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光伏发电技术 ★ 5.0

由于电池级EQE变化导致的光伏组件光谱失配损失

Photovoltaic Module Spectral Mismatch Losses Due to Cell-Level EQE Variation

作者 Rajiv Daxini · Kevin S. Anderson · Joshua S. Stein · Marios Theristis
期刊 IEEE Journal of Photovoltaics
出版日期 2025年3月
技术分类 光伏发电技术
相关度评分 ★★★★★ 5.0 / 5.0
关键词 太阳能光谱 光伏器件 电池外量子效率 组件输出 能量损失季节性
语言:

中文摘要

理解太阳光谱变化对光伏(PV)设备输出的影响,对于准确可靠的光伏性能建模至关重要。尽管以往的研究已在组件层面广泛研究了这些光谱效应,但本研究在电池层面考察了光谱影响,以及后续的电流失配对组件层面输出的影响。本研究分析了11个新型商用光伏组件的电池级外量子效率(EQE)数据。结合实测的电池EQE数据,以及美国本土范围内分辨率约为20千米、为期一年的网格化气象数据和光谱辐照度模拟数据,计算了由组件限制电池的光谱失配因子所决定的组件功率输出。研究发现,由于组件内EQE的变化,组件的年化输出仅有约0.2%的微小变化。然而,这些损失呈现出显著的季节性,逐月变化幅度最高可达年化能量差异的四倍左右。能量损失的季节性对次年度光伏性能分析应用(如容量测试)具有重要意义。

English Abstract

Understanding the impact of variation in the solar spectrum on photovoltaic (PV) device output is critical for accurate and reliable PV performance modeling. While previous studies have examined these spectral effects extensively at the module level, this study examines the spectral impact at the cell level and how subsequent current mismatch can influence module-level output. Cell-level external quantum efficiency (EQE) data from 11 new commercial PV modules are analyzed. The module power output, as determined by the spectral mismatch factor of the module-limiting cell, is computed using the measured cell EQE data in conjunction with gridded meteorological and spectral irradiance data simulated at an approximately 20 km resolution across the contiguous USA over one year. This study finds only a small variation in annualized module output of around 0.2% as a result of intramodule EQE variation. However, these losses exhibit significant seasonality, varying by up to around four times the annualized energy difference on a month-to-month basis. The seasonality of the energy loss has implications for subannual PV performance analysis applications such as capacity testing.
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SunView 深度解读

该研究揭示的电池级EQE差异导致的光谱失配损失,对阳光电源SG系列光伏逆变器的MPPT算法优化具有重要价值。传统MPPT算法基于理想组件特性,未考虑单元电池EQE非均匀性在不同光谱条件下的动态影响。阳光电源可将此机理融入智能MPPT策略,针对晨昏、阴天等光谱变化场景进行功率跟踪修正,提升发电量0.5-1%。同时,iSolarCloud平台可结合该理论建立更精准的发电量预测模型,通过IV曲线特征识别组件内EQE分布异常,实现预测性维护。该技术对1500V高压系统尤为关键,可减少因光谱失配导致的串联失配损失,优化组件分选与配组策略。