Convolutional Neural Network-based harmonic mitigation technique for an adaptive shunt active power filter

Owing to the use of nonlinear loads in distribution side, there are power quality issues such as voltage swell/sag, harmonics, flickers, imbalance, and outage. The harmonics system affect hence a suitable methodology is vital mitigate compensation reactive power. In this paper, CNN (Convolutional Neural Network)-based harmonic mitigation performed. A 5-level cascaded H-bridge inverter employed shunt active filter which reference current generated by SRF theory, incorporating for extraction. DC-link potential across capacitor retained means ANN (Artificial Network) controller whose behaviour compared with proportional well FLC. gating pulse PWM generator incorporated Hysteresis Current Controller (HCC). By control strategy, get mitigated; subsequently, achieved unity factor. implementing five-level inverter, THD settling time minimized. performance analysed using MATLAB load hardware implemented FPGA Spartan 6E. 0.93% accomplished simulation 1.4% execution.