Cyber-physical systems have behaviour that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber-physical systems requires improved understanding of the combined cyber-physical system behaviour and methods for holistic analysis. Therefore, the authors propose leveraging clustering techniques on cyber-physical data from smart grid systems to analyse differences and similarities in behaviour during cyber-, physical-, and cyber-physical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber-physical systems. Through this analysis, deeper insights can be shared with decision-makers on what cyber and physical components are strongly or weakly linked, what cyber-physical pathways are most traversed, and the criticality of certain cyber-physical nodes or edges. This paper presents several types of clustering methods for cyber-physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber-physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber-physical graph interdependency analysis.
As the electric grid becomes increasingly cyber-physical, it is important to characterize its inherent cyber-physical interdepedencies and explore how that characterization can be leveraged to improve grid operation. It is crucial to investigate what data features are transferred at the system boundaries, how disturbances cascade between the systems, and how planning and/or mitigation measures can leverage that information to increase grid resilience. In this paper, we explore several numerical analysis and graph decomposition techniques that may be suitable for modeling these cyber-physical system interdependencies and for understanding their significance. An augmented WSCC 9-bus cyber-physical system model is used as a small use-case to assess these techniques and their ability in characterizing different events within the cyber-physical system. These initial results are then analyzed to formulate a high-level approach for characterizing cyber-physical interdependencies.
The harmonized automatic relay mitigation of nefarious intentional events (HARMONIE) special protection scheme (SPS) was developed to provide adaptive, cyber-physical response to unpredictable disturbances in the electric grid. The HARMONIE-SPS methodology includes a machine learning classification framework that analyzes real time cyber-physical data and determines if the system is in normal conditions, cyber disturbance, physical disturbance, or cyber-physical disturbance. This classification then informs response, if needed and/or suitable, and included cyber-physical corrective actions. Beyond standard power system mitigations, a few novel approaches were developed that included a consensus algorithm-based relay voting scheme, an automated power system triggering condition and corrective action pairing algorithm, and a cyber traffic routing optimization algorithm. Both the classification and response techniques were tested within a newly integrated emulation environment composed of a real-time digital simulator (RTDS) and SCEPTRE™. This report details the HARMONIE-SPS methodology, highlighting both the classification and response techniques, and the subsequent testing results from the emulation environment.
Unpredictable disturbances with dynamic trajectories such as extreme weather events and cyber attacks require adaptive, cyber-physical special protection schemes to mitigate cascading impact in the electric grid. A harmonized automatic relay mitigation of nefarious intentional events (HARMONIE) special protection scheme (SPS) is being developed to address that need. However, for evaluating the HARMONIE-SPS performance in classifying system disturbances and mitigating consequences, a cyber-physical testbed is required to further development and validate the methodology. In this paper, we present a design for a co-simulation testbed leveraging the SCEPTRE™ platform and the real-time digital simulator (RTDS). The integration of these two platforms is detailed, as well as the unique, specific needs for testing HARMONIE-SPS within the environment. Results are presented from tests involving a WSCC 9-bus system with different load shedding scenarios with varying cyber-physical impact.
Traditional protective relay voting schemes utilize simple logic to achieve confidence in relay trip actions. However, the smart grid is rapidly evolving and there are new needs for a next-generation relay voting scheme. In such new schemes, aspects such as inter-relay relationships and out-of-band data can be included. In this work, we explore the use of consensus algorithms and how they can be utilized for groups of relays to vote on system protection actions and also reach consensus on the values of variables in the system. A proposed design is explored with a simple case study with two different scenarios, including simulation in PowerWorld Simulator, to demonstrate the consensus algorithm benefits and future directions are discussed.
Special protection schemes (SPSs) safeguard the grid by detecting predefined abnormal conditions and deploying predefined corrective actions. Utilities leverage SPSs to maintain stability, acceptable voltages, and loading limits during disturbances. However, traditional SPSs cannot defend against unpredictable disturbances. Events such as cyber attacks, extreme weather, and electromagnetic pulses have unpredictable trajectories and require adaptive response. Therefore, we propose a harmonized automatic relay mitigation of nefarious intentional events (HARMONIE)-SPS that learns system conditions, mitigates cyber-physical consequences, and preserves grid operation during both predictable and unpredictable disturbances. In this paper, we define the HARMONIE-SPS approach, detail progress on its development, and provide initial results using a WSCC 9-bus system.