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This paper presents the design and implementation of three-phase four-wire shunt active power filter (SAPF). It consists of insulated gate bipolar transistors, IGBT based current-controlled voltage source inverter (CC-VSI), series coupling inductor and self-supported DC bus. Power electronics based converters and non-linear loads generate waveform-driven power quality issue as harmonics. Three-phase four-wire SAPF mitigates harmonics, compensates for reactive power, neutral current and power factor correction. Conventionally, the positive sequence detection control strategy using phase-locked loop (PLL) is applied as the synchronizing unit vector element to generate reference source currents. Conventional controller tuning process is difficult and fails to perform satisfactorily under supply voltage variation conditions. In this paper, Levenberg-Marquardt back propagation training algorithm based artificial neural network (ANN) controller is proposed to regulate DC link voltage due to its self-adapting and rapid calculation characteristics that allow the controller to handle high nonlinearity and uncertainty in a non-linear system. Weights of a neuron are adapted to minimize total harmonic distortion (THD) of source current under the step, ramp, time series amplitude variation and frequency and amplitude of modulation conditions. The proposed system is modelled in MATLAB/SIMULINK environment and laboratory prototype with dSpace1104 control card is developed. Experimentation results validate the simulated results of the proposed scheme under supply voltage variations for three-phase four-wire distribution system.

Performance Analysis of ANN Based three-phase four-wire Shunt Active Power Filter for Harmonic Mitigation under Distorted Supply Voltage Conditions