Autor según el artículo: Abdel-Nasser M; Mahmoud K; Lehtonen M

Departamento: Enginyeria Informàtica i Matemàtiques

e-ISSN: 1941-0050

Autor/es de la URV: Abdelnasser Mohamed Mahmoud, Mohamed

Palabras clave: Photovoltaic (pv) Irradiance forecasting Deep long short-term memory (lstm) Choquet integral

Resumen: © 2005-2012 IEEE. The intermittent nature associated with photovoltaic (PV) generation is a challenging problem for the optimal planning and efficient management in smart grids. A reliable forecasting model of solar irradiance can play an essential role in allowing high PV penetrations without degrading the grid performance. For this purpose, most related works either use individual forecasting models or ensemble approaches (e.g., weighted average), ignoring the interaction between the values to be aggregated and thus may worsen the forecasting reliability. Differently, in this article, we propose a reliable solar irradiance forecasting method based on long short-term memory (LSTM) models and an aggregation function based on Choquet integral. This novel combination has the following features: 1) LSTM models can achieve accurate predictions because they model the temporal changes in solar irradiance, thanks to their recurrent architecture and memory units, and 2) the Choquet integral can model the interaction between the inputs to be aggregated through a fuzzy measure. This aggregation technique can determine the largest consistency among the conflicting forecasting results, taking advantage of each individual model. To demonstrate the effectiveness of the proposed approach, we compare it with several forecasting methods using six realistic datasets collected from different sites in Finland in which solar irradiance is intermittent. The comparison reveals the high reliability of the proposed forecasting model with different sites and solar profiles.

Áreas temáticas: Interdisciplinar Information systems Engineering, industrial Engenharias iv Engenharias iii Electrical and electronic engineering Control and systems engineering Computer science, interdisciplinary applications Computer science applications Ciência da computação Automation & control systems

Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 1551-3203

Direcció de correo del autor: mohamed.abdelnasser@urv.cat

Identificador del autor: 0000-0002-1074-2441

Fecha de alta del registro: 2023-05-14

Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion

Enlace a la fuente original: https://ieeexplore.ieee.org/document/9097938

URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/

Referencia al articulo segun fuente origial: Ieee Transactions On Industrial Informatics. 17 (3): 1873-1881

Referencia de l'ítem segons les normes APA: Abdel-Nasser M; Mahmoud K; Lehtonen M (2021). Reliable Solar Irradiance Forecasting Approach Based on Choquet Integral and Deep LSTMs. Ieee Transactions On Industrial Informatics, 17(3), 1873-1881. DOI: 10.1109/TII.2020.2996235

DOI del artículo: 10.1109/TII.2020.2996235

Entidad: Universitat Rovira i Virgili

Año de publicación de la revista: 2021

Tipo de publicación: Journal Publications