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Semi AI-based protection element for MMC-MTDC using local-measurements
Data Access Statement: Data supporting this study cannot be made available due to the research data are confidential, because of the arrangement the research groups have made with the commercial partner supporting the research.Copyright © 2022 The Authors. The multi-terminal HVDC system based on the modular multilevel converter (MMC-MTDC) is a promising technique for flexible power transmissions to multiple regions. As such a system is quite sensitive to DC faults, there is an acute need to propose a protection element that can trip the local DC circuit breaker (CB) within several milliseconds once there is an internal DC line fault. However, the existing main protection scheme faces a dilemma balancing selectivity and sensitivity. To solve this problem, a novel semi artificial-intelligence (AI) based protection element is proposed, including a start-up criterion and a fault-identification criterion. The start up criterion is based on the propagation characteristics of the initial fault-induced surge. To enhance the real time performance of the protection element, it will not trip the fault-identification process unless the fault is identified as a forward one. The fault-identification criterion is based on artificial intelligence (AI), and further determines whether the forward fault is internal, which only works if the start-up criterion trips. Simulation results indicate that the proposed protection element has satisfactory speed, sensitivity, and selectivity against internal DC faults and is quite secure under external fault conditions. The impact of disturbances, such as the white noise, abnormal samplings, etc., on the security of the proposed protection element is also discussed.National Natural Science Foundation of China under Grant No. 51907069; Natural Science Foundation of Guangdong Province under Grant No. 2022A1515011079 and 2020A1515010766
Cyber Physical System Security — DoS Attacks on Synchrophasor Networks in the Smart Grid
With the rapid increase of network-enabled sensors, switches, and relays, cyber-physical system security in the smart grid has become important. The smart grid operation demands reliable communication. Existing encryption technologies ensures the authenticity of delivered messages. However, commonly applied technologies are not able to prevent the delay or drop of smart grid communication messages. In this dissertation, the author focuses on the network security vulnerabilities in synchrophasor network and their mitigation methods. Side-channel vulnerabilities of the synchrophasor network are identified. Synchrophasor network is one of the most important technologies in the smart grid transmission system. Experiments presented in this dissertation shows that a DoS attack that exploits the side-channel vulnerability against the synchrophasor network can lead to the power system in stability. Side-channel analysis extracts information by observing implementation artifacts without knowing the actual meaning of the information. Synchrophasor network consist of Phasor Measurement Units (PMUs) use synchrophasor protocol to transmit measurement data. Two side-channels are discovered in the synchrophasor protocol. Side-channel analysis based Denial of Service (DoS) attacks differentiate the source of multiple PMU data streams within an encrypted tunnel and only drop selected PMU data streams. Simulations on a power system shows that, without any countermeasure, a power system can be subverted after an attack. Then, mitigation methods from both the network and power grid perspectives are carried out. From the perspective of network security study, side-channel analysis, and protocol transformation has the potential to assist the PMU communication to evade attacks lead with protocol identifications. From the perspective of power grid control study, to mitigate PMU DoS attacks, Cellular Computational Network (CCN) prediction of PMU data is studied and used to implement a Virtual Synchrophasor Network (VSN), which learns and mimics the behaviors of an objective power grid. The data from VSN is used by the Automatic Generation Controllers (AGCs) when the PMU packets are disrupted by DoS attacks. Real-time experimental results show the CCN based VSN effectively inferred the missing data and mitigated the negative impacts of DoS attacks. In this study, industry-standard hardware PMUs and Real-Time Digital Power System Simulator (RTDS) are used to build experimental environments that are as close to actual production as possible for this research. The above-mentioned attack and mitigation methods are also tested on the Internet. Man-In-The-Middle (MITM) attack of PMU traffic is performed with Border Gateway Protocol (BGP) hijacking. A side-channel analysis based MITM attack detection method is also investigated. A game theory analysis is performed to give a broade