solarspatialtools.stats.variability_index
- solarspatialtools.stats.variability_index(ghi, clearsky, moving_avg_tau=1, norm=False)
Compute the variability index, defined by Stein et al. [1]. Variability Index represents the ratio between the path length of the actual timeseries as compared to that of the clearsky.
As it requires comparison with the clear sky value, this should only be computed using the GHI (or other irradiance), and not clear sky index.
Parameters
- ghipandas.Series or pd.DataFrame with only a single column
a series containing the ghi
- clearskypandas.Series or pd.DataFrame with only a single column
a series with the clear sky ghi. Must have a temporal index.
- moving_avg_taunumeric
The number of averaging timesteps to use
- normbool
should the output be scaled to represent a dt of 1 minute?
Returns
- variability_indexnumeric
the variability index value
[1] J. S. Stein, C. W. Hansen, and M. J. Reno, “The Variability Index: A New and Novel Metric for Quantifying Irradiance and PV Output Variability,” in Proceedings of the World Renewable Energy Forum (Denver, CO, 2012) pp. 13–17. https://www.osti.gov/biblio/1078490