Abstract
This paper presents an effective reliability assessment technique for the cyber-physical generation systems (CPGS)s. The assessment technique incorporates cybersecurity issues in smart grids considering non-normal random variables with nonlinear dependencies. A Bayesian attack graph is adopted for vulnerability analysis of CPGS and model the probabilistic nature of attack paths. In addition, the meantime-to-compromise is modeled at the operation level instead of the component level, which leads to more accurate results in terms of loss of load expectation and expected energy not supplied. Further, a hybrid approximate-analytical method is presented to assess the capacity outage probability table in power systems. The proposed method overcomes the Sequential Monte Carlo simulation (SMCS) drawbacks and demonstrates the effects of cyber-attack and wind farm correlations on generation capacity adequacy assessment. The proposed method is implemented on the modified IEEE Reliability Test System. A comparison with SMCS demonstrates the efficiency and accuracy of the proposed method.
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References
Bahrami M, Fotuhi-Firuzabad M, Farzin H (2020) Reliability evaluation of power grids considering integrity attacks against substation protective IEDs. IEEE Trans Ind Inf 16(2):1035–1044
Davis KR et al (2015) A cyber-physical modeling and assessment framework for power grid infrastructures. IEEE Trans Smart Grid 6(5):2464–2475
Farahbod S, Niknam T, Mohammadi M, Aghaei J, Shojaeiyan S (2022) Probabilistic and deterministic wind speed prediction: ensemble statistical deep regression network. IEEE Access 10:47063–47075
Gunduz H, Jayaweera D (2018) Reliability assessment of a power system with cyber-physical interactive operation of photovoltaic systems. Int J Electr Power Energy Syst 101:371–384
Hammad E, Farraj A, Kundur D (2019) On cyber-physical coupling and distributed control in smart grids. IEEE Trans Ind Inf 15(8):4418–4429
Kong P (2019) Optimal configuration of interdependence between communication network and power grid. IEEE Trans Ind Inf 15(7):4054–4065
Lau P, Wei W, Wang L, Liu Z, Ten C-W (2020) A cybersecurity insurance model for power system reliability considering optimal defense resource allocation. IEEE Trans Smart Grid 11(5):4403–4414
Leversage DJ, Byres EJ (2008) Estimating a system’s mean time-to-compromise. IEEE Secur Priv 6(1):52–60
Li W, Xie L, Deng Z, Wang Z (2016) False sequential logic attack on SCADA system and its physical impact analysis. Comput Secur 58:149–159
Marashi K, Sarvestani SS, Hurson AR (2018) Consideration of cyber-physical interdependencies in reliability modeling of smart grids. IEEE Trans Sustain Comput 3(2):73–83
McQueen MA, Boyer WF, Flynn MA, Beitel GA (2006) Time-to-compromise model for cyber risk reduction estimation. In: Gollmann D, Massacci F, Yautsiukhin A (eds) Quality of protection, vol 23. Springer, Boston, MA, p 78
Mell P, Scarfone K, Romanosky S (2006) Common vulnerability scoring system. IEEE Secur Priv Mag 4(6):85–89
National Vulnerability Database, Information Technology Laboratory (ITL), National Institute of Standards and Technology (NIST). https://nvd.nist.gov/vuln-metrics/cvss. Accessed 29 Apr 2022
Poolsappasit N, Dewri R, Ray I (2012) Dynamic security risk management using bayesian attack graphs. IEEE Trans Dependable Secure Comput 9(1):61–74
Probability Methods Subcommittee (1979) A report prepared by the reliability test system task force of the application of probability methods subcommittee, “IEEE reliability test system.” IEEE Trans Power Appar Syst 98(6):2047–2054
Rostami A, Mohammadi M, Rastegar M (2020) An improved transformation based probabilistic load flow analysis using appropriate reference variable. Int J Electr Power Energy Syst 120:106052
Shi L, Dai Q, Ni Y (2018) Cyber–physical interactions in power systems: a review of models, methods, and applications. Electr Power Syst Res 163:396–412
Shojaeiyan S, Niknam T, Nafar M (2021) A novel bio-inspired stochastic framework to solve energy management problem in hybrid AC-DC microgrids with uncertainty. Int J Bio-Inspired Comput 18(3):165–175
Stergiopoulos G, Dedousis P, Gritzalis D (2022) Automatic analysis of attack graphs for risk mitigation and prioritization on large-scale and complex networks in Industry 4.0. Int J Inf Secur 21(1):37–59
Ten C-W, Liu C-C, Manimaran G (2008) Vulnerability assessment of cybersecurity for SCADA systems. IEEE Trans Power Syst 23(4):1836–1846
Wang C, Zhang T, Luo F, Li F, Liu Y (2019) Impacts of cyber system on microgrid operational reliability. IEEE Trans Smart Grid 10(1):105–115
Xiang Y, Ding Z, Zhang Y, Wang L (2016) Power system reliability evaluation considering load redistribution attacks. IEEE Trans Smart Grid. https://doi.org/10.1109/TSG.2016.2569589
Xin Q, Guo H, Sun B, Zhang JW, Chen C (2015) Cyber-physical modeling and cyber-contingency assessment of hierarchical control systems. IEEE Trans Smart Grid 6(5):2375–2385
Żebrowski P, Couce-Vieira A, Mancuso A (2022) A bayesian framework for the analysis and optimal mitigation of cyber threats to cyber-physical systems. Risk Anal. https://doi.org/10.1111/risa.13900
Zhang Y, Wang L, Xiang Y, Ten C-W (2015) Power system reliability evaluation with scada cybersecurity considerations. IEEE Trans Smart Grid 6(4):1707–1721
Zhang Y, Wang L, Xiang Y, Ten C-W (2016) Inclusion of SCADA cyber vulnerability in power system reliability assessment considering optimal resources allocation. IEEE Trans Power Syst 31(6):4379–4394
Zhang Y, Xiang Y, Wang L (2017) Power system reliability assessment incorporating cyber attacks against wind farm energy management systems. IEEE Trans Smart Grid 8(5):2343–2357
Zhao Y, Liu Q, Kuang J, Xie K, Du W (2021) Modeling multivariate dependence by nonparametric pair-copula construction in composite system reliability evaluation. Int J Electr Power Energy Syst 124:106373
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This work has been supported by the Center for International Scientific Studies and Collaboration (CISSC), Ministry of Science, Research and Technology.
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Rostami, A., Mohammadi, M. & Karimipour, H. Reliability Assessment of Cyber-Physical Generation System. Iran J Sci Technol Trans Electr Eng 47, 617–626 (2023). https://doi.org/10.1007/s40998-022-00566-6
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DOI: https://doi.org/10.1007/s40998-022-00566-6