AVR and PSS Coordination Strategy by Using Multi-objective Ant Lion Optimizer

In this paper a novel optimization method called Multi-Objective Ant Lion Optimizer (MOALO) is proposed for tuning synchronous generator excitation controls in multi machine power system. Devices used in excitation control are automatic voltage regulator (AVR) and power system stabilizer (PSS). Two area four machine model (TAFM) is used for observing power system dynamics through several various operating states. In a performance analysis of a proposed algorithm two objective functions are used. First objective function uses integral of time weighted absolute error of rotor speed, voltage and tie line active power data, while second objective function uses mean value of time domain transitional process quality indicators such as overshoot, undershoot and settling time. A proposed algorithm is tested and its performance is compared with performances of two other multi objective swarm intelligence algorithms: Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Salp Swarm Algorithm (MOSSA). Results are compared and presented as sets of solutions composed in Pareto fronts.