An Electrical Power System Reconfiguration Model Based on Optimal Transmission Switching under Scenarios of Intentional Attacks

Juan Toctaquiza (), Diego Carrión and Manuel Jaramillo
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Juan Toctaquiza: Master’s Program in Electricity, Salesian Polytechnic University, Quito EC170702, Ecuador
Diego Carrión: Master’s Program in Electricity, Salesian Polytechnic University, Quito EC170702, Ecuador
Manuel Jaramillo: Smart Grid Research Group—GIREI (Spanish Acronym), Salesian Polytechnic University, Quito EC170702, Ecuador

Energies, 2023, vol. 16, issue 6, 1-17

Abstract: Currently, operating electrical power systems (EPS) is a complex task that relies on the experience of the operators or the strength of algorithms developed for autonomous operation. The continuous operation of EPS is vulnerable to intentional cybernetic and physical attacks. With the most significant extension and distribution in the EPS, the transmission lines are most exposed to potential attacks. Before this, the entire behavior of the EPS changes, and, on occasions, a blackout can even be generated. The present investigation focused on developing a methodology for reconfiguring the power system against intentional attacks, considering the topology change through optimal switching of transmission lines (OTS) based on optimal DC flows and quantifying the contingency index, which allows for the identification of the weaknesses of the EPS. The methodology was applied to the IEEE 30−bus system, and contingencies were randomly generated, as is typical with intentional attacks. The study successfully identified the reconfiguration strategy of EPS based on OTS-DC, mitigating potential problems such as line loadability and voltage angle deviation in the nodes.

Keywords: contingency analysis; optimal power flow; power electrical network security; intentional attacks in transmission system; optimal transmission switching (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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