Power System Dynamic Stability Enhancement Using Optimum Design of PSS and Static Phase Shifter Based Stabilizer

Power system stability enhancement via individual and coordinated optimum design of power system stabilizer and static phase shifter based stabilizer is thoroughly investigated in this paper. The coordinated design problem of excitation and static phase shifter-based stabilizer at nominal loading condition over a wide range of uncertainties and system parameter variations is formulated as an optimization problem with an eigenvalue-based objective function. The reinforcement learning automata based optimization algorithm called Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) is employed to search for the optimal setting of the proposed controller parameters. The participation factors method is used to identify the poorly damped electromechanical mode which is used in the evaluation of the eigenvalue-based objective function. This study also presents a singular value decomposition-based approach to assess and measure the controllability of the identified electromechanical mode by different control inputs over a wide range of loading conditions. For evaluation of the effectiveness and the robustness of the proposed stabilizers, a weakly connected power system with different disturbances, loading conditions, and system parameter variations is considered. The nonlinear simulation results and the eigenvalues analysis indicate a high performance of the proposed stabilizers and their ability to provide efficient damping of the low frequency oscillations.