K.R.M. Vijaya Chandrakala, S. Balamurugan



Adaptive Neuro-Fuzzy Scheduled Load Frequency Controller for Multi Source Multi Area System Interconnected via Asynchronous Tie-line

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The article focuses towards the development of an optimal secondary controller which could adapt with the varying system conditions. For the analysis, a two area multi source system consisting of thermal, hydro and nuclear system in one area is interconnected with another area comprising of thermal and hydro system. On subjection to unit step load change in demand, the impact on frequency and tie-line power flow variations in multi source multi area is observed under MATLAB / Simulink environment. The fine tuning of frequency and tie-line power flow variations is achieved with the help of secondary controller. Optimal secondary Proportional Integral (PI) controller is chosen based on Zeigler Nichols’ (ZN), Genetic Algorithm (GA), Fuzzy Gain Scheduling (FGS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) tuning techniques. The performance of the controller is evaluated based on performance indices.


Load Frequency Control (LFC), Zeigler Nichols’ (ZN) Method, Genetic Algorithm (GA) Technique, Adaptive Neuro-Fuzzy Gain Scheduling (ANFIS) Technique, Integral Squared Error (ISE)


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Cite this paper

K.R.M. Vijaya Chandrakala, S. Balamurugan. (2017) Adaptive Neuro-Fuzzy Scheduled Load Frequency Controller for Multi Source Multi Area System Interconnected via Asynchronous Tie-line. International Journal of Control Systems and Robotics, 2, 178-186


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