Solar generation facilities are inherently spatially distributed and therefore aggregate solar irradiance in both space and time, smoothing its variability. To represent the spatiotemporal aggregation process, most existing studies focus on the reduced correlation in solar irradiance throughout a plant's spatial distribution. In this paper, we derived a cloud advection model that is instead based upon lagging correlations between upwind/downwind portions of a distributed plant, induced by advection of a fixed cloud pattern over the plant. We use the model to calculate a plant transfer function that can be used to predict the smoothing of the time series. The model was validated using the distributed HOPE-Melpitz measurement dataset, which consisted of 50 solar irradiance sensors at 1 s temporal resolution over a 3 × 2 km² bounding area. The initial validation showed that the advection-based model outperforms other models at predicting the smoothed irradiance time series during manually identified, advection dominated conditions. We also conducted validation on the model against additional advection dominated periods in the dataset that were identified algorithmically. The cloud advection model's performance compared well to models in literature, but degraded slightly as larger cross-wind plant distributions were investigated. The results in this paper highlight the need to incorporate advection effects on spatial aggregation during advection dominated conditions. Future development of spatiotemporal aggregation models is needed to unify advective models with existing correlation reduction models and to identify regimes where each dominate.

中文翻译：

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基于空间聚合的太阳辐照度平滑云对流模型

太阳能发电设施在空间上具有固有的分布，因此在空间和时间上聚合太阳辐照度，平滑其可变性。为了表示时空聚集过程，大多数现有研究都集中在整个植物空间分布中太阳辐照度的降低相关性上。在本文中，我们推导出了一个云平流模型，该模型基于分布式工厂的上风/下风部分之间的滞后相关性，这是由固定云模式在工厂上空的平流引起的。我们使用该模型来计算可用于预测时间序列平滑的植物传递函数。该模型使用分布式 HOPE-Melpitz 测量数据集进行验证，该数据集由 50 个太阳辐照度传感器组成，时间分辨率为 3 × 2 km ²边界区域。初步验证表明，在手动识别的平流主导条件下，基于对流的模型在预测平滑辐照度时间序列方面优于其他模型。我们还针对通过算法识别的数据集中额外的平流主导时期对模型进行了验证。云对流模型的性能与文献中的模型相比很好，但随着对更大的侧风设备分布的研究，其性能略有下降。本文中的结果强调了在平流主导条件下将平流对空间聚集的影响纳入其中的必要性。时空聚合模型的未来发展需要将平流模型与现有的相关性降低模型统一起来，并确定各自占主导地位的制度。