Short-Term Solar Irradiance Forecasts Using Sky Images and Radiative Transfer Model

Juan Du, Qilong Min, Penglin Zhang, Jinhui Guo, Jun Yang and Bangsheng Yin
Additional contact information
Juan Du: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Qilong Min: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Penglin Zhang: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Jinhui Guo: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Jun Yang: State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Bangsheng Yin: Atmospheric Sciences Research Center, State University of New York, Albany, NY 12203, USA

Energies, 2018, vol. 11, issue 5, 1-16

Abstract: In this paper, we propose a novel forecast method which addresses the difficulty in short-term solar irradiance forecasting that arises due to rapidly evolving environmental factors over short time periods. This involves the forecasting of Global Horizontal Irradiance (GHI) that combines prediction sky images with a Radiative Transfer Model (RTM). The prediction images (up to 10 min ahead) are produced by a non-local optical flow method, which is used to calculate the cloud motion for each pixel, with consecutive sky images at 1 min intervals. The Direct Normal Irradiance (DNI) and the diffuse radiation intensity field under clear sky and overcast conditions obtained from the RTM are then mapped to the sky images. Through combining the cloud locations on the prediction image with the corresponding instance of image-based DNI and diffuse radiation intensity fields, the GHI can be quantitatively forecasted for time horizons of 1–10 min ahead. The solar forecasts are evaluated in terms of root mean square error (RMSE) and mean absolute error (MAE) in relation to in-situ measurements and compared to the performance of the persistence model. The results of our experiment show that GHI forecasts using the proposed method perform better than the persistence model.

Keywords: solar forecasting; sky imaging; radiative transfer model; Global Horizontal Irradiance (GHI) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/5/1107/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/5/1107/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:5:p:1107-:d:144045

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().