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Research Article

JCR. 2020; 7(6): 1314-1327


ARTIFICIAL NEURAL NETWORK BASED POWER QUALITY IMPROVEMENT USING SHUNT ACTIVE POWER FILTER

T. Sravanthi, Dr.T. Rajesh, Dr.K. Ezhil Vignesh.

Abstract
Artificial Intelligence methods are the latest developments in power quality enhancement. Fuzzy logic and neural networks also include Artificial Intelligence. This paper deals with the artificial neural network application to power quality improvement. This paper presents a study designed to enhance Total Harmonic Distortion (THD) caused by improper utilization of electronic control (PE) devices as well as nonlinear loads. Shunt Active Power Filter is also one of controller which is used to suppress source currents harmonic currents and to offset the reactive power as it has ability to minimize the harmonic problems that nonlinear loads cause. The P-Q Instant Reactive Power Theory (IRP) is used for the removal of the harmonic component. In DC-link controller and for current error adjustments Artificial Neural Network (ANN) were employed. The hysteresis current controller scheme can be used to generate trigger pulses and to controlling voltage source inverter swapping. Artificial intelligence gives better results when compared to the conventional methods. Continuous and effective electricity supply is required for the operation of modern and advanced society today. Simulations are performed in MATLAB environments using toolbox power system.

Key words: Artificial Neural Networks (ANN), Total Harmonic Distortion (THD), Shunt Active Power Filter (SAPF), Power Quality (PQ).



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