Short-term probabilistic forecasting models using Beta distributions for photovoltaic plants

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Fernandez-Jimenez, LA (Author) Other; Cláudio Monteiro (Author) FEUP; Ramirez-Rosado, IJ (Author) Other

Journal

Title: Energy Reports

Vol. 9 No. 9

Pages: 495-502

ISSN: 2352-4847

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 3 Citations

Other information

Authenticus ID: P-00Z-9CS

DOI: 10.1016/j.egyr.2023.01.059

Abstract (EN): This article presents original probabilistic forecasting models for day-ahead hourly energy generation forecasts for a photovoltaic (PV) plant, based on a semi-parametric approach using three deterministic forecasts. Input information of these new models consists of data of hourly weather forecasts obtained from a Numerical Weather Prediction model and variables related to the sun position for future instants. The proposed models were satisfactorily applied to the case study of a real-life PV plant in Portugal. Probabilistic benchmark models were also applied to the same case study and their forecasting results compared with the ones of the proposed models. The computer results obtained with these proposed models achieve better point and probabilistic forecasting evaluation indexes values than the ones obtained with the benchmark models. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8