Author, as appears in the article.: Abdel-Nasser M; Mahmoud K; Lehtonen M
Department: Enginyeria Informàtica i Matemàtiques
e-ISSN: 1941-0050
URV's Author/s: Abdelnasser Mohamed Mahmoud, Mohamed
Keywords: Photovoltaic (pv) Irradiance forecasting Deep long short-term memory (lstm) Choquet integral
Abstract: © 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.
Thematic Areas: 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
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 1551-3203
Author's mail: mohamed.abdelnasser@urv.cat
Author identifier: 0000-0002-1074-2441
Record's date: 2024-07-27
Papper version: info:eu-repo/semantics/acceptedVersion
Link to the original source: https://ieeexplore.ieee.org/document/9097938
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Ieee Transactions On Industrial Informatics. 17 (3): 1873-1881
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
Article's DOI: 10.1109/TII.2020.2996235
Entity: Universitat Rovira i Virgili
Journal publication year: 2021
Publication Type: Journal Publications