Optimal Coordination PID-PSS Control Based on Craziness Particle Swarm Optimization In Sulselrabar System

The combination of a Power System Stabilizer (PSS) and PID control in a multiengine system provides additional control action on the excitation side of the generator. Optimal coordination is required to use the two controllers. The Sulselrabar system is a complex system that connects large load centers. A study is needed regarding generator stability to support system performance. This study proposes an artificial intelligence optimization method based on Craziness Particle Swarm Optimization (CRPSO) to optimize the PID-PSS parameters. CRPSO is a refinement of the premature convergence of the conventional PSO method. The optimal PID-PSS parameter results in optimal generator excitation performance. The combination of PID-PSS and excitation reduces the oscillations in the system. From the analysis, results obtained optimal performance compared to other control schemes in terms of the excitation output response that gives a maximum signal. The speed response produces a minimum overshoot of −0.01187 & 0.00019pu. Besides that, it is also viewed from the increase in eigenvalues and the maximum damping system, 0.601826596. This increase results in optimal system performance, faster system heading to a steady state and faster settling time.