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中国物理学会期刊

室内光伏理论极限效率计算:基于细致平衡原理

Evaluation of Theoretical Efficiency Limits for Indoor Photovoltaics Based on the Detailed Balance Principle

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  • 物联网技术的快速发展带来低功耗电子设备的指数级增长。在此背景下,面向自供电物联网应用的新兴室内光伏技术受到广泛关注。与标准太阳光谱(AM1.5G)相比,常见室内光源光谱范围窄、强度低,使室内光伏理论极限效率及关键参数存在显著差异。本文基于细致平衡原理,系统研究了室内光伏电池理论极限效率的计算方法。明确了不同方法之间效率差异的物理根源及各自适用场景,建立了从理想热力学极限到实际材料潜在性能的系统评估体系。重点分析了在不同照度和相关色温的白色发光二极管(White Light Emitting Diode,WLED)和荧光灯(Fluorescent Lamp,FL)等常见室内光源条件下,半导体材料带隙对理论极限效率的影响规律。结果表明WLED光源辐照下室内光伏的最佳带隙为1.84 eV,FL光源辐照下室内光伏的最佳带隙为1.94 eV,二者均高于AM1.5G辐照条件下的最佳带隙1.34 eV。3000 K WLED和2700 K FL室内光源在1000 lux辐照条件下的Shockley-Queisser理论极限效率分别高达55.31%和56.60%。本文还计算了BiOI、Se、Sb2S3等多种新兴室内光伏材料在非理想吸收系数和非辐射复合影响下的光谱限制最大效率,揭示了限制光伏材料性能的核心因素。本研究为室内光伏材料的筛选与性能预测提供了系统有效的评估依据。

     

    With the rapid development of low-power wireless sensors for the Internet of Things (IoT), the indoor photovoltaic (IPV) is emerging as a promising sustainable off-grid power supply technology to overcome the limitations of traditional battery-powered systems. Compared with the standard AM1.5G solar spectrum, indoor light sources, including white light emitting diodes (WLEDs) and fluorescent lamps (FLs), possess relatively narrow visible spectra (400–700 nm) and low illuminance (200–1000 lux), leading to distinct optimal bandgaps and theoretical efficiency limits for IPV applications. Moreover, existing studies in this field suffer from three notable limitations: firstly, most investigations adopt only one calculation method without systematic comparison of the underlying physical assumptions, deviation sources and applicable boundaries of different methodologies under a unified framework, leading to poor comparability among reported results; secondly, the quantitative influences of illuminance and correlated color temperature (CCT) on the optimal bandgaps and theoretical efficiency of IPV materials remain incompletely clarified, lacking quantitative guidelines for direct material screening; thirdly, most evaluations of the theoretical IPV performance of emerging lead-free photovoltaic materials in the literature lack a systematic database and performance bottleneck analysis to support targeted material development. To address these issues, this study evaluates the Shockley-Queisser (S-Q) theoretical efficiency limit and the spectroscopically limited maximum efficiency (SLME) based on the detailed balance principle. The spectral irradiances of typical WLED and FL light sources under various illuminance levels (200, 500, 1000 lux) and CCT values (2700 K to 6500 K) were measured using a calibrated spectroradiometer, and further used as the spectral input for subsequent efficiency calculations. On this basis, the dependence of the theoretical efficiency limit on the semiconductor bandgap is systematically analyzed. It is revealed that the optimal bandgaps for IPV are 1.84 eV under 3000 K WLED illumination and 1.94 eV under 2700 K FL illumination, both higher than the 1.34 eV optimal bandgap under AM1.5G irradiation. The S-Q theoretical IPV efficiency limits reach 55.31% and 56.60% under 1000 lux 3000 K WLED and 2700 K FL indoor illuminations, respectively. The theoretical efficiency limit increases with the illumination intensity and tends to saturate at high illuminance levels. Moreover, for a given indoor light source, increasing CCT blue-shifts the emission spectrum and further results in the shift of the optimal bandgap to larger values. Based on the SLME method, we evaluate over 10 emerging lead-free materials for IPV applications. It is found that the absorbers of Se, Sb2S3, and AgBiI4 show relatively low optical absorption loss and non-radiative recombination loss, exhibiting great prospects for IPV applications. This work establishes a full-chain evaluation system from ideal thermodynamic limits to practical device performance, clarifies the applicable scenarios of different theoretical models, and quantifies the impacts of indoor light parameters on key performance indicators. The findings provide a systematic theoretical basis and quantitative tools for material screening and optimization, as well as IPV performance prediction, which are of great significance for promoting the large-scale application of IPV for self-powered IoT systems.

     

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