Concurrent optimal design of TCSC and PSS using symbiotic organisms search algorithm

The symbiotic organisms search (SOS), which has been recently introduced, is a robust powerful metaheuristic global optimizer. This nature-inspired algorithm imitates the symbiotic interaction strategies in an ecosystem exercised by organisms involved in interrelationships to survive and reproduce. One of the main bene cial features of the SOS in contrast to many other competent metaheuristic algorithms is that the algorithm does not need any speci c algorithm parameters or tuning process. This paper applies the SOS algorithm to simultaneously design optimal controllers of a power system equipped with both a power system stabilizer (PSS) and a thyristor-controlled series compensator (TCSC). The algorithm of SOS is utilized to concurrently tune the variables of controllers for both the PSS and TCSC in the nonlinear optimization process. Simulation results reveal that the optimal SOS-based coordinated controllers can signi cantly stabilize the system and efficiently damp oscillations under severe disturbances. Results will also show that the optimal controllers obtained perform slightly better than the optimal controllers obtained using the two commonly used global optimization solvers, the genetic algorithm (GA) and particle swarm optimization.

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