IoT Enabled Microgrid System for Enhancing Power Quality Using Adaptive Neuro-Fuzzy Control Algorithm

Microgrid systems have emerged because of the rising need for efficient and dependable power supply, as well as the widespread use of internet of things (IoT) technologies. However, nonlinear loads, fluctuations in voltage, and harmonics are often present in these systems, resulting in poor power quality. This research proposes a Unified Power Quality Conditioner (UPQC) system to overcome these obstacles. The adaptive neuro-fuzzy inference system is employed with IoT connection that allows the UPQC to dynamically adapt in real-time to power quality issues, keeping important loads supplied with clean, uninterrupted power. The suggested system is shown to be beneficial in preventing power outages by providing continuous monitoring, control, and problem diagnostics. The results set the way for future power supply solutions that are more efficient and dependable by adding to a set of information regarding methods to improve power quality in microgrid systems.