Modeling and Optimisation of a Hybrid Energy Harvesting System for IoT Nodes Through PSO-MPPT

The principal contribution of this research paper is to propose an efficient hybrid solar-wind energy harvesting approach that can be used as a solution to the limited battery energy problem of IoT nodes. Ideally, the IoT Network nodes using optimized Solar-wind Energy Harvesting should function for many years. In order to obtain the optimal power for a hybrid system, the Maximum power point tracking (MPPT) based on Particle Swarm Optimization (PSO) controller is proposed. This is by adjusting the duty cycle of the boost converter for both Solar and wind system based on voltage and current measurements. During this work, the modeling and simulation of the proposed hybrid system with PSO−MPPT technique under various wind speeds and various irradiation levels are done using MATLAB/SIMULINK. The Battery Condition of Charge (SoC), battery voltage and battery Current are evaluated. Simulation results prove that the proposed hybrid system with MPPT using PSO can provide better performance as compared to the Perturb and Observe (P&O) method. The proposed system has the potential to meet the energy demand of IoT nodes. increases the durability, and total efficiency of the IoT devices, making them perpetually powered.