Optimal Tuning of PID Control on Single Machine Infinite Bus Using Ant Colony Optimization

Sudden changes in the load on the electric power system will cause a dynamic disturbance. This interference causes the generator stability to be disrupted because the generator does not respond to the interference quickly. This causes oscillations in the generator in the form of frequency oscillations and rotor angles. One additional control equipment that can improve the stability of a generator is the Power System Stabilizer (PID). When there is a disturbance oscillation on the generator, the PID provides an additional signal to the excitation equipment to provide additional attenuation to the generator. The use of PID is needed to coordinate the determination of the right parameters to achieve good performance control for the system. In the application, the determination of PID parameters still uses the trial & error method, this method is very difficult to get the right parameters. To solve this problem, here the author uses one of the computational techniques (soft computing) artificial intelligence, namely the Ant Colony Optimization (ACO) algorithm to optimize the tuning of the PID parameters. From the simulation results, the optimal PID parameters obtained are P (Proportional) of 53.4899, I (Integral) of 14.6551, and D (Derivative) of 10.5383. With optimal tuning, the SMIB frequency response is perfect compared to the system without PID trial error control and control, this is indicated by the system response that has improved, where the controller is able to provide stability so that the overshoot oscillation can be muted, and the settling time performance is faster for the system goes to steady-state condition. By tuning the right PID parameters, Overshoot that occurs in this system can be muted that is equal to -0.0002609 up to 0.0001954.