Jesús María López-Lezama This email address is being protected from spambots. You need JavaScript enabled to view it.1, Juan Carlos Castro Galeano2 , and Edwin Rivas Trujillo3
1 Grupo de Investigación en Manejo Eficiente de la Energía (GIMEL), Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Antioquia, Calle 67 No 53-108, Medellín, Colombia 2 Grupo de Investigación y Desarrollo en Sistemas Electromecánicos (GridsE), Ingeniería Electromecánica, Universidad Pedagógica y Tecnológica de Colombia (UPTC), Carrera 18 con Calle 22, Facultad Seccional Duitama, Colombia 3 Grupo de Investigación Interferencia Electromagnética (GCEM), Ingeniería Eléctrica, Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Cra 7 No 40B-53, Bogotá, Colombia
The vulnerability assessment of power systems consists on finding the set of most critical assets in order to device strategies to make the system more resilient. The electric grid interdiction problem (EGIP), also known as the terrorist threat problem, addresses this issue by modeling the interaction of a disruptive agent and the system operator. The EGIP is usually modeled as a bilevel programming problem. The disruptive agent is placed in the upper-level optimization problem and aims at maximizing the system damage subject to limited destructive resources. The system operator is placed in the lower-level optimization problem and reacts to the attacks minimizing load shedding by redispatching available generation resources. Traditional approaches to the EGIP consider a simplified version of the network by means of a DC model. This allows some advantages from the standpoint of complexity; nevertheless, the effect of reactive power and voltage magnitudes are neglected in this model. An AC modeling of the network is more accurate but implies higher complexity. This paper presents a comparison of these models applied to the EGIP through an Iterated Local Search metaheuristic. Several tests were performed on a benchmark power system to contrast the performance of both models. Results show that using a DC model provides faster results but also reports conservative solutions that do not fully take into account the actual damage inflicted in the network. This might lead the system operator to underestimate the real vulnerably of the system and not carry out effective corrective or protective actions.
Keywords: Vulnerability; interdiction problem; bilevel programming; iterated local search
References
[1] Pablo H Corredor and Maria E Ruiz. Against all odds. IEEE Power and Energy Magazine, 9(2):59–66, 2011.
[2] Javier Salmeron, Kevin Wood, and Ross Baldick. Analysis of electric grid security under terrorist threat. IEEE Transactions on power systems, 19(2):905–912, 2004.
[3] José M Arroyo and Francisco D Galiana. On the solution of the bilevel programming formulation of the terrorist threat problem. IEEE transactions on Power Systems, 20(2):789–797, 2005.
[4] Alexis L Motto, José M Arroyo, and Francisco D Galiana. A mixed-integer LP procedure for the analysis of electric grid security under disruptive threat. IEEE Transactions on Power Systems, 20(3):1357–1365, 2005.
[5] Javier Salmeron, Kevin Wood, and Ross Baldick. Worstcase interdiction analysis of large-scale electric power grids. IEEE Transactions on power systems, 24(1):96–104, 2009.
[6] Andrés Delgadillo, José Manuel Arroyo, and Natalia Alguacil. Analysis of electric grid interdiction with line switching. IEEE Transactions on Power Systems, 25(2):633– 641, 2009.
[7] José Manuel Arroyo. Bilevel programming applied to power system vulnerability analysis under multiple contingencies. IET generation, transmission & distribution, 4(2):178–190, 2010.
[8] Yezhou Wang and Ross Baldick. Interdiction analysis of electric grids combining cascading outage and medium-term impacts. IEEE Transactions on Power Systems, 29(5):2160–2168, 2014.
[9] Hadi Nemati, Mohammad Amin Latify, and Gholam Reza Yousefi. Tri-level transmission expansion Journal of Applied Science and Engineering, Vol. 23, No 2, Page 175-183 183 planning under intentional attacks: virtual attacker approach–part I: formulation. IET Generation, Transmission & Distribution, 13(3):390–398, 2018.
[10] Natalia Romero, Ningxiong Xu, Linda K Nozick, Ian Dobson, and Dean Jones. Investment planning for electric power systems under terrorist threat. IEEE Transactions on Power Systems, 27(1):108–116, 2011.
[11] Xuan Wu and Antonio J Conejo. An efficient tri-level optimization model for electric grid defense planning. IEEE Transactions on Power Systems, 32(4):2984–2994, 2016.
[12] Jesús M López-Lezama, Juan Cortina-Gómez, and Nicolás Muñoz-Galeano. Assessment of the electric grid interdiction problem using a nonlinear modeling approach. Electric Power Systems Research, 144:243–254, 2017.
[13] Laura Agudelo, Jesús M López-Lezama, and Nicolás Muñoz. Análisis de vulnerabilidad de sistemas de potencia mediante programación binivel. Información tecnológica, 25(3):103–114, 2014.
[14] Ray Daniel Zimmerman, Carlos Edmundo MurilloSánchez, and Robert John Thomas. MATPOWER: Steady-state operations, planning, and analysis tools for power systems research and education. IEEE Transactions on power systems, 26(1):12–19, 2010.
[15] Cliff Grigg, Peter Wong, Paul Albrecht, Ron Allan, Murty Bhavaraju, Roy Billinton, Quan Chen, Clement Fong, Suheil Haddad, and Sastry Kuruganty. The IEEE reliability test system-1996. A report prepared by the reliability test system task force of the application of probability methods subcommittee. IEEE Transactions on power systems, 14(3):1010–1020, 1999.
We use cookies on this website to personalize content to improve your user experience and analyze our traffic. By using this site you agree to its use of cookies.
