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Integrity Attacks on Real-Time Pricing in Electric Power Grids

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Published:23 July 2015Publication History
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Abstract

Modern information and communication technologies used by electric power grids are subject to cyber-security threats. This article studies the impact of integrity attacks on real-time pricing (RTP), an emerging feature of advanced power grids that can improve system efficiency. Recent studies have shown that RTP creates a closed loop formed by the mutually dependent real-time price signals and price-taking demand. Such a closed loop can be exploited by an adversary whose objective is to destabilize the pricing system. Specifically, small malicious modifications to the price signals can be iteratively amplified by the closed loop, causing highly volatile prices, fluctuating power demand, and increased system operating cost. This article adopts a control-theoretic approach to deriving the fundamental conditions of RTP stability under basic demand, supply, and RTP models that characterize the essential behaviors of consumers, suppliers, and system operators, as well as two broad classes of integrity attacks, namely, the scaling and delay attacks. We show that, under an approximated linear time-invariant formulation, the RTP system is at risk of being destabilized only if the adversary can compromise the price signals advertised to consumers, by either reducing their values in the scaling attack or providing old prices to over half of all consumers in the delay attack. The results provide useful guidelines for system operators to analyze the impact of various attack parameters on system stability so that they may take adequate measures to secure RTP systems.

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References

  1. Hunt Allcott. 2009. Real Time Pricing and Electricity Markets. Retrieved from http://economics.stanford.edu/files/Allcott3_13.pdf.Google ScholarGoogle Scholar
  2. Fernando Alvarado. 1999. The stability of power system markets. IEEE Transactions on Power Systems 14, 2 (1999), 505--511.Google ScholarGoogle ScholarCross RefCross Ref
  3. Ameren. 2014. Real-Time Pricing for Residential Customers. Retrieved from http://www.ameren.com/sites/aiu/ElectricChoice/Pages/ResRealTimePricing.aspx.Google ScholarGoogle Scholar
  4. Saurabh Amin, Xavier Litrico, Shankar Sastry, and Alexandre M. Bayen. 2013. Cyber security of water SCADA systems-Part I: Analysis and experimentation of stealthy deception attacks. IEEE Transactions on Control Systems Technology 21, 5 (2013), 1963--1970.Google ScholarGoogle ScholarCross RefCross Ref
  5. Australian Energy Market Operator. 2011. 2011 National Electricity Forecasting. Retrieved from. http://www.aemo.com.au/∼/media/Files/Other/forecasting/0400-0053%20pdf.pdf.Google ScholarGoogle Scholar
  6. Austrilian Energy Market Operator. 2014. Homepage. Retrieved from http://www.aemo.com.au.Google ScholarGoogle Scholar
  7. Galen Barbose, Charles Goldman, Ranjit Bharvirkar, Nicole Hopper, Michael Ting, and Bernie Neenan. 2005. Real Time Pricing as a Default or Optional Service for C&I Customers: A Comparative Analysis of Eight Case Studies. Technical Report. Lawrence Berkeley National Laboratory.Google ScholarGoogle Scholar
  8. Alvaro A. Cárdenas, Saurabh Amin, Zong-Syun Lin, Yu-Lun Huang, Chi-Yen Huang, and Shankar Sastry. 2011. Attacks against process control systems: Risk assessment, detection, and response. In 6th ACM Symposium on Information, Computer and Communications Security (ASIACCS). ACM, 355--366. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Alvaro A. Cárdenas, Saurabh Amin, and Shankar Sastry. 2008. Secure control: Towards survivable cyber-physical systems. In 28th International Conference on Distributed Computing Systems Workshops. IEEE, 495--500. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Joon Young Choi, Seong-Hwang Rim, and Jong-Keun Park. 1998. Optimal real time pricing of real and reactive powers. IEEE Transactions on Power Systems 13, 4 (1998), 1226--1231.Google ScholarGoogle ScholarCross RefCross Ref
  11. ComEd. 2014. ComEd Residential Real-Time Pricing Program. Retrieved from https://rrtp.comed.com/.Google ScholarGoogle Scholar
  12. Ozgur Dalkilic, Atilla Eryilmaz, and Xiaojun Lin. 2013. Stable real-time pricing and scheduling for serving opportunistic users with deferrable loads. In 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 1200--1207.Google ScholarGoogle ScholarCross RefCross Ref
  13. Mike Davis. 2009. Recoverable Advanced Metering Infrastructure. (2009). Black Hat Technical Security Conference, Las Vegas, Nevada.Google ScholarGoogle Scholar
  14. Emeka Eyisi and Xenofon Koutsoukos. 2014. Energy-based attack detection in networked control systems. In The 3rd International Conference on High Confidence Networked Systems (HiCoNS). ACM, ACM, 115--124. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Massimo Filippini. 2011. Short- and long-run time-of-use price elasticities in swiss residential electricity demand. Energy Policy 39, 10 (2011), 5811--5817.Google ScholarGoogle ScholarCross RefCross Ref
  16. Stein-Erik Fleten and Erling Pettersen. 2005. Constructing bidding curves for a price-taking retailer in the norwegian electricity market. IEEE Transactions on Power Systems 20, 2 (2005), 701--708.Google ScholarGoogle ScholarCross RefCross Ref
  17. Georgia Power. 2014. RTP-HA-2 Program. (2014). http://www.georgiapower.com.Google ScholarGoogle Scholar
  18. John J. Grainger and William D. Stevenson. 1994. Power System Analysis. McGraw-Hill, New York.Google ScholarGoogle Scholar
  19. GridLAB-D. 2014. GridLAB-D. Retrieved from http://www.gridlabd.org.Google ScholarGoogle Scholar
  20. Liyan Jia, Robert J. Thomas, and Lang Tong. 2012. Impacts of malicious data on real-time price of electricity market operations. In 45th Hawaii International Conference on System Sciences (HICSS). IEEE, 1907--1914. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Oliver Kosut, Liyan Jia, Robert J. Thomas, and Lang Tong. 2011. Malicious data attacks on the smart grid. IEEE Transactions on Smart Grid 2, 4 (2011), 645--658.Google ScholarGoogle ScholarCross RefCross Ref
  22. Fangxing Li and Rui Bo. 2007. DCOPF-based LMP simulation: Algorithm, comparison with ACOPF, and sensitivity. IEEE Transactions on Power Systems 22, 4 (2007), 1475--1485.Google ScholarGoogle ScholarCross RefCross Ref
  23. Na Li, Lijun Chen, and Steven H. Low. 2011. Optimal demand response based on utility maximization in power networks. In IEEE Power and Energy Society General Meeting. IEEE, 1--8.Google ScholarGoogle Scholar
  24. Mark G. Lijesen. 2007. The real-time price elasticity of electricity. Energy Economics 29, 2 (2007), 249--258.Google ScholarGoogle ScholarCross RefCross Ref
  25. Jie Lin, Wei Yu, Xinyu Yang, Guobin Xu, and Wei Zhao. 2012. On false data injection attacks against distributed energy routing in smart grid. In 3rd International Conference on Cyber-Physical Systems (ICCPS). ACM, 183--192. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Yao Liu, Peng Ning, and Michael K. Reiter. 2011. False data injection attacks against state estimation in electric power grids. ACM Transactions on Information and System Security 14, 1 (2011), 13:1--13:33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Stephen McLaughlin, Dmitry Podkuiko, Sergei Miadzvezhanka, Adam Delozier, and Patrick McDaniel. 2010. Multi-vendor penetration testing in the advanced metering infrastructure. In Annual Computer Security Applications Conference (ACSAC 26). ACM, 107--116. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Tyler Nighswander, Brent Ledvina, Jonathan Diamond, Robert Brumley, and David Brumley. 2012. GPS software attacks. In 19th ACM Conference on Computer and Communications Security (CCS). ACM, 450--461. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Katsuhiko Ogata. 1995. Discrete-Time Control Systems (2nd ed.). Prentice-Hall, Englewood Cliffs, NJ. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Oracle. 2012. Multiple Vulnerabilities in NTP. Retrieved from https://blogs.oracle.com/sunsecurity/entry/multiple_vulnerabilities_in_network_time.Google ScholarGoogle Scholar
  31. PJM. 2014. PJM Operational Data. Retrieved from http://www.pjm.com/pub/account/lmpgen/lmppost.html.Google ScholarGoogle Scholar
  32. Public Act 094-0977. 2014. (2014). http://www.ilga.gov/legislation/publicacts/94/PDF/094-0977.pdf.Google ScholarGoogle Scholar
  33. Li Ping Qian, Ying Jun Angela Zhang, Jianwei Huang, and Yuan Wu. 2013. Demand response management via real-time electricity price control in smart grids. IEEE Journal on Selected Areas in Communications 31, 7 (2013), 1268--1280.Google ScholarGoogle ScholarCross RefCross Ref
  34. Mardavij Roozbehani, Munther A. Dahleh, and Sanjoy K. Mitter. 2012a. Volatility of power grids under real-time pricing. IEEE Transactions on Power Systems 27, 4 (2012), 1926--1940.Google ScholarGoogle ScholarCross RefCross Ref
  35. Mardavij Roozbehani, M. Ohannessian, D. Materassi, and M. A. Dahleh. 2012b. Load-Shifting Under Perfect and Partial Information: Models, Robust Policies, and Economic Value. Retrieved from https://dahleh.lids.mit.edu/wp-content/uploads/2012/08/2012-Load-ShiftingUnderPerfectAndPartialInformation.pdf.Google ScholarGoogle Scholar
  36. Ishtiaq Rouf, Hossen Mustafa, Miao Xu, Wenyuan Xu, Rob Miller, and Marco Gruteser. 2012. Neighborhood watch: Security and privacy analysis of automatic meter reading systems. In 19th ACM Conference on Computer and Communications Security (CCS). ACM, 462--473. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Pedram Samadi, A.-H. Mohsenian-Rad, Robert Schober, Vincent W. S. Wong, and Juri Jatskevich. 2010. Optimal real-time pricing algorithm based on utility maximization for smart grid. In 1st IEEE International Conference on Smart Grid Communications (SmartGridComm’10). IEEE, 415--420.Google ScholarGoogle ScholarCross RefCross Ref
  38. Pedram Samadi, Hamed Mohsenian-Rad, Vincent W. S. Wong, and Robert Schober. 2014. Real-time pricing for demand response based on stochastic approximation. IEEE Transactions on Smart Grid 5, 2 (2014), 789--798.Google ScholarGoogle ScholarCross RefCross Ref
  39. Kevin P. Schneider, Yousu Chen, David P. Chassin, Robert Pratt, Dave Engel, and Sandra Thompson. 2008. Modern Grid Initiative Distribution Taxonomy Final Report. Retrieved from http://www.gridlabd.org/models/feeders/taxonomy_of_prototypical_feeders.pdf.Google ScholarGoogle Scholar
  40. Schneider Electric. 2014. Technical Note of ION Smart Meter. Retrieved from http://www.powerlogic.com/literature/ION%20Time%20Synchronization%20and%20Timekeeping.pdf.Google ScholarGoogle Scholar
  41. Shams N. Siddiqi and Martin L. Baughman. 1993. Reliability differentiated real-time pricing of electricity. IEEE Transactions on Power Systems 8, 2 (1993), 548--554.Google ScholarGoogle ScholarCross RefCross Ref
  42. Siddharth Sridhar and Manimaran Govindarasu. 2014. Model-based attack detection and mitigation for automatic generation control. IEEE Transactions on Smart Grid 5, 2 (2014), 580--591.Google ScholarGoogle ScholarCross RefCross Ref
  43. James L. Sweeny. 2002. The California Electricity Crisis. Hoover Institution Press, Stanford, CA.Google ScholarGoogle Scholar
  44. Symantec. 2014. Symantec Security Response. Dragonfly: Cyberespionage Attacks Against Energy Suppliers. Retrieved from http://www.symantec.com/content/en/us/enterprise/media/security_response/whitepapers/Dragonfly_Threat_Against_Western_Energy_Suppliers.pdf.Google ScholarGoogle Scholar
  45. The Wall Street Journal. 2009. Spies Penetrate U.S. Electric Grid. Retrieved from http://www.wsj.com/articles/SB123914805204099085.Google ScholarGoogle Scholar
  46. U.S. Energy Information Administration. 2014. How Much Electricity Is Lost in Transmission and Distribution in U.S.? Retrieved from http://www.eia.gov/tools/faqs/faq.cfm?id=105&t==3.Google ScholarGoogle Scholar
  47. Le Xie, Yilin Mo, and Bruno Sinopoli. 2011. Integrity data attacks in power market operations. IEEE Transactions on Smart Grid 2, 4 (2011), 659--666.Google ScholarGoogle ScholarCross RefCross Ref
  48. Rongshan Yu, Wenxian Yang, and Susanto Rahardja. 2012. A statistical demand-price model with its application in optimal real-time price. IEEE Transactions on Smart Grid 3, 4 (2012), 1734--1742.Google ScholarGoogle ScholarCross RefCross Ref
  49. Yanling Yuan, Zuyi Li, and Kui Ren. 2011. Modeling load redistribution attacks in power systems. IEEE Transactions on Smart Grid 2, 2 (2011), 382--390.Google ScholarGoogle ScholarCross RefCross Ref

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