Damping power systems oscillations using FACTS combinations

The damping of electromechanical modes of oscillation in power systems can be made by static VAR compensator (SVC) and/or power system stabilizer (PSS). The paper presents a combinations of using an SVC, controlled by a nonlinear dynamic controller based adaptive neural network, with a PSS, controlled by variable structure fuzzy logic control. The proposed system is used for both damping low frequency modes of oscillation of the power systems, and enhancing the system dynamic performance at post-fault conditions. The proposed variable structure fuzzy logic controller implements the signals of speed deviation and its rate of change, and internal machine angle deviation and its rate of change. The nonlinear dynamic controller based adaptive neural network implements the speed deviation signal. The proposed scheme is validated using a sample single machine connected to an infinite bus power system through a double transmission line circuit. The studied system is modeled and represented by nonlinear differential equations. Matlab software is used for solving the system equations. The time simulation indicates the superiority of using both SVC and PSS over using either of them alone in the studied power system. The results show that using the FACTS combinations provides very fast damping, with less overshoot, and reduces the amount of reactive compensation required for the SVC, and reduces the exciter gain.