Model Power System Stabilizer Berbasis Neuro-Fuzzy Adaptif - Agus Jamal , Ramadoni Syahputra (Universitas Muhammadiyah Yogyakarta, 2011)
Low frequency oscillations are detrimental to the goals of maximum power transfer and optimal power system security. A contemporary solution to this problem is the addition of power system stabilizers (PSS) to the automatic voltage regulators on the generators in the power system. For large scale power systems comprising of many interconnected machines, the PSS parameter tuning is a complex exercise due to the presence of several poorly damped modes of oscillation. The problem is further being complicated by continuous variation in power system operating conditions. This research proposes the PSS model based on adaptive neuro-fuzzy for designing robust power system stabilizers for a multi machine system. Simulations were carried out using several fault tests at transmission line on a Two-Area Multimachine Power System. Simulation is done by using Matlab-Simulink software. The result shows that power transfer response using the model is more robust than Delta w PSS, especially for single phase to ground fault.