Differential search algorithm in multi machine power system stabilizers for damping oscillations

Power system oscillations, a major problem in power system, is suppressed employing power system stabilizers (PSSs). Proper optimization of PSSs is a complex design problem. In this paper, a bio-inspired metaheuristic optimization technique named as differential search algorithm (DSA) is presented to solve the optimization problem of multi machine PSSs. The optimization of PSSs is converted as a cost function then DSA is applied to tune the optimal parameters for PSSs by minimizing the cost function. PSSs are optimized in order to achieve adequate damping for local and inter-area modes of growing oscillations in a multi machine power system. Simulations are conducted in linear and non-linear models of power system to verify the robustness of proposed algorithm. A comprehensive investigation is conducted to compare the performance of DSA based PSSs with the tuned PSSs using bacterial foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) in terms of convergence, improvements of electromechanical modes and system damping over oscillations. The obtained results show that the presented DSA technique is efficient for PSS optimization for the safety of multi machine power system.

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