An IoT-Based Controller Realization for PV System Monitoring and Control

Abstract

The increased penetration of PV-based micro-grid in distributed feeder system leads to power quality issues, especially under islanded condition. In this study, the artificial neural network is considered as the inverter control system in PV-based micro-grid, which is optimally placed in a 13-node feeder system. Artificial neural network (ANN) improves the performance and efficiency of the inverter and adjusts power quality. The proposed method is simulated through MATLAB/Simulink, and the results are compared for IoT-based PI and IoT-based ANN controllers. IoT-based systems are beneficial from the point of view of historical big data analysis for effective system planning and design. The total harmonic distortion, voltage, and phase angle variations are to be monitored and maintained within a satisfactory range for the enhancement of micro-grid power quality during grid-connected and islanded modes of operation.