<div>Current harmonics are one of the major causes for grid pollution. Shunt active power filters (SAPFs) are employed for harmonic current compensation. Separation of fundamental and harmonic currents is essential for the control of APF.</div><div>Artificial neural networks (ANN) are an attractive option for the extraction of fundamental current components. The use of power converters such as rectifiers and ac voltage controllers often result in discontinuity in the current. In three phase systems, the discontinuity does not impact the ANN based extraction as three current quantities are available as input to the ANN. However, in a single phase system, extraction cannot be carried out in case of a discontinuity in the waveform. For a single phase system, this paper proposes ANN based fundamental active current extraction with single phase to three phase transformation. ANN separates the fundamental active and harmonic components with the help of the 3-phase currents obtained through the transformation. Thus, extracted fundamental active component is used for controlling the SAPF to ensure total current harmonic distortion within the 5% limit. The performance of the proposed extraction scheme is evaluated for loads and the proposed extraction technique is compared with the other techniques for</div><div>the purpose of validation.</div>

ANN Based Fundamental Current Extraction Scheme for Single Phase Shunt Active Filtering

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