Cyber Anomaly-Aware Distributed Voltage Control With Active Power Curtailment and DERs

Partha S. Sarker, Md. Fazley Rafy,Anurag K. Srivastava, R. K. Singh

IEEE Transactions on Industry Applications(2024)

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摘要
Operations of power distribution systems with Distributed Energy Resources (DERs) can be managed in scalable manner with advanced distributed control algorithms. Distributed algorithms utilizing digital controller also bring cyber vulnerabilities. In this work, a converter-inverter topology that can utilize a communication network and a distributed feedback-based Volt-Watt controller has been developed. Circuit topology of the converter-inverter and DER is verified with both PSIM simulation software and a laboratory prototype shown. The paper presents multiple simulated cyber attack scenarios exploiting vulnerabilities to test the capability of the developed distributed control approach. Finally, a multivariate LSTM-autoencoder-based anomaly detection-mitigation application has been developed to minimize the impact of cyber attacks on distributed controller operations. To validate the developed algorithms, a Cyber-Physical System (CPS) test-bed has been developed, which uses OpenDSS for power system simulation, Mininet for communication network emulation, and integrates applications using Python. The test-bed has been designed to simulate comprehensive distributed operations with various use cases, including attack surfaces, distributed control, and detection-mitigation applications. Our developed approaches have been validated using a modified 123-bus unbalanced distribution network with DERs. The results clearly show that our proposed converter-inverter topology for DER integration, voltage control application, and anomaly detection-mitigation application can significantly improve the efficiency, performance, and security of distribution systems that rely on DERs.
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关键词
Anomaly detection-mitigation,converter-inverter topology,co-simulation,cyber-attacks,cyber-power systems,Distributed Energy Resources (DERs),distributed optimization,multivariate LSTM autoencoder,test-bed,mininet
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