Cloud field #26
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Cloud field #26
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…rom documentation directly to validate.
…for scale_field_lave, and then to define what to do with the data.
… the field. No doublecheck on the realism yet. At a glance it looks like our spatial variance is very small, because we assume a 1 second spatiotemporal resolution. That means our crosswind distances for large cloud velocities are actually very large, which is to say that many along-wind spaced points get the exact same time series with only temporal shifting. That could be good or bad depending on your point of view. Maybe "it is what it is" for the Lave scaling case, but this could be a contribution that I make to the methodology.
# Conflicts: # demos/synthetic_clouds_demo.ipynb
…ed to fix up the python file demos and write docs for readthedocs
…g method subroutines.
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Implementation of Lave et al cloud field approach for synthetic irradiance generation/downscaling. Special thanks to Sophie Pelland and Matt Lave for sharing Matlab code that was used behind the scenes in preparing this.
[1] Matthew Lave, Matthew J. Reno, Robert J. Broderick, "Creation and Value of Synthetic High-Frequency Solar Inputs for Distribution System QSTS Simulations," 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC), Washington, DC, USA, 2017, pp. 3031-3033, doi: https://dx.doi.org/10.1109/PVSC.2017.8366378.