Methodology for identifying near-optimal interdiction strategies for a power transmission system

被引:83
|
作者
Bier, Vicki M. [1 ]
Gratz, Ell R.
Haphuriwat, Naraphorn J.
Magua, Wairimu
Wierzblcki, Kevin R.
机构
[1] Univ Wisconsin, Dept Ind & Syst Engn, Madison, WI 53711 USA
[2] Univ Wisconsin, Dept Elect & Comp Engn, Madison, WI 53711 USA
基金
美国国家科学基金会;
关键词
vulnerability assessment; transmission systems; greedy algorithm; interdiction; hardening;
D O I
10.1016/j.ress.2006.08.007
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Previous methods for assessing the vulnerability of complex systems to intentional attacks or interdiction have either not been adequate to deal with systems in which flow readjusts dynamically (such as electricity transmission systems), or have been complex and computationally difficult. We propose a relatively simple, inexpensive, and practical method ("Max Line") for identifying promising interdiction strategies in such systems. The method is based on a greedy algorithm in which, at each iteration, the transmission line with the highest load is interdicted. We apply this method to sample electrical transmission systems from the Reliability Test System developed by the Institute of Electrical and Electronics Engineers, and compare our method and results with those of other proposed approaches for vulnerability assessment. We also study the effectiveness of protecting those transmission lines identified as promising candidates for interdiction. These comparisons shed light on the relative merits of the various vulnerability assessment methods, as well as providing insights that can help to guide the allocation of scarce resources for defensive investment. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1155 / 1161
页数:7
相关论文
共 50 条
  • [11] ColdBus: A Near-Optimal Power Efficient Optical Bus
    Peter, Eldhose
    Thomas, Arun
    Dhawan, Anuj
    Sarangi, Smruti R.
    2015 IEEE 22ND INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING (HIPC), 2015, : 275 - 284
  • [12] The Power of Convex Relaxation: Near-Optimal Matrix Completion
    Candes, Emmanuel J.
    Tao, Terence
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2010, 56 (05) : 2053 - 2080
  • [13] Optimal and Near-Optimal Policies for Wireless Power Transfer Considering Fairness
    Rezaei, Roohollah
    Movahednasab, Mohammad
    Omidvar, Naeimeh
    Pakravan, Mohammad Reza
    2018 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2018,
  • [14] Near-Optimal Strategies for Nonlinear and Uncertain Networked Control Systems
    Busoniu, Lucian
    Postoyan, Romain
    Daafouz, Jamal
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2016, 61 (08) : 2124 - 2139
  • [15] Study on near-optimal path finding strategies in a road network
    Shi Jun
    Li Jian-yuan
    Cao Han
    Wang Xi-li
    JOURNAL OF ALGORITHMS & COMPUTATIONAL TECHNOLOGY, 2008, 2 (03) : 319 - 333
  • [16] OPTIMAL AND NEAR-OPTIMAL INCENTIVE STRATEGIES IN THE HIERARCHICAL CONTROL OF MARKOV-CHAINS
    SAKSENA, VR
    CRUZ, JB
    AUTOMATICA, 1985, 21 (02) : 181 - 191
  • [17] Near-optimal methodology for in-flight synthesis of trajectory options set
    Dutta P.
    Park S.G.
    Menon P.K.
    Journal of Air Transportation, 2020, 28 (02): : 49 - 64
  • [18] Near-Optimal Decentralized Power Supply Restoration in Smart Grids
    Agrawal, Pritee
    Kumar, Akshat
    Varakantham, Pradeep
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (AAMAS'15), 2015, : 1275 - 1283
  • [19] Adaptive Near-Optimal Compensation in Lossy Polyphase Power Systems
    Lev-Ari, Hanoch
    Hernandez, Ronald D.
    Stankovic, Aleksandar M.
    Marengo, Edwin A.
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2018, 26 (02) : 732 - 739
  • [20] Designing unique words for near-optimal training in block transmission systems
    Coon, Justin P.
    Sandell, Magnus
    EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, 2010, 21 (01): : 13 - 22