GWO optimized PV-battery based AI interfaced UPQC system for power quality improvement

The demand for improved Power Quality (PQ) in distributed power systems has raised due to the increase in sensitive irregular load integration and PV system-based power generation. In order to upgrade the entire system with developed PQ, a Unified Power Quality Conditioner (UPQC), a unique power device is proposed in this work. Using a shunt compensator, the PV system delivers active power to the load. Photovoltaic (PV) systems is used for uninterrupted energy flow to the load. The output voltage obtained from PV module is irregular, so that a DC-DC converter is required to step-up/step-down the output. In this paper, Luo converter is used in which the converter operation is regulated using Grey Wolf Optimisation (GWO) based Proportional Integral (PI) controller. PWM generator provides necessary pulses to the converter which in turn provides constant supply to the load. The battery converter is used for charging and discharging of the batteries in both direction for further use. To overcome harmonic distortion observed in the input AC source, an Artificial Neural Network (ANN) aids in the operation of shunt active filter of the UPQC. The proposed ANN controller reduces control complexity and effectively overcomes power quality issues. The AC source output is fed as input to ANN which generates reference current. PWM generator with hysteresis control converts the reference current as PWM pulses received from ANN and supplies to shunt converter of UPQC. Then the DC supply is converted to AC by reducing harmonic distortion using LC filter and it is fed to the load. On the basis of MATLAB simulations, the effectiveness of the proposed PV-UPQC configuration in eliminating load current harmonics and source voltage fluctuations thereby improving PQ is analyzed.