Parametric methods for probabilistic forecasting of solar irradiance

Seyyed A. Fatemi, Anthony Kuh and Matthias Fripp

Renewable Energy, 2018, vol. 129, issue PA, 666-676

Abstract: This paper proposes two parametric probabilistic forecast methods using beta and two-sided power distributions to predict solar irradiance. It also evaluates their performance. To improve their performance metrics a hybrid procedure based on the beta transformed linear opinion pool is utilized. Our simulations show that these methods – despite their simple structure – can effectively forecast solar irradiance and accurately describe its stochastic characteristics. The proposed approach is flexible and could be extended to many different point forecast methods which otherwise minimize RMSE or MSE.

Keywords: Probabilistic forecast; Solar radiation; Power system (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148118306530
Full text for ScienceDirect subscribers only

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:eee:renene:v:129:y:2018:i:pa:p:666-676

DOI: 10.1016/j.renene.2018.06.022

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().