31st International Power System Conference - PSC 2016, Teherán (Irán). 24-26 octubre 2016
Resumen:
Transmission network is one of the most attractive targets for destructive agents due to its widespread, crucial importance for the society and operation conditions close to its static and dynamic limits. In this paper a framework is proposed for Transmission System Reinforcement (TSR) problem to consider vulnerability caused by intentional attacks. The proposed problem considers both economic and vulnerability issues in the objective function. The attacks are modeled by a set of scenarios for different load levels. Weight of each scenario is calculated based on the amount of damage the attacker could put on the transmission system operation. We formulate the TSR problem as a Mixed Integer Nonlinear Programming (MINLP) problem and successfully transform it into an equivalent Mixed Integer Linear Programming (MILP) problem for which efficient solvers are available. As the case study, 24-bus Reliability Test System (RTS) is utilized to illustrate the effectiveness of the proposed framework. Sensitivity of optimal reinforcement decisions on different parameters such as budget, scenario number, and the peak load level is presented and analyzed.
Resumen divulgativo:
La red de transmisión es uno de los objetivos más atractivos para los agentes destructivos debido a su extensión y condiciones de operación cercanas a sus límites estáticos y dinámicos. En este artículo se propone un marco para el problema de refuerzo del sistema de transmisión para considerar la vulnerabilidad causada por ataques intencionales.
Palabras clave: demand seasonality; intentional attacks; mixed integer linear programming; stochastic programming; transmission system reinforcement (TSR); vulnerability
Fecha de publicación: 2016-10-24.
Cita:
H. Nemati, M.A. Latify, G.R. Yousefi, Transmission system reinforcement under intentional attacks considering demand seasonality, 31st International Power System Conference - PSC 2016, Teherán (Irán). 24-26 octubre 2016.
