Implementation of the Cloud Advection Model as described by Ranalli et al. Simulates the smoothing of irradiance timeseries by a spatially distributed plant based on cloud advection. For more details see these references:
- J. Ranalli, E.E.M. Peerlings and T. Schmidt, “Cloud Advection and Spatial Variability of Solar Irradiance,” 2020 47th IEEE Photovoltaic Specialists Conference (PVSC), 2020. https://doi.org/10.1109/PVSC45281.2020.9300700
- J. Ranalli and E.E.M. Peerlings, "Cloud Advection Model of Solar Irradiance Smoothing by Spatial Aggregation". (forthcoming, under review by Journal of Renewable and Sustainable Energy).
The code to run the model.
A demonstration of the model in action based upon a uniformly distributed 1-d plant.
A demonstration of the model based upon a random 5km by 5km distribution of points that makeup a plant. As the model relies on a 1-d representation of the plant, these points are projected onto a line representing the cloud motion over the reference point.
Sample data is provided in livermore.csv. This dataset is a CSV file reproduction of the demo data included with the Wavelet Variability Model. Please refer to the source repository for the WVM in PVLIB MATLAB for info and license https://github.com/sandialabs/wvm.
Running the model requires numpy. The demo additionally requires matplotlib for the plots.