Design of UPQC with Solar PV and Battery Storage Systems for Power Quality Improvement

Abstract

In this paper, the unified PQ conditioner (UPQC) is associated with photovoltaic (PV) and battery-storage systems (BSSs) to address the PQ issues. The hybrid fuzzy-sliding mode control (HFSMC) based maximum-power-point tracking system (MPPTs) is adopted for solar PV system to extract maximum output. To minimize the complexity of the conventional system, levenberg-marquardt trained artificial neural network (ANN) controller is proposed to the UPQC in order to generate the effective reference signals for shunt, series converters which eliminates the necessity of conventional abc, dq0, αβ transformations. The main aim of the proposed ANN based UPQC is to achieve the constant direct current (DC) link capacitor voltage during load changes with low settling time, elimination of imperfections in current waveforms, thereby reducing total harmonic distortions (THD) and to improve power factor, mitigation of sag, swell, disturbances and unbalances in source voltage. The performance of developed method is tested on five case studies with different combination of loads, variable irradiation and source voltages conditions. To demonstrate the supremacy of the developed method the comparative study with the proportional integral controller (PIC) was carried out. The proposed method shows an excellent performance in reducing voltage fluctuations and THD successfully and thereby improving power factor.