Soiling is responsible for a loss of 3%–4% of the potential global solar power production that is estimated to rise because of increased deployment in dusty environments [Ilse et al., Joule 3, 2303–2321 (2019)]. For effective mitigation strategies and site selection soiling ratio data is crucial. Soiling can be measured directly by comparing the power or short circuit current of a soiled PV cell or module to that of a clean photovoltaic (PV) device of the same model. In recent years, a number of indirect soiling sensors such as Kipp and Zonen's DustIQ and Atonometric's MARS were introduced. These sensors do not use PV cells to determine the soiling ratio. Indirect soiling sensors derive soiling based on information such as particle concentration and size. The soiling loss of PV systems shows a strong angle of incidence (AOI) dependent pattern for sunny conditions. This pattern is not reproduced by indirect sensors such as DustIQ and MARS. We developed a method to adapt the soiling measurement of indirect soiling sensors using the AOI and the Linke turbidity. The adaptation is based on an analysis of the AOI dependence of the reference cell-derived soiling ratio. Linke turbidity is derived from irradiance measurements. The method reduces the root mean square error between the soiling ratios detected by the DustIQ and a colocated pair of PV reference cells from 0.7% to 0.2%. It can improve cumulative performance calculations that use indirect soiling measurements as an input.

中文翻译：

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间接光学沾污传感器沾污率测量的入射角和漫辐射适应

污染导致全球潜在太阳能发电量损失 3%–4%，估计由于在多尘环境中部署的增加而增加 [Ilse等人。, 焦耳3, 2303–2321 (2019)]。对于有效的缓解策略和场地选择，污染率数据至关重要。通过将污染的光伏电池或模块的功率或短路电流与相同型号的清洁光伏 (PV) 设备的功率或短路电流进行比较，可以直接测量污染。近年来，引入了许多间接污染传感器，如 Kipp 和 Zonen 的 DustIQ 和 Atonometric 的 MARS。这些传感器不使用 PV 电池来确定污染率。间接污染传感器根据颗粒浓度和大小等信息得出污染情况。光伏系统的污染损失在阳光充足的条件下显示出强烈的入射角 (AOI) 依赖模式。DustIQ 和 MARS 等间接传感器无法再现这种模式。我们开发了一种使用 AOI 和 Linke 浊度来调整间接污染传感器的污染测量的方法。适应是基于对参考细胞衍生的污染率的 AOI 依赖性的分析。Linke 浊度来自辐照度测量值。该方法将 DustIQ 检测到的污染率与并置的一对 PV 参考电池之间的均方根误差从 0.7% 降低到 0.2%。它可以改进使用间接污染测量作为输入的累积性能计算。该方法将 DustIQ 检测到的污染率与并置的一对 PV 参考电池之间的均方根误差从 0.7% 降低到 0.2%。它可以改进使用间接污染测量作为输入的累积性能计算。该方法将 DustIQ 检测到的污染率与并置的一对 PV 参考电池之间的均方根误差从 0.7% 降低到 0.2%。它可以改进使用间接污染测量作为输入的累积性能计算。