-time remote measurements. In the proposed method, the existing scheme configuration is examined by a configuration pre-screening process based on the addressed references in an oriented graph. The permissible intervals for remote measurement errors and the reliability of statistical information are discussed. A practical example is presented and the exploitation of results has proved its accuracy and efficiency.>
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Citations
Cited by
State estimation for real-time monitoring of distribution systems
Baran, M. E., & Kelley, A. W. (1994) · IEEE Transactions on Power Systems · doi:10.1109/59.336098 · Cited by 474
Bayesian State Estimation for Unobservable Distribution Systems Via Deep Learning
Mestav, K. R., Luengo-Rozas, J., & Tong, L. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2019.2919157 · Cited by 216
Metadata
- Authors
- Roytelman, I., & Shahidehpour, S. M.
- Venue
- IEEE Transactions on Power Delivery
- Published
- 1993
- Volume
- 8
- Issue
- 4
- Pages
- 2009-2015
- ISSN
- 0885-8977 (ISSN-L)
- OpenAlex
- W2168701939
- Cited by
- 230
- References
- 0
- FWCI
- 5.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: State estimation for electric power distribution systems in quasi real-time conditions. https://app.cochat.ai/papers/10.1109/61.248315
- The paper
- Roytelman, I., & Shahidehpour, S. M. (1993). State estimation for electric power distribution systems in quasi real-time conditions. IEEE Transactions on Power Delivery. https://doi.org/10.1109/61.248315
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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.
