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A Prediction Algorithm to Enhance Grid Resilience Toward Cyber Attacks in WAMCS Applications

handle: 20.500.11937/63027
Monitoring and control of electrical power grids are highly reliant on the accuracy of the digital measurements. These digital measurements reflect the precision of the installed sensors, which are vulnerable to the injection of unknown parameters in the form of device malfunction and cyberattacks. This may question the operational security and reliability of many cyberphysical infrastructure such as smart grid. To resolve this issue, a multisensor temporal prediction based wide-area control scheme is proposed in this paper. The feasibility of the designed scheme is verified in an advanced synchrophasor measurements based wide-area monitoring and control system (WAMCS). This WAMCS adopts a flexible ac transmission system device (the primary controller) for controlling the smart grid's voltage profile. The algorithm is validated in a real-time environment with an innovative software-in-the-loop testing setup. The performance of the proposed technique in the presence of false-data-injection attacks shows promising results.
- Higher Colleges of Technology United Arab Emirates
- Higher Colleges of Technology United Arab Emirates
- Curtin University Australia
- Khalifa University of Science and Technology United Arab Emirates
- Khalifa University of Science and Technology United Arab Emirates
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).88 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
