Distributed monitoring for the prevention of cascading failures in operational power grids

Electrical power grids are vulnerable to cascading failures that can lead to large blackouts. Detection and prevention of cascading failures in power grids is impor- tant. Currently, grid operators mainly monitor the state (loading level) of individual components in power grids. The complex architecture of power grids, with many interdependencies, makes it difficult to aggregate data provided by local compo- nents in a timely manner and meaningful way: monitoring the resilience with re- spect to cascading failures of an operational power grid is a challenge. This paper addresses this challenge. The main ideas behind the paper are that (i) a robustness metric based on both the topology and the operative state of the power grid can be used to quantify power grid robustness and (ii) a new proposed a distributed computation method with self-stabilizing properties can be used to achieving near real-time monitoring of the robustness of the power grid. Our con- tributions thus provide insight into the resilience with respect to cascading failures of a dynamic operational power grid at runtime, in a scalable and robust way. Com- putations are pushed into the network, making the results available at each node, allowing automated distributed control mechanisms to be implemented on top.

[1]  V. Belevitch,et al.  Summary of the History of Circuit Theory , 1962, Proceedings of the IRE.

[2]  Patrick D. McDaniel,et al.  Security and Privacy Challenges in the Smart Grid , 2009, IEEE Security & Privacy.

[3]  Piet Van Mieghem,et al.  A topological investigation of phase transitions of cascading failures in power grids , 2014, 1407.4953.

[4]  Devavrat Shah,et al.  Fast Distributed Algorithms for Computing Separable Functions , 2005, IEEE Transactions on Information Theory.

[5]  Wilsun Xu,et al.  Load Monitoring Using Distributed Voltage Sensors and Current Estimation Algorithms , 2014, IEEE Transactions on Smart Grid.

[6]  Haibo He,et al.  Multi-Contingency Cascading Analysis of Smart Grid Based on Self-Organizing Map , 2013, IEEE Transactions on Information Forensics and Security.

[7]  Xie Xiaorong.  WIDE-AREA REAL TIME DYNAMIC SECURITY MONITORING SYSTEM OF NORTH CHINA POWER GRID , 2004 .

[8]  Devavrat Shah,et al.  Gossip Algorithms , 2009, Found. Trends Netw..

[9]  Anjan Bose,et al.  Towards More Flexible and Robust Data Delivery for Monitoring and Control of the Electric Power Grid , 2007 .

[10]  Panayiotis Kotzanikolaou,et al.  Risk mitigation strategies for critical infrastructures based on graph centrality analysis , 2015, Int. J. Crit. Infrastructure Prot..

[11]  Radhika Nagpal,et al.  Firefly-inspired sensor network synchronicity with realistic radio effects , 2005, SenSys '05.

[12]  Frances M. T. Brazier,et al.  A robustness metric for cascading failures by targeted attacks in power networks , 2013, 2013 10th IEEE INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC).

[13]  Márk Jelasity,et al.  Gossip-based aggregation in large dynamic networks , 2005, TOCS.

[14]  A. El-Sakkary,et al.  The gap metric: Robustness of stabilization of feedback systems , 1985 .

[15]  Adilson E Motter,et al.  Cascade-based attacks on complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Réka Albert,et al.  Structural vulnerability of the North American power grid. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Martijn Warnier,et al.  MATCASC: A tool to analyse cascading line outages in power grids , 2013, 2013 IEEE International Workshop on Inteligent Energy Systems (IWIES).

[18]  Zhang Ning,et al.  Impact of Large-Scale Wind Farm Connecting With Power Grid on Peak Load Regulation Demand , 2010 .

[19]  Gerhard P. Hancke,et al.  Opportunities and Challenges of Wireless Sensor Networks in Smart Grid , 2010, IEEE Transactions on Industrial Electronics.

[20]  R. Arditi,et al.  Coupling in predator-prey dynamics: Ratio-Dependence , 1989 .

[21]  Gilbert M. Masters,et al.  Renewable and Efficient Electric Power Systems , 2004 .

[22]  Franco Zambonelli,et al.  Handling dynamics in diffusive aggregation schemes: An evaporative approach , 2010, Future Gener. Comput. Syst..

[23]  Zhejing Bao,et al.  Analysis of cascading failure in electric grid based on power flow entropy , 2009 .

[24]  Xiaogang Chen,et al.  Impact of Characteristic Path Length on Cascading Failure of Power Grid , 2006, 2006 International Conference on Power System Technology.

[25]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[26]  Hao-Tian Zhang,et al.  Monitoring system for smart grid , 2012, 2012 International Conference on Machine Learning and Cybernetics.

[27]  Ian Dobson,et al.  Examining criticality of blackouts in power system models with cascading events , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[28]  Khosrow Moslehi,et al.  A Reliability Perspective of the Smart Grid , 2010, IEEE Transactions on Smart Grid.

[29]  Piet Van Mieghem,et al.  Performance analysis of communications networks and systems , 2006 .

[30]  Charles Kim,et al.  Vulnerability Assessment of Power Grid Using Graph Topological Indices , 2007 .

[31]  Stephen P. Boyd,et al.  Gossip algorithms: design, analysis and applications , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[32]  David Hales,et al.  Identifying Malicious Peers Before It's Too Late: A Decentralized Secure Peer Sampling Service , 2007, First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007).

[33]  Pei Zhang,et al.  Risk assessment of cascading outages: Part I — Overview of methodologies , 2011, 2011 IEEE Power and Energy Society General Meeting.

[34]  V. E. Lynch,et al.  Critical points and transitions in an electric power transmission model for cascading failure blackouts. , 2002, Chaos.

[35]  Rizos Sakellariou,et al.  A taxonomy of grid monitoring systems , 2005, Future Gener. Comput. Syst..

[36]  T.G. Habetler,et al.  Power line sensornet - a new concept for power grid monitoring , 2006, 2006 IEEE Power Engineering Society General Meeting.

[37]  Fei Xue,et al.  Extended topological approach for the assessment of structural vulnerability in transmission networks , 2010 .

[38]  Frances M. T. Brazier,et al.  Structural vulnerability assessment of electric power grids , 2013, Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control.

[39]  Stefan Dulman,et al.  LossEstimate: Distributed failure estimation in wireless networks , 2012, J. Syst. Softw..

[40]  Frances M. T. Brazier,et al.  An entropy-based metric to quantify the robustness of power grids against cascading failures , 2013 .

[41]  Fei Xue,et al.  Analysis of structural vulnerabilities in power transmission grids , 2009, Int. J. Crit. Infrastructure Prot..

[42]  Sakshi Pahwa,et al.  Robustness measure for power grids with respect to cascading failures , 2011, Cnet@ITC.

[43]  Yogish Sabharwal,et al.  Real Time Contingency Analysis for Power Grids , 2011, Euro-Par.

[44]  Liangzhong Yao,et al.  Vulnerability assessment for cascading failures in electric power systems , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[45]  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.