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Power-system state-estimation security: Attacks and protection schemes
KTH, School of Electrical Engineering (EES), Communication Networks.ORCID iD: 0000-0002-4876-0223
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0003-1835-2963
2010 (English)In: Smart Grid Communications and Networking, Cambridge University Press, 2010, 388-412 p.Chapter in book (Other academic)
Abstract [en]

Introduction Supervisory control and data acquisition (SCADA) systems are widely used to monitor and control large-scale transmission power grids. Monitoring traditionally involves the measurement of voltage magnitudes and power flows; these data are collected by meters located in substations. In order to deliver the measured data from the substations to the control centre, the measurement data measured by meters in the same substation are multiplexed by a remote terminal unit (RTU) [1, 2]. Because electric power transmission systems extend over large geographical areas, typically entire countries, wide-area networks (WANs) are used to deliver the multiplexed measurement data from the substations to the control centre. For large-scale transmission grids it is often not feasible to measure all power flows and voltages of interest. Furthermore, the measurements are often noisy. Therefore the measurement data are usually fed into a model-based state estimator (SE) at the control centre, which is used to estimate the complete physical state (complex bus voltages) of the power grid. The SE is used to identify faulty equipment and corrupted measurement data through the so-called bad-data detection (BDD) system. Apart from BDD, the state estimate is used by the human operators and by the energy-management systems (EMS) found in modern SCADA systems, such as optimal power flow analysis, and contingency analysis (CA), see for example [1]. Future power grids will be even more dependent on accurate state estimators to fulfil their task of optimally and dynamically routing power flows, because clean renewable power generation tends to be less predictable than nonrenewable power generation.

Place, publisher, year, edition, pages
Cambridge University Press, 2010. 388-412 p.
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-167665DOI: 10.1017/CBO9781139013468.018ScopusID: 2-s2.0-84924663915ISBN: 9781139013468ISBN: 9781107014138OAI: diva2:816355

QC 20150603

Available from: 2015-06-03 Created: 2015-05-22 Last updated: 2015-06-03Bibliographically approved

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Dán, GyörgySou, Kincheong C.Sandberg, Henrik
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