A simple but accurate two-state model for nowcasting PV power

Marius Paulescu, Nicoleta Stefu, Ciprian Dughir, Andreea Sabadus, Delia Calinoiu and Viorel Badescu

Renewable Energy, 2022, vol. 195, issue C, 322-330

Abstract: A two-state model for short-term forecasting of PV plants output power (further referred as PV2-state) is proposed. PV2-state connects in an inventive way an empirical estimator for clear-sky photovoltaic (PV) power output with a statistical predictor for the sunshine number, a binary indicator stating whether the Sun shines or not. PV2-state shows remarkable features: (1) accessibility (only data series resulted from the PV plant monitoring are processed), (2) universality (no physical models for PV plant components are required) and (3) high-performance (due to a continuous adaptation to the actual atmospheric and PV modules conditions). Based on different error metrics, the model performance is investigated from three perspectives: forecast accuracy, forecast precision and the response to the variability in the state-of-the-sky. The study was conducted with high-quality data collected from a fully monitored experimental micro-PV plant developed on the Solar Platform of the West University of Timisoara, Romania. By processing information about the actual performance of the PV plant, PV2-state proves a notable advance in the forecast precision, becoming a robust competitor in the race for high-accuracy in intra-hour forecast of PV power.

Keywords: PV power; Sunshine number; Forecasting; Estimation; Accuracy (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:195:y:2022:i:c:p:322-330

DOI: 10.1016/j.renene.2022.05.056

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