The article focuses towards the development of an optimal secondary controller which could adapt with the varying system conditions to maintain the frequency and tie-line power flow variations within the nominal value. 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 via parallel AC-DC links. 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. On subjection to different load variations at different intervals of time, ANFIS tuned PI controller has retained the frequency and tie-line power variations for a robust multi source multi area system interconnected via parallel AC-DC links in a much faster way to its nominal values than other methods. The performance of the controller is evaluated based on performance indices.
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Dr. Vijaya Chandrakala K. R. M. and Dr. Balamurugan S., “Adaptive neuro-fuzzy scheduled load frequency controller for multi source multi area system interconnected via parallel ac-dc links”, International Journal on Electrical Engineering and Informatics, vol. 10, no. 3, pp. 479-490, 2018.