Increasing the Resilience of Cyber Physical Systems in Smart Grid Environments using Dynamic Cells

Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

Abstract:

Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: Cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1130543

References:

1] D. Wachholder and C. Stary, “Enabling emergent behavior in systems-of-systems through bigraph-based modeling,” in System of Systems Engineering Conference (SoSE), 2015 10th, may 2015, pp. 334–339.
[2] I. S. Danda B. Rawat Joel J.P.C. Rodrigues, Cyber-Physical Systems: From Theory to Practice. CRC Press, 2015.
[3] J. Shi, J. Wan, H. Yan, and H. Suo, “A survey of Cyber-Physical Systems,” 2011 International Conference on Wireless Communications and Signal Processing, WCSP 2011, 2011.
[4] K. G. S. L. M. P. Gaddadevara Matt Siddesh Ganesh Chandra Deka, Cyber-Physical Systems: A Computational Perspective. Chapman and Hall/CRC, 2015.
[5] N. B. M. Isa, T. C. Wei, A.Yatim, and A. H. M. Yatim, “Smart grid technology: Communications, power electronics and control system,” in International Conference on Sustainable Energy Engineering and Application (ICSEEA). IEEE, oct 2015, pp. 10–14.
[Online]. Available: http://ieeexplore.ieee.org/lpdocs/epic03/ wrapper.htm?arnumber=7380737
[6] K. Sampigethaya, R. Poovendran, and T. Br, “Cyber-physical integration in future aviation information systems,” in 2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC). IEEE, 2012, pp. 7C2—-1.
[7] J. Plourde, D. Arney, and J. M. Goldman, “OpenICE: An open, interoperable platform for medical cyber-physical systems,” 2014 ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2014, p. 221, 2014.
[8] S. Karnouskos, “Cyber-physical systems in the SmartGrid,” IEEE International Conference on Industrial Informatics (INDIN), pp. 20–23, 2011.
[9] L. Rogovchenko-Buffoni, A. Tundis, M. Z. Hossain, M. Nyberg, and P. Fritzson, “An Integrated Toolchain For Model Based Functional Safety Analysis,” Journal of Computational Science, vol. 5, no. 3, pp. 408–414, 2014.
[Online]. Available: http: //dx.doi.org/10.1016/j.jocs.2013.08.009
[10] Y. Strengers, “Smart Energy in Everyday Life: Are You Designing for Resource Man?” interactions, vol. 21, no. 4, pp. 24–31, jul 2014.
[Online]. Available: http://doi.acm.org/10.1145/2621931
[11] H. H. Yan, J. F. Wan, and H. Suo, “Adaptive Resource Management for Cyber-Physical Systems,” in Mechatronics and Applied Mechanics, ser. Applied Mechanics and Materials, vol. 157. Trans Tech Publications, 2012, pp. 747–751.
[12] P. Smith, D. Hutchison, J. P. G. Sterbenz, M. Sch¨oller, A. Fessi, M. Karaliopoulos, C. Lac, and B. Plattner, “Network resilience: A systematic approach,” IEEE Communications Magazine, vol. 49, no. 7, pp. 88–97, 2011.
[13] G. Denker, N. Dutt, S. Mehrotra, M.-O. Stehr, C. Talcott, and N. Venkatasubramanian, “Resilient dependable cyber-physical systems: a middleware perspective,” Journal of Internet Services and Applications, vol. 3, no. 1, pp. 41–49, 2012.
[Online]. Available: http://dx.doi.org/10.1007/s13174-011-0057-4
[14] M. Amin, “Challenges in reliability, security, efficiency, and resilience of energy infrastructure: Toward smart self-healing electric power grid,” in Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE, jul 2008, pp. 1–5.
[15] N. A. S. Abdullah, N. L. M. Noor, and E. N. M. Ibrahim, “Resilient organization: Modelling the capacity for resilience,” International Conference on Research and Innovation in Information Systems, ICRIIS, vol. 2013, pp. 319–324, 2013.
[16] X. Zhao, Z. Zhou, Z. Li, and Z. Qin, “Redundancy deployment strategy based on energy balance for wireless sensor networks,” in Communications and Information Technologies (ISCIT), 2012 International Symposium on, oct 2012, pp. 702–706.
[17] E. Rodriguez-Diaz, J. C. Vasquez, and J. M. Guerrero, “Intelligent DC Homes in Future Sustainable Energy Systems: When efficiency and intelligence work together.” IEEE Consumer Electronics Magazine, vol. 5, no. 1, pp. 74–80, jan 2016.
[18] P. Smith and A. Schaeffer-Filho, “Management Patterns for Smart Grid Resilience,” in Service Oriented System Engineering (SOSE), 2014 IEEE 8th International Symposium on, apr 2014, pp. 415–416.
[19] D. Seo, H. Lee, and A. Perrig, “Secure and Efficient Capability-Based Power Management in the Smart Grid,” in Parallel and Distributed Processing with Applications Workshops (ISPAW), 2011 Ninth IEEE International Symposium on, may 2011, pp. 119–126.
[20] A. Pahwa, S. A. DeLoach, B. Natarajan, S. Das, A. R. Malekpour, S. M. Shafiul Alam, and D. M. Case, “Goal-Based Holonic Multiagent System for Operation of Power Distribution Systems,” IEEE Transactions on Smart Grid, vol. 6, no. 5, pp. 2510–2518, 2015.
[21] C. M. Colson, M. H. Nehrir, and R. W. Gunderson, “Distributed multi-agent microgrids: A decentralized approach to resilient power system self-healing,” Proceedings - ISRCS 2011: 4th International Symposium on Resilient Control Systems, pp. 83–88, 2011.
[22] A. Berns and S. Ghosh, “Dissecting Self- * Properties,” 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, pp. 10–19, 2009.
[23] D. E. Olivares, A. Mehrizi-Sani, A. H. Etemadi, C. A. Ca˜nizares, R. Iravani, M. Kazerani, A. H. Hajimiragha, O. Gomis-Bellmunt, M. Saeedifard, R. Palma-Behnke, G. A. Jim´enez-Est´evez, and N. D. Hatziargyriou, “Trends in Microgrid Control,” IEEE Transactions on Smart Grid, vol. 5, no. 4, pp. 1905–1919, 2014.
[24] A. Koestler, The Ghost in the Machine. Macmillan, 1967.
[25] M. Calabrese, A. Amato, V. di Lecce, and V. Piuri, “Hierarchical-granularity holonic modelling,” Journal of Ambient Intelligence and Humanized Computing, vol. 1, no. 3, pp. 199–209, 2010.
[26] P. Legato and R. Mazza, “A Simulation Optimization based Approach for Team Building in Cyber Security,” Journal of Simulation and Process Modelling, 2015.
[27] M. Erol-Kantarci and H. T. Mouftah, “Energy-Efficient Information and Communication Infrastructures in the Smart Grid: A Survey on Interactions and Open Issues,” IEEE Communications Surveys and Tutorials, vol. 17, no. 1, pp. 179–197, 2015.
[28] A. Hahn and M. Govindarasu, “Cyber attack exposure evaluation framework for the smart grid,” IEEE Transactions on Smart Grid, vol. 2, no. 4, pp. 835–843, 2011.
[29] C. Cecati, C. Citro, A. Piccolo, and P. Siano, “Smart operation of wind turbines and diesel generators according to economic criteria,” IEEE Transactions on Industrial Electronics, vol. 58, no. 10, pp. 4514–4525, 2011.
[30] V. C. Gungor, D. Sahin, T. Kocak, S. Ergut, C. Buccella, C. Cecati, and G. P. Hancke, “Smart Grid Technologies: Communication Technologies and Standards,” IEEE Transactions on Industrial Informatics, vol. 7, no. 4, pp. 529–539, nov 2011.
[Online]. Available: http://ieeexplore. ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6011696
[31] R. M. Oviedo, F. Ramos, S. Gormus, P. Kulkarni, and M. Sooriyabandara, “A comparison of centralized and distributed monitoring architectures in the smart grid,” IEEE Systems Journal, vol. 7, no. 4, pp. 832–844, 2013.
[32] S. Ramchurn, P. Vytelingum, A. Rogers, and N. Jennings, “Agent-Based Control for Decentralised Demand Side Management in the Smart Grid,” AAMAS ‘11, Taipei,, pp. 5–12, 2011.
[Online]. Available: http://eprints.soton.ac.uk/271985/
[33] A. Vaccaro, V. Loia, G. Formato, P. Wall, and V. Terzija, “A Self-Organizing Architecture for Decentralized Smart Microgrids Synchronization, Control, and Monitoring,” IEEE Transactions on Industrial Informatics, vol. 11, no. 1, pp. 289–298, feb 2015.
[Online]. Available: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper. htm?arnumber=6863653
[34] S. Chouhan, J. Ghorbani, H. Inan, A. Feliachi, and M. A. Choudhry, “Smart MAS restoration for distribution system with Microgrids,” IEEE Power and Energy Society General Meeting, 2013.
[35] A. Felix, H. S. V. S. K. Nunna, S. Doolla, and A. Shukla, “Multi agent based restoration for smart distribution system with microgrids,” 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015, pp. 2341–2347, 2015.
[36] A. Barbato, A. Capone, L. Chen, F. Martignon, and S. Paris, “A distributed demand-side management framework for the smart grid,” Computer Communications, vol. 57, pp. 13–24, 2015.
[Online]. Available: http://dx.doi.org/10.1016/j.comcom.2014.11.001
[37] R. Deng, Z. Yang, F. Hou, M.-Y. Chow, and J. Chen, “Distributed Real-Time Demand Response in Multiseller–Multibuyer Smart Distribution Grid,” IEEE Transactions on Power Systems, vol. 30, no. 5, pp. 2364–2374, 2015.