Open AccessModel Power System Stabilizer Berbasis Neuro-Fuzzy Adaptif
Author(s) -
Agus Jamal,
Ramadoni Syahputra
Publication year - 2015
Publication title -
semesta teknika
Language(s) - English
Resource type - Journals
eISSN - 2502-5481
pISSN - 1411-061X
DOI - 10.18196/st.v14i2.543
Subject(s) - electric power system , control theory (sociology) , fault (geology) , matlab , power (physics) , computer science , maximum power transfer theorem , control engineering , power transmission , engineering , artificial intelligence , physics , control (management) , quantum mechanics , seismology , geology , operating system
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.