Small Signal Stability Analysis of Multi-Machine Power System Using Genetic Algorithm Technique

This paper introduces an innovative approach for determining the dynamic stability margin of a power system. The method employs a Genetic Algorithm (GA) to optimize the parameters of a Conventional Power System Stabilizer (CPSS) linked with the Automatic Voltage Regulator (AVR) in a multi-machine power system. The objective is to tune the stabilizers in a way that effectively shifts the lightly damped and undamped electromechanical modes of all plants to a specified region in the s-plane. To achieve this, a multiobjective problem is formulated, optimizing a composite set of objective functions that include the damping factor of the lightly damped electromechanical modes. The dynamic behavior of the system is assessed using small signal stability analysis, while the stability of the system is evaluated by monitoring the variations of eigenvalues under line-to-ground (LG) fault conditions. The proposed method is then demonstrated on a 3-machine 9-bus system, and the effectiveness and robustness of the suggested Power System Stabilizers (PSSs) are showcased by incorporating them into a conventional AVR-PSS model. This allows the proposed approach to efficiently damp low-frequency oscillations in the power system.