One-Hour Prediction of the Global Solar Irradiance from All-Sky Images Using Artificial Neural Networks

verfasst von

Cristian Crisosto, Martin Hofmann, Riyad Mubarak, Gunther Seckmeyer

Abstract

We present a method to predict the global horizontal irradiance (GHI) one hour ahead in one-minute resolution using Artificial Neural Networks (ANNs). A feed-forward neural network with Levenberg-Marquardt Backpropagation (LM-BP) was used and was trained with four years of data from all-sky images and measured global irradiance as input. The pictures were recorded by a hemispheric sky imager at the Institute of Meteorology and Climatology (IMuK) of the Leibniz Universität Hannover, Hannover, Germany (52.23 N, 09.42 E, and 50 m above sea level). The time series of the global horizontal irradiance was measured using a thermopile pyranometer at the same site. The new method was validated with a test dataset from the same source. The irradiance is predicted for the first 10-30 min very well; after this time, the length of which is dependent on the weather conditions, the agreement between predicted and observed irradiance is reasonable. Considering the limited range that the camera and the ANN can "see", this is not surprising. When comparing the results to the persistence model, we observed that the forecast accuracy of the new model reduced both the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) of the one-hour prediction by approximately 40% compared to the reference persistence model under various weather conditions, which demonstrates the high capability of the algorithm, especially within the first minutes.

Organisationseinheit(en)

Institut für Meteorologie und Klimatologie

Typ

Artikel

Journal

Energies

Band

11

ISSN

1996-1073

Publikationsdatum

11.2018

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Erneuerbare Energien, Nachhaltigkeit und Umwelt, Energieanlagenbau und Kraftwerkstechnik, Energie (sonstige), Steuerung und Optimierung, Elektrotechnik und Elektronik

Ziele für nachhaltige Entwicklung

SDG 7 – Erschwingliche und saubere Energie, SDG 13 – Klimaschutzmaßnahmen

Elektronische Version(en)

https://doi.org/10.3390/en11112906 (Zugang: Offen)
https://doi.org/10.15488/4836 (Zugang: Offen)