Power Estimation for Indoor Light Energy Harvesting Systems

Abstract

The growing interest in indoor light energy harvesting for wireless sensor systems and low-power electronics has created a demand for systematic design methods that optimize the system implementation and component choices for different lighting scenarios. Although the spectrum of light is known to influence the efficiency and output power of a photovoltaic (PV) cell, existing power estimation methods neglect the spectrum. By contrast, the power estimation method proposed in this article takes spectral and intensity information into account. It uses low-cost sensors to measure spectral information and select an appropriate device model based on the classification of the light source. The method is evaluated under different light conditions, including individual light sources, mixed artificial light sources, and mixtures of artificial light and sunlight. The results demonstrate that the proposed implementation selects a reasonable model in most cases, including mixed light source conditions. Using light source specific models for PV panels, the resulting estimation error is low and has clear advantages over methods neglecting spectral information.