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Risk assessment framework for power control systems with PMU-based intrusion response system
Cyber threats are serious concerns for power systems. For example, hackers may attack power control systems via interconnected enterprise networks. This paper proposes a risk assessment framework to enhance the resilience of power systems against cyber attacks. The duality element relative fuzzy evaluation method 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 the phasor measurement unit data. Power system stability is predicted through the 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.
Risk assessment framework for power control systems with PMU-based intrusion response system
Cyber threats are serious concerns for power systems. For example, hackers may attack power control systems via interconnected enterprise networks. This paper proposes a risk assessment framework to enhance the resilience of power systems against cyber attacks. The duality element relative fuzzy evaluation method 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 the phasor measurement unit data. Power system stability is predicted through the 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.
Risk assessment framework for power control systems with PMU-based intrusion response system
Jie Yan (author) / Manimaran Govindarasu (author) / Chen-Ching Liu (author) / Ming Ni (author) / Umesh Vaidya (author)
2015
Article (Journal)
Electronic Resource
Unknown
Cyber security , Supervisory control and data acquisition (SCADA) , Risk assessment , Intrusion response system (IRS) , Conditional Lyapunov exponents (CLEs) , Phasor measurement unit (PMU) , Production of electric energy or power. Powerplants. Central stations , TK1001-1841 , Renewable energy sources , TJ807-830
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