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arXiv · 1901.07525

Model Estimation for Solar Generation Forecasting using Cloud Cover Data

Daniele Pepe·Gianni Bianchini·Antonio Vicino
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Abstract

This paper presents a parametric model approach to address the problem of photovoltaic generation forecasting in a scenario where measurements of meteorological variables, i.e., solar irradiance and temperature, are not available at the plant site. This scenario is relevant to electricity network operation, when a large number of PV plants are deployed in the grid. The proposed method makes use of raw cloud cover data provided by a meteorological service combined with power generation measurements, and is particularly suitable in PV plant integration on a large-scale basis, due to low model complexity and computational efficiency. An extensive validation is performed using both simulated and real data.

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Daniele Pepe, Gianni Bianchini, Antonio Vicino. 2019-01-22. Model Estimation for Solar Generation Forecasting using Cloud Cover Data. https://doi.org/10.1016/j.solener.2017.08.086

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