色素敏化染料
计算机科学
光伏
光伏系统
背景(考古学)
高效能源利用
能量收集
电
环境科学
持续性
建筑工程
能量(信号处理)
电信
电气工程
工程类
物理
生物
古生物学
电解质
量子力学
生态学
电极
作者
Mona Rahmatian,Hoseyn Sayyaadi,Mohsen Ameri
标识
DOI:10.1016/j.ecmx.2024.100606
摘要
Since dye-sensitized solar cells (DSSC) have a suitable efficiency in the invisible region, they present a promising avenue for sustainable energy generation, particularly in the context of indoor environments where ambient lighting prevails. This paper proposes a novel numerical model tailored to assess the performance of DSSCs under indoor lighting conditions, with a specific focus on their potential application in powering Internet of Things (IoT) devices. By considering factors such as radiation intensity and spectral composition, particularly from common indoor light sources like Light Emitting Diodes (LEDs) and Fluorescent lights, the model offers insights into the efficiency and viability of DSSCs in indoor settings. Since empirical analyses are difficult and expensive, the existence of a numerical model that investigates cell behavior under indoor illumination can be beneficial for developing such cells. In conducting verifying analyses under varying lighting conditions, the study demonstrates notable efficiencies of DSSCs, with LED 3000 K illumination at 1000 lux intensity yielding the highest performance. While DSSCs may appear less economically viable in environments with readily available electricity, their potential significance lies in providing sustainable energy solutions for IoT devices, thus reducing dependency on conventional power sources and contributing to environmental sustainability. The scientific significance of this research lies in its contribution to understanding the behavior of DSSCs under indoor lighting, offering insights into their potential applications in powering IoT devices. By providing a numerical model for evaluating DSSC performance under realistic indoor conditions, this study opens avenues for further research in optimizing DSSC technology for indoor energy harvesting applications, thereby advancing the field of renewable energy and sustainable technology integration.
科研通智能强力驱动
Strongly Powered by AbleSci AI