Enhancing Power Oscillation Control: Comparative Analysis of Damping Controllers and Hybrid Computational Intelligence Methods for Power System Stabilization

In this paper, Artificial ecosystem optimization (AEO) and Ant bee colony (ABC) optimization were used to design damping controllers for power oscillation damping and control. The damping controllers designed are power system stabilizer (PSS), proportional integral derivative-PSS (PID-PSS), fractional order (FO) PID-PSS (FOPID-PSS), tilt integral derivative-PSS(TID-PSS), all designed using the AEO optimization and Neurofuzzy controller (NFC) designed using the ABC optimization. The damping controllers were validated on the IEEE New England power test system which is a ten-machine system. A comparison of results obtained was done based on the settling time of the rotor angle and rotor speed control of the synchronous generators (machines) in the ten-machine power test system. PID-PSS, FOPID-PSS and TID-PSS showed improved rotor angle and rotor speed control in comparison to the PSS damping controller only. NFC however, indicates a better control of the rotor angle and rotor speed than all other controllers designed.