Reflectance losses on solar mirrors due to soiling are a significant challenge for Concentrating Solar Power (CSP) plants. Soiling losses can vary significantly from site to site -- with (absolute) reflectance losses varying from fractions of a percentage point up to several percentage points per day (pp/day), a fact that has motivated several studies in soiling predictive modelling. Yet, existing studies have so far neglected the characterization of statistical uncertainty in their parameters and predictions. In this paper, two reflectance loss models are proposed that model uncertainty: an extension of a previously developed physical model and a simplified model. A novel uncertainty characterization enables Maximum Likelihood Estimation techniques for parameter estimation for both models, and permits the estimation of parameter (and prediction) confidence intervals. The models are applied to data from ten soiling campaigns conducted at three Australian sites (Brisbane, Mount Isa, Wodonga). The simplified model produces high-quality predictions of soiling losses on novel data, while the semi-physical model performance is mixed. The statistical distributions of daily losses were estimated for different dust loadings. Under median conditions, the daily soiling losses for Brisbane, Mount Isa, and Wodonga are estimated as $0.53 \pm 0.66$, $0.08 \pm 0.08$, and $0.58 \pm 0.15$ pp/day, respectively. Yet, higher observed dust loadings can drive average losses as high as $2$ pp/day. Overall, the results suggest a relatively simple approach characterizing the statistical distributions of soiling losses using airborne dust measurements and short reflectance monitoring campaigns.

翻译：由于污损导致的太阳镜反射率损失是聚光太阳能发电厂面临的一项重大挑战。污损损失在不同场址间存在显著差异——（绝对）反射率损失可从每天零点几个百分点到每天几个百分点不等，这一事实推动了多项污损预测建模研究。然而，现有研究迄今未考虑其参数和预测中统计不确定性的表征。本文提出了两种建模不确定性的反射率损失模型：一种是对先前开发的物理模型的扩展模型，另一种是简化模型。一种新颖的不确定性表征方法使得两种模型的参数估计能够采用极大似然估计技术，并允许估计参数（及预测）置信区间。这些模型应用于在澳大利亚三个场址（布里斯班、芒特艾萨、沃东加）进行的十次污损实验数据。简化模型在新型数据上能对污损损失进行高质量预测，而半物理模型的性能则参差不齐。针对不同粉尘负荷，估算了日损失量的统计分布。在中位条件下，布里斯班、芒特艾萨和沃东加的日污损损失估计值分别为$0.53 \pm 0.66$、$0.08 \pm 0.08$和$0.58 \pm 0.15$ pp/天。然而，观测到的较高粉尘负荷可使平均损失高达每天$2$ pp。总体而言，研究结果表明，利用空气中粉尘测量数据和短期反射率监测活动来表征污损损失统计分布的方法相对简单。