A new emergency control method and a preventive mechanism against cascaded events to avoid large-scale blackouts

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Yan, Jie
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Chen-ching Liu
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Electrical and Computer Engineering

Cascaded events may cause a major blackout which will lead to a massive economic loss and even fatalities. Significant research efforts have been made to address the issue systematically: preventive mechanisms are designed to mitigate the impact of initiating events on power systems; emergency control methods are proposed to prevent power systems from entering an unstable state; restorative control methods are developed to stop the propagation of power system instability and to prevent widespread blackouts.

This work contributes to the development of new emergency control methods and preventive mechanisms.

First, a new emergency control scheme is proposed for preventing power systems from a loss of synchronism. Traditional out-of-step relays may fail to predict losses of synchronism as the dynamics of power systems become more and more complex. In recent years, the installation of the Phasor Measurement Units (PMUs) on power grids has increased significantly and, therefore, a large amount of real-time data is available for on-line monitoring of power system dynamics. This research proposes a PMU-based application for on-line monitoring of rotor angle stability. The Lyapunov Exponents are used to predict a loss of synchronism within large power systems. The relationship between rotor angle stability and the Maximal Lyapunov Exponent (MLE) is established. A computational algorithm is developed for the calculation of MLE in an operational environment. The effectiveness of the monitoring scheme is illustrated with a 3-machine system and a 200-bus system model.

Then, a preventive mechanism against cyber attacks is developed. Cyber threats are serious concerns for power systems. For example, hackers may attack power control systems via the interconnected enterprise networks. This research proposes a risk assessment framework to enhance the resilience of power systems against cyber attacks. The Duality Element Relative Fuzzy Evaluation Method (DERFEM) is employed to evaluate identified security vulnerabilities within cyber systems of power systems quantitatively; The Attack Graph is used to identify possible intrusion scenarios that exploit multiple vulnerabilities; an Intrusion Response system (IRS) is developed to monitor the impact of intrusion scenarios on power system dynamics in real time. IRS calculates the Conditional Lyapunov Exponents (CLEs) on line based on PMU data. Power system stability is predicted through values of CLEs. Control actions based on CLEs will be suggested if power system instability is likely to happen. A generic wind farm control system is used for case study. The effectiveness of IRS is illustrated with the IEEE 39 bus system model.

Sat Jan 01 00:00:00 UTC 2011