Optimal tuning of power system stabilizers by probability method

It is well known that the power system stabilizer (PSS) which is designed at one operating point cannot guarantee the stabilizing effect of PSS over a wide range of operating conditions. To achieve the PSS with high stabilizing performance against various conditions, this paper focuses on the new parameters optimization of PSS by the probability method. The PSS structure is the practical 2^nd-order lead-lag compensator with the local input signal. The optimal tuning of PSS parameters is carried out under random operating conditions generated by Monte Carlo method so that the probability of the occurrence of desired damping ratio for target oscillation modes are maximized. The particle swarm optimization is used to solve for optimal PSS parameters. Study results in the IEEE-39 bus New England system confirm that the proposed PSS yields better damping effect than the conventional PSS under various operating conditions and severe faults.