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Stochastic generation of 1-minute solar radiation data

Introduction

Some applications require 1-minute solar radiation data that cannot be derived directly from satellite imagery. A solution to produce such data is to use a stochastic generator that increases the temporal resolution from the native satellite resolution (10, 15 or 30 minutes) to 1-minute time step.

The limitation of this approach is that the so-generated data only has a sense in a statistical fashion. In other words, it should be only used as a whole to characterize the solar resource by means of the probability data distribution since it does not represent the actual variation of solar radiation minute by minute.

The data generated is not suitable in case the absolute accuracy of 1-minute modeled data vs real data is important.  However, for purposes such as battery sizing, when statistical characteristics such as ramps/variability are of interest, the Solargis 1-minute stochastically generated data should be helpful.

Stochastic generation of 1-minute GHI data

The approach used by Solargis to implement the stochastic generator is based on Markov processes. First, tailored transition probability matrices (TPM) for the location of interest and for 4 different sky conditions (from stable to highly variable GHI) are determined on the fly. For this, Solargis relies on its own sky-type classifier and a multi-year worldwide data base of 1-minute GHI measurements from which only the locations with the most similar solar climatic features compared to the location of interest are considered. Next, 1-minute GHI is generated using 10/15/30-min GHI values and the TPMs as inputs following regular Markov processes methods with the constraint that only 1-minute GHI values whose mean is close to the 10/15/30-min GHI input within a tolerance limit (±1 W/m2) are accepted.

Since this approach relies on a very extensive data base of 1-min GHI observations, it allows focusing on the locations with the features that better represent the local GHI climatology including, in particular, ramps and cloud enhancement events.

Generation of 1-minute DNI data

1-minute DNI data is generated from the stochastic 1-minute GHI data using the DIRINDEX model as with the Solargis satellite model.