Indoor photovoltaic energy harvesting system based on maximum power point control for battery-free smart sensors

Read full text
Authors: Severine Wiysahnyuy Yufenyuy, Ghislain Mengounou Mengata, Léandre Nneme Nneme, Umaru Mohammed Bongwirnso
Cited by: 1
References: 47

Abstract

Photovoltaic energy harvesting has been proven to be a remarkable technique that can provide clean energy for powering smart sensors. However, in indoor settings, the energy scavenged is typically insufficient and unstable to power these sensors. This work presents a battery-free system for powering smart sensors in indoor environments using photovoltaic energy harvesting. The suggested system includes a photovoltaic harvester, an Energy Harvesting Circuit (EHC), and a target load. The EHC is based on the LTC3105 integrated circuit, which employs the maximum power point control technique to ensure that much energy as possible is harvested. An extensive experimental evaluation was conducted using multiple PV module technologies under various indoor light conditions. Based on the maximum harvestable power, open circuit voltage, and size, a 36 cm 2 polycrystalline photovoltaic module was selected for the proposed system. The EHC was tuned with help of the Grey Wolf Optimisation algorithm(GWO)to function only at the maximum power point of the photovoltaic module. The proposed system successfully started and ran the TH01-WH sensor under 100 lx of the incandescent lamp, recording an efficiency of 67.54 %, which represents a solid and realistic benchmark for a device built from standard components and optimized via computational intelligence techniques. This system is less complex and more affordable than MPPT-based harvesting systems, making it ideal for indoor smart sensors operating on low-power budgets

Fields of Study & Subjects

Innovative Energy Harvesting Technologies Energy Harvesting in Wireless Networks Photovoltaic System Optimization Techniques

Publication details

Journal / source
Computers & Electrical Engineering
Publisher
Elsevier BV
Volume
133
Pages
111046–111046
Publication date
17 February 2026
Language
EN