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非常规光伏器件中能量收集性能评估的统计方法
Statistical methods for assessment of energy harvesting performance in unconventional photovoltaics
语言:
中文摘要
本文报道了对安装在实地的大面积发光太阳能聚光器(LSC)基窗户长期监测其能量收集趋势的结果。描述了这些非常规、集成于窗户中的光伏器件的主要特征和与材料相关的方面,以及用于评估其性能的实验室技术。介绍了适用于评估随季节变化和设计差异影响的实地性能特征的新统计方法。利用长期观测数据集,识别出传统光伏器件与基于LSC的光伏器件之间的关键性能差异。实验结果表明,在恶劣天气条件下,配备三维结构光伏模块和荧光聚合物中间层的窗户通常比屋顶安装的硅基光伏组件具有更高的能量产出稳定性。本文提出了一种用于量化能量产出稳定性的新参数,揭示了墙面安装及混合朝向的窗户集成光伏系统相较于传统屋顶安装系统的显著优势。数据集还揭示了能量产出性能与窗户设计类型之间的相关性。所提出的分析方法有望有助于确定适用于商业化尺寸LSC的最佳材料组合,从而补充基于小面积样品的标准实验室评估手段。
English Abstract
Abstract Results of long-term monitoring of the energy harvesting trends in field-installed large area luminescent solar concentrator based windows are reported. The main features and materials-related aspects of these unconventional, window-integrated photovoltaics are described, together with the laboratory techniques used to rate their performance. New statistical methods suitable for benchmarking the season-dependent and design-dependent field performance characteristics are described. Key performance differences between conventional and LSC based photovoltaics are identified using long-term observational datasets. Experimental results show that windows equipped with 3D structured PV modules and fluorescent polymer interlayers often feature higher energy yield stability in adverse weather conditions compared to roof-mounted silicon panels. A new parameter proposed for the quantification of the energy yield stability reveals strong advantages of the wall-mounted and mixed-orientation window-integrated PV over the conventional roof-mounted systems. The datasets also reveal correlations between the energy yield performance and window design types. The proposed data analysis methods are expected to help identify the best material combinations for use in commercial-size LSCs, complementing the standard lab assessments made using small-area samples.
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SunView 深度解读
该LSC光伏窗技术的长期性能监测方法对阳光电源SG系列逆变器的MPPT优化具有重要参考价值。研究揭示的非常规光伏在弱光和恶劣天气下的高稳定性特征,可指导我们优化MPPT算法以适应墙面安装、混合朝向等复杂场景。提出的能量收益稳定性量化参数可集成到iSolarCloud平台,用于预测性维护和多场景性能基准对比,提升分布式光伏系统在建筑一体化应用中的发电效率评估能力,为ST储能系统的充放电策略优化提供数据支撑。