Advanced MPPT Strategy and Interleaved SEPIC Converter for Efficient Hybrid Micro-grid with IoT Monitoring

The increase in global energy demand continues to cause the supply demand imbalance, thus necessitating the adoption of advanced approaches for efficient energy generation and management. This work addresses this situation by proposing an Internet of Things (IoT)-enabled micro grid that combines an Advanced Maximum Power Point Tracking (MPPT) method and an Interleaved SEPIC Converter to maximise solar energy collection of Photovoltaic (PV) systems. The Interleaved SEPIC Converter assists with improving output voltage level and minimising input current ripple. The MPPT method, is developed using a Tabu Search-driven Artificial Neural Network (ANN), which process real time voltage and track the Maximum Power Point (MPP) of solar PV systems with high precision. This DC output is converted AC using three phase Voltage Source Inverter (VSI) suitable for grid integration. Additionally, the IoT connected PV system provides real-time monitoring, fault diagnostics, and data logging to assist in overall management, and operational flexibility. Simulation using MATLAB validates that the proposed work demonstrates an improvement in converter efficiency by 94% and optimized MPPT tracking efficiency by $\mathbf{9 8. 5 \%}$.