Optimizing IoT network lifetime through an enhanced hybrid energy harvesting system

Abstract

The growing need for sustainable and renewable energy sources has become critical with the Internet of Things (IoT) advancement. IoT relies on low-power, battery-operated devices, but the limited lifespan of these batteries requires frequent recharging or replacement, which is costly and time-consuming. Researchers have proposed energy harvesting systems that capture sustainable ambient energy from the environment to address this issue. This paper presents a hybrid system for harvesting sustainable energy from solar and wind sources. The system features a boost converter controlled by a novel hybrid method combining the Honey Badger Algorithm (HBA) and Harris Hawks Optimization (HHO). This method maximizes power extraction from solar and wind sources, enhancing overall system efficiency. Additionally, the system includes an innovative energy management algorithm that selects the most powerful input source while protecting the storage battery from overcharging or complete depletion, thereby extending its lifespan. The proposed design is validated through MATLAB/Simulink simulations. The HHO–HBA MPPT is compared with existing MPPT methods, evaluating efficiency, battery charge curves, and IoT network energy status. Simulation results show that the proposed approach significantly increases network longevity, offering a cost-effective and sustainable solution for the energy needs of Wireless Sensor Network (WSN)-IoT devices.