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The flexibility provided by High Voltage Direct Current (HVDC) systems can be further extended by Wide Area Monitoring, Protection, and Control (WAMAPC) systems. WAMPAC systems enable many HVDC applications and, on the other hand, inevitably introduce cybersecurity concerns that need to be addressed. In this work, a security domain layer and decision framework is reported to detect and mitigate the impact of false data injection (FDI) attacks targeting HVDC stations. Specifically, a rule-based cyber-attack detection method is introduced and implemented on Raspberry Pi and tested on the real-time HVDC simulation facility on the real-time digital simulator (RTDS) platform at ABB U.S. Corporate Research Center.

The wide area measurement, protection, and control (WAMPAC) system enables high voltage direct current (HVDC) systems to provide advanced grid applications in various areas such as transient stability improvement, wide area damping control, and maximum power transfer improvement. However, the WAMPAC system inevitably introduces an enlarged attack surface from the perspective of a would-be cyber attacker. In this paper, two cyber-attack detection methods are proposed to detect false data injection (FDI) attacks toward HVDC controllers through WAMPAC systems: 1) learning based method and 2) model based method. The performance of the two methods is evaluated on Kundur's two-area system.