Comparison of ANFIS Controller with ANN Controller for Power Quality Enhancement

Comparison of ANFIS Controller with ANN Controller for Power Quality Enhancement

R Lakshmi1, N Ramesh Raju2, S Ramesh3, K Gunaprasad4, V Supriya5

1Associate Professor, Department of EEE, Siddharth Institute of Engineering and Technology, Puttur, Andhra Pradesh, India.

2Professor & Head, Department of EEE, Siddharth Institute of Engineering and Technology, Puttur, Andhra Pradesh, India.

3Professor, Department of EEE, Siddharth Institute of Engineering and Technology, Puttur,

Andhra Pradesh, India.

4Professor, Department of EEE, Siddharth Institute of Engineering and Technology, Puttur,

Andhra Pradesh, India

5Assistant Professor, Department of EEE, Siddharth Institute of Engineering and Technology, Puttur,Andhra Pradesh, India

ABSTRACT

This work presents an analysis of an adaptive Neuro-fuzzy inference system (ANFIS) based shunt hybrid active filter (SHAF) for power quality enhancement in electrical power systems. The proposed SHAF integrates a passive filter with a shunt active filter and utilizes ANFIS for real-time harmonic identification and suppression. The simulation results of the ANFIS-based control are discussed in detail, above controller mitigating harmonic distortion, improving power factor, and enhancing voltage regulation. The analysis of the proposed system is performed under various operating conditions, and its performance is compared with other conventional methods. The results indicate that the proposed ANFIS-based SHAF provides superior performance in terms of efficiency, accuracy, and robustness for power quality enhancement in electrical power systems. By using Matlab/Simulink software.

Keywords: Harmonic analysis, neural networks, power harmonic filters, power system analysis computing, total harmonic distortion.