IoT-Based Smart Electrification System

Abstract

This paper aims here innovative, smart electrification system using a solar photovoltaic panel employing Kalman filter and IoT. The purpose of the Kalman filter is to—increase the efficiency of a maximum power point tracking (MPPT). The incorporation of IoT enables the real-time data collection. The proposed model is fed the data from a photo voltaic panel (PV). The system consists of voltage and current sensors along with Arduino-Uno to store the collected data. The proposed simulation model is an MPPT that employs Perturb and Observe (P&O) algorithm and a Kalman filter. Experimental setup is then investigated using Typhoon HIL (Hardware-In-the-Loop) simulation test bench. This paves the way for the real-time monitoring of PV panels. Further, Typhoon HIL setup aids for automatic and intelligent control of loads and visualization of live data. The effectiveness of the model proposed is to examine in terms of lesser time of convergence, increased efficiency, reduced error factor, and percentage increment in output power. Thus, the IoT-based remote monitoring will ensure the comfortable sub-station monitoring and display of power and earnings.