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Power Grids, Smart Grids and Complex Networks

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Nonlinear Phenomena in Complex Systems: From Nano to Macro Scale

Abstract

We present some possible Complex Networks approaches to study and understand Power Grids and to improve them into Smart Grids . We first sketch the general properties of the Electric System with an attention to the effects of Distributed Generation. We then analyse the effects of renewable power sources on Voltage Controllability. Afterwords, we study the impact of electric line overloads on the nature of Blackouts. Finally, we discuss the possibility of implementing Self Healing capabilities into Power Grids through the use of Routing Protocols.

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References

  1. Arenas A, Diaz-Guilera A, Kurths J, Moreno Y, Zhou C (2008) Synchronization in complex networks. Phys Rep 469:93–153

    Article  MathSciNet  ADS  Google Scholar 

  2. Buldyrev SV, Parshani R, Paul G, Stanley HE, Havlin S (2010) Catastrophic cascade of failures in interdependent networks. Nature 464:1025–1028

    Article  ADS  Google Scholar 

  3. Liu Y-Y, Slotine J-J, Barabasi A-L (2011) Controllability of complex networks. Nature 473:167–173. http://dx.doi.org/10.1038/nature10011

    Google Scholar 

  4. Dorogovtsev SN, Goltsev AV, Mendes JFF (2008) Critical phenomena in complex networks. Rev Mod Phys 80:1275–1335

    Article  ADS  Google Scholar 

  5. Costa LF et al (2011) Analyzing and modeling real-world phenomena with complex networks: a survey of applications. Adv Phys 60:329–412

    Article  ADS  Google Scholar 

  6. Perra N, Gonçalves B, Pastor-Satorras R, Vespignani A (2012) Activity driven modeling of time varying networks. Sci Rep 2. http://dx.doi.org/10.1038/srep00469

  7. Barrat A, Barthelemy M, Vespignani A (2008) Dynamical processes on complex networks Cambridge University Press, Cambridge/New York

    Google Scholar 

  8. Alvarez-Hamelin JI, Fleury E, Vespignani A, Ziviani A (2012) Complex dynamic networks: tools and methods. Comput Netw 56:967–969

    Article  Google Scholar 

  9. Casteigts A, Flocchini P, Quattrociocchi W, Santoro N (2012) Time-varying graphs and dynamic networks. Int J Parallel Emergent Distrib Syst IJPEDS 27:387–408

    Article  Google Scholar 

  10. 2003 Homeland Security Presidential Directive HSPD-7 (2003). http://georgewbush-whitehouse.archives.gov/news/releases/2003/12/20031217-5.html

  11. EU COM (2006) 786 EU directive on European Programme for Critical Infrastructure Protection, Brussels, 12.12.2006. http://eur-lex.europa.eu/LexUriServ/site/en/com/2006/com2006_0786en01.pdf

  12. Rinaldi SM, Peerenboom JP, Kelly TK (2001) Identifying, understanding and analyzing critical infrastructure interdependencies. IEEE Control Syst Mag 21:11–25

    Article  Google Scholar 

  13. Baghaie M, Moeller S, Krishnamachari B (2010) Energy routing on the future grid: a stochastic network optimization approach. In: International conference on power system technology (POWERCON), Hangzhou, 2010, pp 1–8

    Google Scholar 

  14. Stagg G, El-Abiad A (1968) Computer methods in power system analysis. McGraw-Hill Education, New York

    Google Scholar 

  15. Filatrella G, Nielsen AH, Pedersen NF (2008) Analysis of a power grid using a Kuramoto-like model. Eur Phys J B – Condens Matter Complex Syst 61:485–491

    Google Scholar 

  16. Fioriti V, Ruzzante S, Castorini E, Marchei E, Rosato V (2009) Stability of a distributed generation network using the Kuramoto models. In: Setola R, Geretshuber S (eds) Critical information infrastructure security. Springer, Berlin/Heidelberg, pp 14–23

    Chapter  Google Scholar 

  17. Dörfler F, Bullo F (2012) Synchronization and transient stability in power networks and nonuniform Kuramoto oscillators. SIAM J Control Optim 50(3):1616–1642. doi:10.1137/110851584, http://epubs.siam.org/doi/abs/10.1137/110851584

  18. Dobson I, Carreras BA, Lynch VE, Newman DE (2001) System sciences, 2001. In: Proceedings of the 34th annual Hawaii international conference on an initial model fo complex dynamics in electric power system blackouts, pp 710–718. doi:10.1109/HICSS.2001.926274

  19. Wood AJ, Wollenberg BF (1984) Power generation, operation and control. Wiley, New York

    Google Scholar 

  20. Carreras BA, Lynch VE, Dobson I, Newman DE (2002) Critical points and transitions in an electric power transmission model for cascading failure blackouts. Chaos: Interdiscip J Nonlinear Sci 12:985–994

    Article  MATH  MathSciNet  Google Scholar 

  21. Sachtjen ML, Carreras BA, Lynch VE (2000) Disturbances in a power transmission system. Phys Rev E 61:4877–4882

    Article  ADS  Google Scholar 

  22. Youssef M, Scoglio C, Pahwa S (2011) Robustness measure for power grids with respect to cascading failures. In: Proceedings of the 2011 international workshop on modeling, analysis, and control of complex networks, CNET ’11, San Francisco. ITCP, pp 45–49

    Google Scholar 

  23. Stott B, Jardim J, Alsac O (2009) Dc power flow revisited. IEEE Trans Power Syst 24:1290–1300

    Article  Google Scholar 

  24. Scala A, Mureddu M, Chessa A, Caldarelli G, Damiano A (2013) Distributed generation and resilience in power grids. In: Hammerli BM, Kalstad Svendsen N, Lopez J (eds) Critical information infrastructures security. Lecture notes in computer science, vol 7722. Springer, Berlin/Heidelberg, pp 71–79. doi:10.1007/978-3-642-41485-5_7, ISBN:978-3-642-41484-8, http://dx.doi.org/10.1007/978-3-642-41485-5_7

  25. Grainger J, Stevenson W (1994) Power system analysis. McGraw-Hill, New York

    Google Scholar 

  26. Azzalini A (2005) The skew-normal distribution and related multivariate families. Scand J Stat 32:159–188

    Article  MATH  MathSciNet  Google Scholar 

  27. Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput Netw ISDN Syst 30:107–117

    Article  Google Scholar 

  28. Chung F, Zhao W Pagerank and random walks on graphs. http://www.math.ucsd.edu/~fan/wp/lov.pdf

  29. NERC North America Electric Reability Corporation (2006). http://www.nerc.com/

  30. ENTSO-E European Network of Transmission System Operators for Electricity (2008). https://www.entsoe.eu/

  31. Report 1010701 (2005) Mitigating cascading outages on power systems: recent research approaches and emerging methods. Technical report, EPRI

    Google Scholar 

  32. Blackout in the United States and Canada, April 2004 (2004). https://reports.energy.gov/

  33. Pahwa S, Hodges A, Scoglio CM, Wood S (2010) Topological analysis of the power grid and mitigation strategies against cascading failures. In: Proceedings of the 4th international IEEE systems conference, San Diego, pp 272–276

    Google Scholar 

  34. Quattrociocchi W, Caldarelli G, Scala A (2014) Self-healing networks: redundancy and structure. PLoS ONE 9(2):e87986. doi:10.1371/journal.pone.0087986. Public Library of Science. http://dx.doi.org/10.1371%2Fjournal.pone.0087986

  35. Caldarelli G (2007) Scale-free networks Oxford University Press, Oxford

    Google Scholar 

  36. Watts DJ, Strogatz SH (1998) Collective dynamics of /‘small-world/’ networks. Nature 393:440–442. http://dx.doi.org/10.1038/30918

    Google Scholar 

  37. Barabási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512

    Article  MathSciNet  ADS  Google Scholar 

  38. Wilson DB (1996) Generating random spanning trees more quickly than the cover time. In: Proceedings of the 28th annual ACM symposium on the theory of computing, Philadephia. ACM, pp 296–303

    Google Scholar 

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Acknowledgements

AS, GC and WQ thank US grant HDTRA1-11-1-0048, CNR-PNR National Project “Crisis-Lab” and EU FET project MULTIPLEX nr.317532. SP and CS acknowledge the support of the US Department of Energy grant EE-0003812: “Resourceful Kansas”. The contents of the paper do not necessarily reflect the position or the policy of funding parties.

Author information

Authors and Affiliations

  1. ISC-CNR Physics Department, Univ. La Sapienza, Piazzale Moro 5, 00185, Roma, Italy

    Antonio Scala

  2. IMT Alti Studi Lucca, piazza S. Ponziano 6, 55100, Lucca, Italy

    Guido Caldarelli & Alessandro Chessa

  3. Dipartimento di Ingegneria Elettrica ed Elettronica, Univ. di Cagliari, Cagliari, Italy

    Alfonso Damiano

  4. Linkalab, Complex Systems Computational Laboratory, 09129, Cagliari, Italy

    Mario Mureddu

  5. Department of Electrical and Computer Engineering, College of Engineering, Kansas State University, Manhattan, KS, USA

    Sakshi Pahwa & Caterina Scoglio

  6. London Institute of Mathematical Sciences, 22 South Audley St, Mayfair, W1K 2NY, London, UK

    Walter Quattrociocchi

Authors
  1. Antonio Scala
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  2. Guido Caldarelli
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  3. Alessandro Chessa
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  4. Alfonso Damiano
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  5. Mario Mureddu
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  6. Sakshi Pahwa
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  7. Caterina Scoglio
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  8. Walter Quattrociocchi
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Corresponding author

Correspondence to Antonio Scala .

Editor information

Editors and Affiliations

  1. Turin Polytechnic University in Tashkent, Tashkent, Uzbekistan

    Davron Matrasulov

  2. Department of Physics, Boston University, Boston, Massachusetts, USA

    H. Eugene Stanley

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Scala, A. et al. (2014). Power Grids, Smart Grids and Complex Networks. In: Matrasulov, D., Stanley, H. (eds) Nonlinear Phenomena in Complex Systems: From Nano to Macro Scale. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8704-8_8

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  • DOI: https://doi.org/10.1007/978-94-017-8704-8_8

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  • Online ISBN: 978-94-017-8704-8

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