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In this paper, a stochastic model with regime switching is developed forsolar photo-voltaic (PV) power in order to provide short-term probabilisticforecasts. The proposed model for solar PV power is physics inspired andexplicitly incorporates the stochasticity due to clouds using differentparameters addressing the attenuation in power.Based on the statisticalbehavior of parameters, a simple regime-switching process between the threeclasses of sunny, overcast and partly cloudy is proposed. Then, probabilisticforecasts of solar PV power are obtained by identifying the present regimeusing PV power measurements and assuming persistence in this regime. Toillustrate the technique developed, a set of solar PV power data from a singlerooftop installation in California is analyzed and the effectiveness of themodel in fitting the data and in providing short-term point and probabilisticforecasts is verified. The proposed forecast method outperforms a variety ofreference models that produce point and probabilistic forecasts and thereforeportrays the merits of employing the proposed approach.

A Stochastic Model for Short-Term Probabilistic Forecast of Solar Photo-Voltaic Power