solarspatialtools.synthirrad.cloudfield.cloudfield_timeseries
- solarspatialtools.synthirrad.cloudfield.cloudfield_timeseries(weights, scales, size, frac_clear, ktmean, ktmax, kt1pct, scaling='original', edgesmoothing=3)
Generate a time series of cloud fields based on the properties of a time series of kt values. This is an implementation of the method described by Lave et al [1]. Some aspects of the implementation diverge slightly from the initial paper to follow a subsequent code implementation of the method shared by the original authors.
[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.
Parameters
- weightsnp.ndarray
The wavelet weights at each scale
- scaleslist
The scales of the wavelets, should be integer values interpreted as 2**(scale-1) seconds
- sizetuple
The size of the field to generate, x by y
- frac_clearfloat
The fraction of clear sky
- ktmeanfloat
The mean of the kt values
- ktmaxfloat
The maximum of the kt values
- kt1pctfloat
The 1st percentile of the kt values
- scalingstr
The scaling method to use. Either ‘original’ or ‘basic’
- edgesmoothingint
The size of the uniform filter for edge smoothing
Returns
- field_finalnp.ndarray
The final field of simulated clouds