Open AccessDesign of Load Frequency Controller for Multi-area System Using AI Techniques
Author(s) -
Suman Machavarapu,
M. Venkateswara Rao,
P.V.R.R. Bhogendra Rao
Publication year - 2020
Publication title -
journal européen des systèmes automatisés/journal européen des systèmes automaitsés
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.16
H-Index - 20
eISSN - 2116-7087
pISSN - 1269-6935
DOI - 10.18280/jesa.530413
Subject(s) - control theory (sociology) , controller (irrigation) , artificial neural network , automatic frequency control , electric power system , frequency deviation , pid controller , fuzzy logic , control engineering , computer science , engineering , power (physics) , control (management) , temperature control , artificial intelligence , telecommunications , physics , quantum mechanics , agronomy , biology
The paper presents an adaptive Load Frequency Controller (LFC) based on a neural network for the interconnected multi-area systems. When there is an imbalance between active power generation and demand there will deviation in the frequency from the reference value. Major disturbances that lead to the variation in frequency beyond the allowable limits are variation in load demand and faults, etc. Initially PID based LFC which is a conventional controller is used to bring back the variations in frequency when there is a disturbance. But these conventional controllers will operate certain operating points only, very slow and, are less efficient for nonlinear systems. To avoid the flaws in the conventional controller the artificial intelligent controllers such as neural network and fuzzy logic controllers are designed. The three, two area, and single area systems are considered as the test systems. The response of all the test systems is observed without and with PI, fuzzy, and neural network controllers. It was observed that the neural network controller is outperforming in damping the variation in the frequency due to the disturbances.