Analysing the Performance of Distributed Generation System Based on Renewable Energy through ANN-Tuned UPQC

Abstract

This article presents an advanced approach to enhancing power quality in a three-phase, low-voltage network that is integrated with a hybrid renewable energy system. This system utilizes an Artificial Neural Network (ANN)-based Unified Power Quality Conditioner (UPQC). A thorough performance analysis was carried out on this system, which harnesses energy from solar photovoltaic (PV) and wind sources and is regulated by an ANN-controlled UPQC. This novel ANN controller aims to exceed the capabilities of the conventional proportional-integral (PI) controller, and particularly the proportional-integral-derivative (PID) controller, by improving both the steady-state and dynamic performance. The system, referred to as UPQC-ANN-RE, directs energy from wind turbines and photovoltaic arrays into a 3-phase, 4-wire electrical distribution network. In its role as a UPQC, it significantly enhances key power quality metrics such as voltage and current harmonics and power factor. A detailed examination of the active-real power flow through the converters provides further insights into the operational dynamics of the system.