Open AccessPSS AND IPFC POD controllers coordinated tuning by an Adaptive Genetic Algorithm with Hyper-mutation
Author(s) -
Luis Gustavo Cordero Bautista,
Percival Bueno de Araujo
Publication year - 2018
Publication title -
tecnia
Language(s) - English
Resource type - Journals
eISSN - 2309-0413
pISSN - 0375-7765
DOI - 10.21754/tecnia.v28i2.541
Subject(s) - control theory (sociology) , controller (irrigation) , controllability , flexible ac transmission system , electric power system , electric power transmission , genetic algorithm , engineering , transmission system , pid controller , power (physics) , matlab , control engineering , transmission (telecommunications) , computer science , power flow , mathematics , control (management) , temperature control , machine learning , agronomy , physics , electrical engineering , artificial intelligence , biology , operating system , quantum mechanics
Flexible AC transmission systems (FACTS) are a modern technology to increase controllability in power systems. This work presents an analysis of Interline Power Flow Controller (IPFC) which is a FACTS device. This device control and manage power flow in transmission lines. Supplementary damping controller is installed on IPFC Proportional Integral (PI) control. Power Oscillation Damping (POD) and Power System Stabilizers (PSS) contribute to power system stability. This works represents the electric power system and Interline Power Flow Controller FACTS device by a current sensitivity model (CSM). This work focuses on small-signal stability studies using an Adaptive Genetic Algorithm and Hyper-mutation (AGAH) to design simultaneously controller parameters. Adaptive Genetic Algorithm aims to find optimal controller parameters to enhance greatly stability of the power system. This paper considers two areas 14 bus symmetrical system in order to assess proposed algorithm. Simulations are carried out in MatLab platform in order to compare genetic algorithm with proposed algorithm performance. Results show AGAH outweighed AG by time convergence and accuracy.