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1 This survey presents an analysis concerning faults and their causes affecting electric power grids, aiming to identify both: (i) strategies and approaches that are used to improve EPG resilience, and (ii) research opportunities in some areas that have not + 1114 word(s) 1114 2019-12-17 10:26:58 |
2 format change -4 word(s) 1110 2019-12-19 06:42:59 | |
3 format change + 3 word(s) 1113 2020-10-23 03:20:55 |
Power Grid

One of the most critical infrastructures in the world is electrical power grids (EPGs). New threats affecting EPGs, and their different consequences, are analyzed in this survey along with different approaches that can be taken to prevent or minimize those consequences, thus improving EPG resilience. The necessity for electrical power systems to become resilient to such events is becoming compelling; indeed, it is important to understand the origins and consequences of faults. This survey provides an analysis of different types of faults and their respective causes, showing which ones are more reported in the literature. As a result of the analysis performed, it was possible to identify four clusters concerning mitigation approaches, as well as to correlate them with the four different states of the electrical power system resilience curve.

  • natural disasters
  • cyber and physical attacks
  • system errors
  • electrical power grid faults
  • resilient system

1. Power Grid Faults

The scale of the cause will influence the respective consequences of the originated fault. If a small cause occurs, it will originate a small-scale fault that will only affect some residential houses and will be easy to repair, possibly being solved in a few hours. On the contrary, if it is a large-scale cause, like, for example, a hurricane or a terrorist attack, it can originate a large-scale fault, like a blackout or a cascading failure, affecting a large geographical area and possibly taking days or weeks to recover from. Large-scale outages also have serious economic and social consequences that will affect the consumer. In the case of a large-scale outage, a robust system is expected to recover, when compared to a non-robust system, and to have the capacity of restoring to its initial state.

In the entry, three main cause clusters are reported:

  • Natural Causes: different types of natural disasters that could lead to a fault in the EPG, such as hurricanes, storms, flooding, earthquakes, tornados, heat waves or solar flares;
  • Errors: causes related to human faults or equipment technical malfunction;
  • Attacks: cyber-attacks such as denial of service (most common), or human attacks such as terrorism.

These causes, when they occur, can lead to a wide variety of faults in the EPG. In Table 1, different EPG faults are presented, separated into three clusters for each cause that originates the faults. First, there are natural causes, where extreme events like hurricanes, storms or flooding are considered. Second, there are errors, which can be due to human or equipment failure, and third, there are attacks, of cyber or physical origin. Table 1 shows the principal references where these causes/faults are reported.

Table 1. Faults reported in the literature.




Natural Causes

-                      Blackout


-                      Cascading fault

-                      Collapse of transmission towers

-                      Damage and faults on substations

-                      Downed wires

-                      Lines disconnected

-                      Fault currents

-                      Fault of distribution and transmission lines

-                      Fault of transformers

-                      Faults and damage to overhead transmission and distribution lines

-                      Flashover of transmission lines

-                      Increased current

-                      Line faults

-                      Power loss

-                      Line overloads

-                      Localized blackouts and momentary interruptions

-                      Short circuits

-                      Stability limits exceeded

-                      Substation flood

-                      Thermal overloads

-                      Transfer capability limited

-                      Transformer slippage on the foundation and fall or complete collapse of the foundation

-                      Underground cable loads affected

-                      Voltage and frequency instabilities


-                      Blackout


-                      Cascading outages

-                      Fault currents

-                      Fault of transformers

-                      Frequency deviation

-                      Hidden faults of protection

-                      Line faults

-                      Line overloads

-                      Voltage and frequency instabilities


-                      Blackout

-                      Cascading failures

-                      Control infrastructures of smart grids affected


-                      Delay, blockage or corruption

-                      Downed wires

-                      Economic and social disruptions

-                      Line faults

-                      Localized blackouts and momentary interruptions

-                      Power loss

-                      Widespread damage

2. The Origins of Power Grid Faults

In order to analyze all the relations amongst causes and faults in EPGs, a graphical representation using visualization software NodeXL (Social Media Research Foundation, California, CA, USA) was performed, following the strategy adopted in[50][51]. With this analysis, it was possible to understand the importance of studying the cause/fault relations and identify less studied areas. For this analysis, a range of 65 articles was studied, and the same article can mention different faults regarding one cause or vice versa, i.e., the same fault can be instigated by different causes. The analysis performed is represented by the graph presented in Figure 1, created using the Force Atlas algorithm[52]. The blue squares denote causes, and the corresponding faults are denoted by green triangles. The size of the elements (squares and triangles) is proportional to the number of times they are discussed in the surveyed literature.

Figure 1. Graphical relationship of EPG faults and causes.

Analyzing Figure 1 and considering the abovementioned clusters, the literature review shows that 84% of articles mention faults due to natural causes. The most referenced natural causes are hurricanes and storms, with 22% of articles mentioning these causes, following by other natural events such as heat waves or thunderstorms, which were studied in 20% of all articles considered in this survey. Still in the natural causes cluster, windstorms and tornados represent a 14% percentage of articles, and earthquakes appear in 11% of the studied articles[15][27][28][29]. Continuing to the errors cluster, equipment errors and human failures were analyzed together and represent 17% of studied articles, while animal or physical contacts with lines represent only 5% of the articles considered for this survey. Finally, for the attacks cluster, cyber-attacks represent 17% of read articles, a huge percentage when compared with physical attacks, which represent only 6% of the studied literature for this survey[19][30].

The abovementioned causes are connected to the resulting faults, represented in Figure 3 by green triangles. As seen before in Table 1, the same fault can be originated by different causes. In Figure 1, the largest triangles represent faults that are mentioned more in the analyzed articles for this survey. Blackout, the fault represented by the largest triangle in Figure 1, was referenced in 16% of the 65 articles studied in this analysis. A detailed observation in Figure 2a, focusing on the blackout green triangle and its connecting lines from causes, shows that some of the lines are thicker than others. For example, the line that connects hurricanes and storms is denser than the line connecting physical attacks, meaning that blackout is more related with hurricanes and storms than with physical attacks.

Figure 2. Close-up views of the causes/faults graph.

Also, looking at Figure 2b, both “Hurricane and storms” and “Equipment and human failures”, despite being of different clusters, i.e., natural causes and errors, can originate the same type of faults such as cascading failures and fault currents, the second most referenced faults in studied articles, being mentioned in 9% of them.

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  1. James Hare; Xiaofang Shi; Shalabh Gupta; Ali Bazzi; Fault diagnostics in smart micro-grids: A survey. Renewable and Sustainable Energy Reviews 2016, 60, 1114-1124, 10.1016/j.rser.2016.01.122.
  2. Abi-Samra, N.C.; Malcolm, W.P. Extreme weather effects on power systems. In Proceedings of the IEEE Power and Energy Society General Meeting, Detroit, MI, USA, 24–28 July 2011; pp. 1–5.
  3. Abi-Samra, N.C.; Forsten, K.R.; Entriken, R. Sample Effects of extreme weather on power systems and components, part I: Sample effects on distribution systems. In Proceedings of the 2010 IEEE Power and Energy Society General Meeting, Providence, RI, USA, 25–29 July 2010; Volume 34, pp. 1–34.
  4. Anya Castillo; Risk analysis and management in power outage and restoration: A literature survey. Electric Power Systems Research 2014, 107, 9-15, 10.1016/j.epsr.2013.09.002.
  5. Mathaios Panteli; Pierluigi Mancarella; Modeling and Evaluating the Resilience of Critical Electrical Power Infrastructure to Extreme Weather Events. IEEE Systems Journal 2015, 11, 1733-1742, 10.1109/jsyst.2015.2389272.
  6. Fauzan Hanif Jufri; Jun-Sung Kim; Jaesung Jung; Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event. Energies 2017, 10, 1779, 10.3390/en10111779.
  7. David Yates; Byron Quan Luna; Roy Rasmussen; Dick Bratcher; Luca Garrè; Fei Chen; Mukul Tewari; Peter Friis-Hansen; Yates D.; Luna B.Q.; et al. Stormy Weather: Assessing Climate Change Hazards to Electric Power Infrastructure: A Sandy Case Study. IEEE Power and Energy Magazine 2014, 12, 66-75, 10.1109/mpe.2014.2331901.
  8. Chad Abbey; David Cornforth; Nikos Hatziargyriou; Keiichi Hirose; Alexis Kwasinski; Elias Kyriakides; Glenn Platt; Lorenzo Reyes; Siddharth Suryanarayanan; Powering Through the Storm: Microgrids Operation for More Efficient Disaster Recovery. IEEE Power and Energy Magazine 2014, 12, 67-76, 10.1109/mpe.2014.2301514.
  9. Singh, N.; Gupta, A. A study on mitigation of blackout risks in smart grid. In Proceedings of the IICPE IEEE India International Conference on Power Electronics, Patiala, India, 17–19 November 2016; pp. 1–4.
  10. Martijn Warnier; Stefan Dulman; Yakup Koç; Eric Pauwels; Distributed monitoring for the prevention of cascading failures in operational power grids. International Journal of Critical Infrastructure Protection 2017, 17, 15-27, 10.1016/j.ijcip.2017.03.003.
  11. Chuanyi Ji; Yun Wei; H. Vincent Poor; Resilience of Energy Infrastructure and Services: Modeling, Data Analytics, and Metrics. Proceedings of the IEEE 2017, 105, 1354-1366, 10.1109/jproc.2017.2698262.
  12. Haixiang Gao; Ying Chen; Shengwei Mei; ShaoWei Huang; Yin Xu; Resilience-Oriented Pre-Hurricane Resource Allocation in Distribution Systems Considering Electric Buses. Proceedings of the IEEE 2017, 105, 1214-1233, 10.1109/jproc.2017.2666548.
  13. Allison C. Reilly; Gina L. Tonn; Chengwei Zhai; Seth D. Guikema; Hurricanes and Power System Reliability-The Effects of Individual Decisions and System-Level Hardening. Proceedings of the IEEE 2017, 105, 1429-1442, 10.1109/jproc.2017.2689720.
  14. McClure, G.; Langlois, S.; Rogier, J. Understanding how overhead lines respond to localized high intensity wind storms. In Proceedings of the 2008 Structures Congress-Structures Congress 2008: Crossing the Borders, Vancouver, British, 24–26 April 2008; American Society of Civil Engineers: Reston, VA, USA, 2008; Volume 314, pp. 1–10
  15. Mathaios Panteli; Pierluigi Mancarella; Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies. Electric Power Systems Research 2015, 127, 259-270, 10.1016/j.epsr.2015.06.012.
  16. David M. Ward; The effect of weather on grid systems and the reliability of electricity supply. Climatic Change 2013, 121, 103-113, 10.1007/s10584-013-0916-z.
  17. Paul Hines; Jay Apt; Sarosh Talukdar; Large blackouts in North America: Historical trends and policy implications. Energy Policy 2009, 37, 5249-5259, 10.1016/j.enpol.2009.07.049.
  18. Chen Chen; Jianhui Wang; Dan Ton; Modernizing Distribution System Restoration to Achieve Grid Resiliency Against Extreme Weather Events: An Integrated Solution. Proceedings of the IEEE 2017, 105, 1267-1288, 10.1109/jproc.2017.2684780.
  19. Araneda, J.C.; Rudnick, H.; Mocarquer, S.; Miquel, P. Lessons from the 2010 Chilean earthquake and its impact on electricity supply. In Proceedings of the IEEE 2010 Powercon International Conference on Power System Technology: Technological Innovations Making Power Grid Smarter, Hangzhou, China, 24–28 October 2010; pp. 1–7.
  20. M. Shinozuka; X. Dong; T. C. Chen; X. Jin; Seismic performance of electric transmission network under component failures. Earthquake Engineering & Structural Dynamics 2007, 36, 227-244, 10.1002/eqe.627.
  21. Camillo Nuti; Alessandro Rasulo; Ivo Vanzi; Seismic safety evaluation of electric power supply at urban level. Earthquake Engineering & Structural Dynamics 2007, 36, 245-263, 10.1002/eqe.622.
  22. Mathaios Panteli; Dimitris N. Trakas; Pierluigi Mancarella; Nikos D. Hatziargyriou; Boosting the Power Grid Resilience to Extreme Weather Events Using Defensive Islanding. IEEE Transactions on Smart Grid 2016, 7, 2913-2922, 10.1109/tsg.2016.2535228.
  23. Zhaohong Bie; Yanling Lin; Gengfeng Li; Furong Li; Battling the Extreme: A Study on the Power System Resilience. Proceedings of the IEEE 2017, 105, 1253-1266, 10.1109/jproc.2017.2679040.
  24. Faults Monitoring System in the Electric Power Grid of Medium Voltage. In Proceedings of the Procedia Computer Science, Porto, Portugal, 8–11 May 2018; Elsevier: Amsterdam, The Netherlands, 2018; Volume 130, pp. 696–703.
  25. R. Billinton; G. Singh; Application of adverse and extreme adverse weather: modelling in transmission and distribution system reliability evaluation. IEE Proceedings - Generation, Transmission and Distribution 2006, 153, 115, 10.1049/ip-gtd:20045058.
  26. Brian Mills; Dan Unrau; Laurel Pentelow; Kelsey Spring; Assessment of lightning-related damage and disruption in Canada. Natural Hazards 2009, 52, 481-499, 10.1007/s11069-009-9391-2.
  27. Zhiyi Li; Mohammad Shahidehpour; Farrokh Aminifar; Ahmed AlAbdulwahab; Yusuf Al-Turki; Networked Microgrids for Enhancing the Power System Resilience. Proceedings of the IEEE 2017, 105, 1289-1310, 10.1109/jproc.2017.2685558.
  28. Yezhou Wang; Chen Chen; Jianhui Wang; Ross Baldick; Research on Resilience of Power Systems Under Natural DisastersA Review. IEEE Transactions on Power Systems 2015, 31, 1-10, 10.1109/tpwrs.2015.2429656.
  29. Qiang Xie; Ruiyuan Zhu; Earth, Wind, and Ice. IEEE Power and Energy Magazine 2011, 9, 28-36, 10.1109/MPE.2010.939947.
  30. Xu, Y.; Liu, C.C.; Schneider, K.P.; Ton, D.T. Toward a resilient distribution system. In Proceedings of the IEEE Power and Energy Society General Meeting, Denver, CO, USA, 26–30 July 2015; Volume 2015, pp. 1–5.
  31. P. Hines; K. Balasubramaniam; E.C. Sanchez; Cascading failures in power grids. IEEE Potentials 2009, 28, 24-30, 10.1109/mpot.2009.933498.
  32. Reza Arghandeh; Alexandra Von Meier; Laura Mehrmanesh; Lamine Mili; On the definition of cyber-physical resilience in power systems. Renewable and Sustainable Energy Reviews 2016, 58, 1060-1069, 10.1016/j.rser.2015.12.193.
  33. Weilin Li; Xiaobin Zhang; Simulation of the smart grid communications: Challenges, techniques, and future trends. Computers & Electrical Engineering 2014, 40, 270-288, 10.1016/j.compeleceng.2013.11.022.
  34. Baldick, R.; Chowdhury, B.; Dobson, I.; Dong, Z.; Gou, B.; Hawkins, D.; Huang, H.; Joung, M.; Kirschen, D.; Li, F.; 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. In Proceedings of the 2008 IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, PA, USA, 20–24 July 2008; pp. 1–8.
  35. G. Andersson; P. Donalek; R. Farmer; N. Hatziargyriou; I. Kamwa; P. Kundur; N. Martins; J. Paserba; P. Pourbeik; J. Sanchez-Gasca; et al. Causes of the 2003 Major Grid Blackouts in North America and Europe, and Recommended Means to Improve System Dynamic Performance. IEEE Transactions on Power Systems 2005, 20, 1922-1928, 10.1109/tpwrs.2005.857942.
  36. Kaitovic, I.; Lukovic, S.; Malek, M. Proactive failure management in smart grids for improved resilience: A methodology for failure prediction and mitigation. In Proceedings of the 2015 IEEE Globecom Workshops, GC Wkshps 2015-Proceedings, San Diego, CA, USA, 6–10 December 2015; pp. 1–6.
  37. Vaiman; Keith Bell; Chen; Chowdhury; Ian Dobson; Hines; Papic; Miller; Zhang; Risk Assessment of Cascading Outages: Methodologies and Challenges. IEEE Transactions on Power Systems 2011, 27, 631-641, 10.1109/TPWRS.2011.2177868.
  38. Ilhami Colak; Seref Sagiroglu; Gianluca Fulli; Mehmet Yesilbudak; Catalin-Felix Covrig; A survey on the critical issues in smart grid technologies. Renewable and Sustainable Energy Reviews 2016, 54, 396-405, 10.1016/j.rser.2015.10.036.
  39. Xi Fang; Satyajayant Misra; Guoliang Xue; Dejun Yang; Smart Grid — The New and Improved Power Grid: A Survey. IEEE Communications Surveys & Tutorials 2011, 14, 944-980, 10.1109/SURV.2011.101911.00087.
  40. Diman Zad Tootaghaj; Novella Bartolini; Hana Khamfroush; Ting He; Nilanjan Ray Chaudhuri; Thomas La Porta; Tom La Porta; Mitigation and Recovery From Cascading Failures in Interdependent Networks Under Uncertainty. IEEE Transactions on Control of Network Systems 2019, 6, 501-514, 10.1109/tcns.2018.2843168.
  41. Wenye Wang; Zhuo Lü; Cyber security in the Smart Grid: Survey and challenges. Computer Networks 2013, 57, 1344-1371, 10.1016/j.comnet.2012.12.017.
  42. Giuliano Andrea Pagani; Marco Aiello; The Power Grid as a complex network: A survey. Physica A: Statistical Mechanics and its Applications 2013, 392, 2688-2700, 10.1016/j.physa.2013.01.023.
  43. Pietro Danzi; Marko Angjelichinoski; Cedomir Stefanovic; Tomislav Dragicevic; Petar Popovski; Software-Defined Microgrid Control for Resilience Against Cyber Attacks. IEEE Trans. 2018, 10, 5258–5268, 10.1109/TSG.2018.2879727.
  44. Beth-Anne Schuelke-Leech; Betsy Barry; Matteo Muratori; B.J. Yurkovich; Big Data issues and opportunities for electric utilities. Renewable and Sustainable Energy Reviews 2015, 52, 937-947, 10.1016/j.rser.2015.07.128.
  45. Melike Erol-Kantarci; H. T. Mouftah; Smart grid forensic science: applications, challenges, and open issues. IEEE Communications Magazine 2013, 51, 68-74, 10.1109/MCOM.2013.6400441.
  46. Jing Liu; Yang Xiao; Shuhui Li; Wei Liang; C. L. Philip Chen; Cyber Security and Privacy Issues in Smart Grids. IEEE Communications Surveys & Tutorials 2012, 14, 981-997, 10.1109/SURV.2011.122111.00145.
  47. Kebina Manandhar; Xiaojun Cao; Fei Hu; Yao Liu; Detection of Faults and Attacks Including False Data Injection Attack in Smart Grid Using Kalman Filter. IEEE Transactions on Control of Network Systems 2014, 1, 370-379, 10.1109/tcns.2014.2357531.
  48. Yihai Zhu; Jun Yan; Yufei Tang; Yan Lindsay Sun; Haibo He; Resilience Analysis of Power Grids Under the Sequential Attack. IEEE Transactions on Information Forensics and Security 2014, 9, 2340-2354, 10.1109/tifs.2014.2363786.
  49. Oliver Kosut; Liyan Jia; Robert J. Thomas; Lang Tong; Malicious Data Attacks on the Smart Grid. IEEE Transactions on Smart Grid 2011, 2, 645-658, 10.1109/TSG.2011.2163807.
  50. Smith, M.A.; Shneiderman, B.; Milic-Frayling, N.; Mendes Rodrigues, E.; Barash, V.; Dunne, C.; Capone, T.; Perer, A.; Gleave, E. Analyzing (social media) networks with NodeXL. In Proceedings of the Fourth International Conference on Communities and Technologies-C&T ’09, State College, PA, USA, 25–27 June 2009; ACM Press: New York, NY, USA, 2009; p. 255.
  51. Himelboim, I.; Smith, M.A. NodeXL.. The International Encyclopedia of Communication Research Methods; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2017; pp. 1–3.
  52. Mathieu Jacomy; Tommaso Venturini; Sebastien Heymann; Mathieu Bastian; ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software. PLOS ONE 2014, 9, e98679, 10.1371/journal.pone.0098679.
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