A Novel Combination of Mycielski-Markov, Regime Switching and Jump Diusion Models for Solar Energy

With renewable energy sources growing, solar power generation is becoming ever more popular around the world, so
forecasting and scenario analysis of Solar Photovoltaic production is benecial for grid operators and investors. In this
paper, we introduce a novel combination of a Mycielski-Markov model, standard regime switching, and jump diusion
models to generate 1-minute Global Horizontal Irradiance time series over any time scale. It can simulate dierent
scenarios of solar irradiance in the future after being trained on empirical data. We verify our model using statistical
tests to compare our simulations with those from an observed time-series in Mauritius. The resulting model is able to
generate simulations retaining the statistical properties of the data. Further, we nd the proposed calibration process to
be robust, and identied that splitting the day into 16 periods to be perfect balance to counter overtting. The proposed
model has the potential to better understand the eects of including large scale Solar Photovoltaic generation into an
energy network, value future investments, or even allow for a cost-benet analysis of subsidies.