Probabilistic Risk-Based Security Assessment of Power Systems Considering Incumbent Threats and Uncertainties

In-depth security analyses of power systems (PSs) require to consider the vulnerabilities to natural and human-related threats, which may cause multiple dependent contingencies. On the other hand, such events often lead to high impact on the system, so that decision-making aimed to enhance security may become difficult. Introducing the uncertainty, the risk associated to each contingency can be evaluated, thus allowing to perform effective contingency ranking. This paper describes an in-depth security assessment methodology, based on an “extended” definition of risk (including threats, vulnerability, contingency, and impact) aimed to perform the risk assessment of the integrated power and Information and Communication Technology (ICT) systems. The results of the application to test cases and realistic PSs show the added value of the proposed approach with respect to conventional security analyses in dealing with uncertainty of threats, vulnerabilities, and system response.

[1]  Tranchita Rativa,et al.  Evaluation du risque pour la sécurité des réseaux électrique face aux événements intentionnels , 2008 .

[2]  V. Vittal,et al.  Risk Assessment for Transformer Loading , 2001, IEEE Power Engineering Review.

[3]  R. Billinton,et al.  Application of adverse and extreme adverse weather: modelling in transmission and distribution system reliability evaluation , 2006 .

[4]  Roberto Calisti,et al.  Probabilistic assessment of electric power grids vulnerability under seismic action: a case study , 2013 .

[5]  Pierluigi Mancarella,et al.  Modeling and Evaluating the Resilience of Critical Electrical Power Infrastructure to Extreme Weather Events , 2017, IEEE Systems Journal.

[6]  S. Guikema,et al.  Statistical models of the effects of tree trimming on power system outages , 2006, IEEE Transactions on Power Delivery.

[7]  P. Pourbeik,et al.  Review of the Current Status of Tools and Techniques for Risk-Based and Probabilistic Planning in Power Systems , 2011 .

[8]  Fred Nicolls,et al.  Characterisation of power system events on South African transmission power lines , 2012 .

[9]  M. Paolone,et al.  A Statistical Approach for Estimating the Correlation between Lightning and Faults in Power Distribution Systems , 2006, 2006 International Conference on Probabilistic Methods Applied to Power Systems.

[10]  M. E. Ruiz,et al.  Against All Odds , 2011, IEEE Power and Energy Magazine.

[11]  Patrick Panciatici,et al.  iTesla: Innovative tools for electrical system security within large areas , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[12]  I. Dobson,et al.  Initial review of methods for cascading failure analysis in electric power transmission systems IEEE PES CAMS task force on understanding, prediction, mitigation and restoration of cascading failures , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[13]  Gerd Kjolle,et al.  An integrated framework for power and ICT system risk-based security assessment , 2013, 2013 IEEE Grenoble Conference.

[14]  D. Štraub,et al.  Effect of weather conditions, geography and population density on wildfire occurrence: A Bayesian Network model , 2011 .

[15]  J. Morales,et al.  Point Estimate Schemes to Solve the Probabilistic Power Flow , 2007, IEEE Transactions on Power Systems.

[16]  C. Singh,et al.  A practical approach for integrated power system vulnerability analysis with protection failures , 2004, IEEE Transactions on Power Systems.

[17]  Gerd Kjolle,et al.  Risk assessment tool for operation: From threat models to risk indicators , 2015, 2015 IEEE Eindhoven PowerTech.

[18]  L. Soder,et al.  Modelling of Ice Storms and their Impact Applied to a Part of the Swedish Transmission Network , 2007, 2007 IEEE Lausanne Power Tech.

[19]  E. Ciapessoni,et al.  Cascadings in large power systems: Benchmarking static vs. time domain simulation , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[20]  Aldo V. Vecchia,et al.  A unified approach to probabilistic risk assessments for earthquakes, floods, landslides, and volcanoes : proceedings of a multidisciplinary workshop held in Golden, Colorado, November 16-17, 1999 , 1999 .

[21]  M.H.J. Bollen,et al.  On Operational Risk Assessment in Transmission Systems - Weather Impact and Illustrative Example , 2008, Proceedings of the 10th International Conference on Probablistic Methods Applied to Power Systems.

[22]  V. Vittal,et al.  Online Risk-Based Security Assessment , 2002, IEEE Power Engineering Review.

[23]  D. Jayaweera,et al.  Value of Security: Modeling Time-Dependent Phenomena and Weather Conditions , 2002, IEEE Power Engineering Review.

[24]  Robin Preece,et al.  Probabilistic Risk Assessment of Rotor Angle Instability Using Fuzzy Inference Systems , 2015, IEEE Transactions on Power Systems.

[25]  E. Ciapessoni,et al.  Effect of renewable and load uncertainties on the assessment of power system operational risk , 2014, 2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS).

[26]  Mhj Math Bollen,et al.  Literature search for reliability data of components in electric distribution networks , 1993 .

[27]  Cesar A. Silva-Monroy,et al.  Conceptual Framework for Developing Resilience Metrics for the Electricity, Oil, and Gas Sectors in the United States , 2014 .

[28]  William H. Bartley,et al.  Analysis of Transformer Failures , 2003 .

[29]  F. Silvestro,et al.  An innovative platform integrating deterministic and probabilistic tools for power system security assessment within a unified approach , 2012, 2012 IEEE International Energy Conference and Exhibition (ENERGYCON).

[30]  D. Wells,et al.  New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement , 1994, Bulletin of the Seismological Society of America.

[31]  H. P. Berg,et al.  Reliability of main transformers , 2011 .

[32]  Yang Liu.  Short-term operational reliability evaluation for power systems under extreme weather conditions , 2015, 2015 IEEE Eindhoven PowerTech.

[33]  Enrico Pons,et al.  Analysis of the structural vulnerability of the interconnected power grid of continental Europe with the Integrated Power System and Unified Power System based on extended topological approach , 2013 .

[34]  H. Borsi,et al.  Estimation of the Lifetime of the Electrical Components in Distribution Networks , 2007, IEEE Transactions on Power Delivery.

[35]  NUREG/CR-6949, "The Employment of Empirical Data and Bayesian Methods in Human Reliability Analysis: A Feasibility Study." , 2008 .

[36]  T. J. Overbye.  Engineering resilient cyber-physical systems , 2012, 2012 IEEE Power and Energy Society General Meeting.

[37]  Seth Blumsack,et al.  The Topological and Electrical Structure of Power Grids , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[38]  R. Barben.  Vulnerability Assessment of Electric Power Supply under Extreme Weather Conditions , 2010 .

[39]  Stephen H. Conrad,et al.  A behavioral theory of insider-threat risks: A system dynamics approach , 2008, TOMC.

[40]  A. Torres,et al.  Bayesian Networks and Monte Carlo Simulations in the Evaluation of the Risk of Terrorism for the Colombian Electrical Infrastructure , 2006, 2006 International Conference on Probabilistic Methods Applied to Power Systems.