Open AccessArtificial-neural-network based unified power flow controller for mitigation of power oscillations
Author(s) -
Vireshkumar Mathad,
Gururaj Kulkarni
Publication year - 2021
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v24.i3.pp1323-1331
Subject(s) - unified power flow controller , control theory (sociology) , electric power system , controller (irrigation) , flexible ac transmission system , artificial neural network , fault (geology) , pid controller , ac power , engineering , open loop controller , control engineering , power (physics) , computer science , voltage , power flow , electrical engineering , control (management) , physics , closed loop , temperature control , machine learning , seismology , geology , artificial intelligence , biology , quantum mechanics , agronomy
The series and shunt control scheme of unified power flow controller (UPFC) impacts the performance and stability of the power system during power swing. UPFC is the most versatile and voltage source converter device as it can control the real and reactive power of the transmission system simultaneously or selectively. When any system is subjected to any disturbance or fault, there are many challenges in damping power oscillation using conventional methods. This paper presents the neural network-based controller that replaces the proportional-integral (PI) controller to minimize the power oscillations. The performance of the artificial neural network (ANN) controller is evaluated on IEEE 9 bus system and compared with a conventional PI controller.