Performance Analysis of Artificial Intelligence Controller for PV and Battery Connected UPQC

Abstract

Nowadays, integration of the non-conventional energy sources like wind, tidal, solar etc into the grid is suggested in order to minimize the losses in the distribution network and to meet the demand. The arrival of the power electronics equipments to control the nonlinear loads has made an impact on the power quality. The unified power quality conditioner (UPQC) is a FACTS device with the back to back converters, coupled together with a DC-Link capacitor. This paper suggests an intelligent hybrid controller for the solar Photo-voltaic system and Battery storage system integrated UPQC. The proposed controller adapts both the qualities of artificial neural network and Integral sliding-mode controller. The synchronization of phases is created by self tuning filter (STF) in association with unit vector generation method (STF-UVGM) for the superior performance of UPQC during the unbalanced/ distorted supply voltages conditions. Therefore, the necessity of Phase-locked-loop, Low pass filters and High pass filters are eliminated. However, STF is used for separating the Harmonic and Fundamental components. In addition, STF-UVGM was used for generation of synchronization phases of series and shunt filters. The prime objectives of the suggested artificial neural network integral sliding mode hybrid controller (ANNISMHC) are fast action to retain the DC-Link voltage to the constant value during load/ irradiation variations, diminish the harmonics in the current waveforms, power-factor enhancement, maximum mitigation of sag, swell and disturbances in supply voltage, and compensation for the unbalanced supply voltages. The working of suggested ANNISMHC was investigated on five test cases for several combinations of loads, and balanced/unbalanced supply voltages. However, to demonstrate supremacy of the suggested ANNISMHC comparative study with the different controllers those are available in literature and also with the standard controllers like PIC, SMC, and FLC. The ANNISMHC shows an extra-ordinary performance in diminishing THD thereby improving PF and reducing voltage distortions.