Robust Evolutionary Technique Based On Gravitational Search Algorithm for Dynamically Tuning Controller Parameters of SVC for Transient Stability Enhancement

Abstract

With the advent of modernization, the demand for electricity is increasing exponentially. Low frequency electromechanical oscillations have posed a major challenge to the power transfer capabilities and stability of modern power system. For the effective mitigation of these electromechanical oscillations, a coordinated design of Power System Stabilizer (PSS) and Static Var Compensator (SVC) is proposed for a two machine system, with the application of a novel optimization technique called Gravitational Search Algorithm (GSA).PSS helps in the effective damping of electromechanical oscillations and enhancement of transient stability. However, at times only use of PSS in long transmission lines is not enough. FACTS devices is a recent technology that is being used extensively to improve controllability in power flow. Unified use of PSS along with a unique Flexible AC Transmission System (FACTS) device named SVC can result in improvement in reliability, controllability and reduction of power system oscillations thus further improving the system stability. Furthermore the PID controller of PSS is tuned dynamically using a global search technique called Gravitational Search Algorithm (GSA) for the system to respond effectively to non linearities present in power system. The results show the robustness and the flexibility of the new GSA based PID controller over a wide range of faults by effectively reducing oscillations. The system stability is improved to a great extent in terms of rise time, settling time and peak overshoot. Furthermore the GSA optimized PID controller gives much minimized THD as compared to conventional PID. For the justification and validation of the GSA technique in attaining enhanced stability, the two machine system is introduced with single phase triple L-G fault. The conventional PID based PSS simulation results are compared with GSA optimized PID based PSS simulation results using MATLAB.