Power Quality Monitoring of a Photovoltaic System Through IoT

The stability and dependability of the grid are of crucial importance as the integration of photovoltaic (PV) systems into electricity grids gathers momentum. Because of their bidirectional power flow and intermittent energy production, PV grid systems present a variety of issues when it comes to power quality (PQ). Effective grid management and stability are limited by the fact that conventional monitoring techniques have difficulties in providing real-time insights into harmonics, voltage stability, and transient disturbances. PV grid systems can only function at peak efficiency if the electricity being transmitted and distributed is of the best possible quality. To address the challenge of power quality monitoring in PV grid systems, this research provides an innovative strategy utilizing Internet of Things (IoT) devices and incremental conductance (IC) Maximum Power Point Tracking (MPPT). Grid operators can immediately identify deviations and problems because of the system's continuous, real-time monitoring of vital power quality metrics, made possible by the IoT. The technology provides predicted insights into power quality fluctuations by analyzing past data and patterns, which improves grid stability and resource allocation. The PV grid system is implemented in Matlab tool and PQ variations may be accurately predicted using historical data, improving grid stability and resource utilization. The study's results will aid in the efficient incorporation of renewable energy sources into the grid by assuring optimum power quality in PV grid systems.