Utilization of Adaptive Neuro Fuzzy Inference System Integrated Unified Power Quality Conditioner for Enhancement of Power Quality in Distribution System

The growing use of nonlinear electronic loads has created significant challenges for utilities and end-users alike when it comes to maintaining power quality. As a result, there is a growing focus on improving the quality of the electricity supply, with custom power devices being used to safeguard sensitive loads and enhance the quality and reliability of the power supply. One such custom power device is the Unified Power Quality Conditioner (UPQC), which has become widely used for mitigating power quality issues. ANFIS is a powerful tool for modelling and analysing complex systems, and its application to the UPQC is expected to yield valuable insights into the device's performance in mitigating power quality issues. In this paper, the UPQC is modelled and analysed using the Adaptive Neuro-Fuzzy Inference Method (ANFIS) to improve the power quality of a 16-bus distribution system. The consequence of this analysis will become a milestone for comparing different power quality improvement techniques and identifying the most effective strategies for enhancing power quality in distribution systems. All the performance analysis has been carried out on the MA TLAB/Simulink platform.