A multi-objective stochastic tri-level programming for highlighting the role of the pumped-storage power plant on electric grid defense budget

This paper attempted to highlight the impact of a pumped-storage hydro plant on the electricity grid defense budget, which is spent to increase the power system resilience against terrorist attacks. A stochastic tri-level programming approach known as the defender-attacker-defender technique was applied to detect the defense plan by considering the pumped-storage hydro plant. The stochastic parameter was related to the water volume of the upper reservoir during the disruptive attack. In the stochastic tri-level programming model, the upper level was formulated to identify the components that should be defended for mitigating the system vulnerability against disruptive agent attacks. A terrorist agent seeks to find a set of components for maximizing power system damage. Therefore, the middle level was used to model the disruptive behavior. Finally, the lower level modeled the system operator behavior during the attack. The system operator generally applied flexible sources such as storage to reduce the effects of the attack. Thus, the role of the pump-storage hydro plant was evident at this level. The proposed tri-level problem was solved by transforming it into an equivalent bi-level program, which was solved by using an enumeration algorithm. Simulation results illustrate the effectiveness of the pump-storage hydro plant in reducing the power system defender budget