Component Damage Source Identification for Critical Infrastructure Systems

Cyber-Physical Systems (CPS) are becoming increasingly prevalent for both Critical Infrastructure and the Industry 4.0 initiative. Bad values within components of the software portion of CPS, or the computer systems, have the potential to cause major damage if left unchecked, and so detection and locating of where these occur is vital. We further define features of these computer systems and create a use-based system topology. We then introduce a function to monitor system integrity and the presence of bad values as well as an algorithm to locate them. We then show an improved version, taking advantage of several system properties to increase efficiency. We additionally delve into the use of digital twins for simulating potential bad values faster-than-real-time. Finally, we show evidence of our non-digital twin model’s effectiveness through simulation

Predictive Mitigation of Short Term Voltage Instability Using a Faster Than Real-Time Digital Replica

Predictive mitigation of undesired events has long been seen as a supportive complement to corrective mitigation that could relax the stringent requirements on the correctiveactions and increase reliability of the overall system. This article describes one such predictive measure, i.e. the use of faster than real-time simulation in detecting faults and predicting the dynamic behavior for the resilient operation of future smart grid systems. A predictive mitigation strategy is proposed for a fault induced dynamic voltage recovery (FIDVR) event. These events, although rare, are typically addressed with under voltage load shedding schemes (UVLS) which leave significant portion of loadunder-supplied. We show that, by using the digital faster than real-time replica, the minimal level of UVLS can be determined on-the fly as the event develops while ensuring only the minimal amount of load shed.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid

Predictive Mitigation of Short Term Voltage Instability Using a Faster Than Real-Time Digital Replica

Predictive mitigation of undesired events has long been seen as a supportive complement to corrective mitigation that could relax the stringent requirements on the correctiveactions and increase reliability of the overall system. This article describes one such predictive measure, i.e. the use of faster than real-time simulation in detecting faults and predicting the dynamic behavior for the resilient operation of future smart grid systems. A predictive mitigation strategy is proposed for a fault induced dynamic voltage recovery (FIDVR) event. These events, although rare, are typically addressed with under voltage load shedding schemes (UVLS) which leave significant portion of loadunder-supplied. We show that, by using the digital faster than real-time replica, the minimal level of UVLS can be determined on-the fly as the event develops while ensuring only the minimal amount of load shed