Load Frequency Controls of Three Are Interconnected Power System with Adaptive Neuro Fuzzy Inference System Approach

Anil Kumar, Obulasetty M-Tech Scholar, Rami Reddy Ch
Now days in industry or any area increasing load is a vast problem for power generation plants due to increase in demand for power. So making balance between generation and demand is the operating principle of load frequency control (LFC). So there is a need of robust control of both systems frequency and tie-line power flows. This thesis presents the design and analysis of Neuro Fuzzy controller based on Adaptive Neuro-Fuzzy inference system (ANFIS) architecture for Load frequency control
more » ... of interconnected areas, to regulate the frequency deviation and tile line power deviations. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This newly developed control strategy combines the advantage of neural networks and fuzzy inference system and has simple structure that is easy to implement. So, In order to keep system performance near its optimum, This ANFIS replaces the original conventional proportional Integral (PI) controller and a fuzzy logic (FL) controller were also utilizes the same area criteria error input. Simulation results are tested in MATLAB/SIMULINK.The performance of the proposed ANFIS based Neuro-Fuzzy controller damps out the frequency deviation and attains the steady state value with less settling time and reduces the overshoot of the different frequency deviations and also reduces the interchanged tie line power compare to the Conventional PI, Fuzzy Controllers.