Coordination PID-PSS Control Based on Ant Colony optimization In Sulselrabar System

Abstract

The stability of a generator has an important function in the continuity of electricity production. A multimachine electric power system has many generators connected. The Sulselrabar system consists of several interconnected power plants. Proper coordination between generating centres can support the performance of the electric power system, especially when disturbances can disrupt system stability. Sudden load changes are one of the electric power system’s disturbances, which can impact the generator’s stability. In generator operation, the controller is assigned to the generator excitation equipment. However, the dynamics of the electric power system continue to evolve, causing the generator excitation equipment to reach its limit when a large disturbance occurs. Control equipment such as PID and Power System Stabilizer (PSS) produce good performance on the system. The use of these controls requires optimal coordination in finding the right parameters and locations. In this study, an approach is proposed in coordinating PID and PSS controllers for multi-engine generators in the Sulselrabar system. The Ant Colony optimization (ACO) algorithm is a smart algorithm that adopts the behavior of ants in finding food sources. ACO is used for precise PID-PSS parameter optimization. A case study was used in Sengkang generators that were subjected to load change disturbances. From the simulation results, it is obtained that the performance of the Sengkang generator is optimal in terms of speed overshoot response and minimum rotor angle. The application of PID-PSS also increases the damping system so that the oscillations generated due to disturbances can be properly attenuated.