Reliability Analysis of Electric Power Systems Considering Cyber Security
The modern smart grid is the next generation of electric power systems; it is essentially a cyber and physical system (CPS). The essential part of CPS is the energy management system (EMS) and supervisory control and data acquisition (SCADA), which is increasingly the focus of insider and external cyberattacks. The SCADA/EMS system’s cybersecurity faces significant obstacles, which affect the electric power system’s dependability.
The dependability of the system will be impacted by cyber threat characteristics. Cyber threats can impact system reliability due to their diverse attack paths and skill sets.
Furthermore, the target system’s altered structure could also affect the system’s dependability. Nonetheless, there is a dearth of research on the reliability analysis of the electrical power system with regard to cybersecurity concerns.
Numerous mathematical techniques can be employed to measure cyber threats, and simulation methods can be used to create a reliability analysis model. For instance, Bayesian Networks (BNs) can be used to model the attack paths of cyberattacks on the exploited iii vulnerabilities in order to analyze the vulnerabilities of the SCADA/EMS system in the electric power system. Cyberattack characteristics can be characterized by applying the Common Vulnerability Scoring System (CVSS)-based mean time-to-compromise (MTTC) and mean time-to-failure (MTTF). Furthermore, methods for simulating system reliability analysis, such as sequential or non-sequential Monte Carlo Simulation (MCS), can compute reliability indices.
This thesis examines the SCADA/EMS system’s dependability in the electric power system while taking various cybersecurity concerns into account. Bayesian Networks (BNs) create the Bayesian attack path models of cyberattacks on the SCADA/EMS components. Cyberattacks are measured by their mean time-to-compromise (MTTC), which is determined by applying a modified Semi-Markov Process (SMP) and MTTC models. The system reliability is assessed by computing the electric power system reliability indexes, such as LOLP and EENS, through MCS, based on the IEEE Reliability Test System (RTS) 96. Additionally, various lurking strategies for cyberattacks are taken into account and examined.
The simulation results indicate that the MTTC of cyberattacks, which is impacted by the attack paths, attacking skill levels, and the complexity of the target structure, is closely related to the system reliability of the SCADA/EMS system in the electric power system taking cyber security into consideration. LOLP values decrease in tandem with an increase in MTTC values of cyberattacks, indicating improved system safety and reliability. Furthermore, as the complexity of cyberattack lurking strategies rises, the EENS values of the corresponding IV scenarios sharply rise even though the LOLP values of the scenarios don’t. This suggests that cyber security is worse and system reliability is more unpredictable. Insider attacks are finally covered, along with an estimation and comparison of the corresponding LOLP and EENS values taking lurking behavior into account. Due to insider attacks that cause MTTCs to drop, both LOLP and EENS values sharply increase. This suggests that insider attacks have a greater potential to negatively affect system dependability than do external cyberattacks. The findings of this thesis could aid in the development of ideal defenses against cyberattacks on the electrical grid.
