Use of scalable fuzzy time series methods to predict electrical demand

Electric power is one of the main engines of humanity since the late eighteenth century, therefore, understanding the behavior of the demand of this corresponds to a very important study. Within this field, electricity demand prediction has been one of the most developed activities in several resear...

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Autores principales: Rubio León, José Miguel, Rubio Cienfuegos, José Manuel
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2023
Materias:
Ciencias Informáticas
FTS methods
PWFTS model
Electrical demand
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/155439
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-155439
record_format dspace
spelling I19-R120-10915-1554392023-07-11T20:01:31Z http://sedici.unlp.edu.ar/handle/10915/155439 isbn:978-950-34-2271-7 Use of scalable fuzzy time series methods to predict electrical demand Rubio León, José Miguel Rubio Cienfuegos, José Manuel 2023-06 2023 2023-07-11T17:56:45Z en Ciencias Informáticas FTS methods PWFTS model Electrical demand Electric power is one of the main engines of humanity since the late eighteenth century, therefore, understanding the behavior of the demand of this corresponds to a very important study. Within this field, electricity demand prediction has been one of the most developed activities in several researches, where the use of fuzzy time series models has had good results. This paper presents the use of scalable fuzzy time series methods, which were developed by Petronio Silva [1] to predict the Spanish electricity demand collected by the Spanish TSO, whose computational implementation uses a Mamdani fuzzy inference system, which directly processes a time series containing the demand data and its register. It should be noted that the database also includes forecasts made by the same Spanish TSO, so comparisons are made with these forecasts. Facultad de Informática Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 46-52
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
FTS methods
PWFTS model
Electrical demand
spellingShingle Ciencias Informáticas
FTS methods
PWFTS model
Electrical demand
Rubio León, José Miguel
Rubio Cienfuegos, José Manuel
Use of scalable fuzzy time series methods to predict electrical demand
topic_facet Ciencias Informáticas
FTS methods
PWFTS model
Electrical demand
description Electric power is one of the main engines of humanity since the late eighteenth century, therefore, understanding the behavior of the demand of this corresponds to a very important study. Within this field, electricity demand prediction has been one of the most developed activities in several researches, where the use of fuzzy time series models has had good results. This paper presents the use of scalable fuzzy time series methods, which were developed by Petronio Silva [1] to predict the Spanish electricity demand collected by the Spanish TSO, whose computational implementation uses a Mamdani fuzzy inference system, which directly processes a time series containing the demand data and its register. It should be noted that the database also includes forecasts made by the same Spanish TSO, so comparisons are made with these forecasts.
format Objeto de conferencia
Objeto de conferencia
author Rubio León, José Miguel
Rubio Cienfuegos, José Manuel
author_facet Rubio León, José Miguel
Rubio Cienfuegos, José Manuel
author_sort Rubio León, José Miguel
title Use of scalable fuzzy time series methods to predict electrical demand
title_short Use of scalable fuzzy time series methods to predict electrical demand
title_full Use of scalable fuzzy time series methods to predict electrical demand
title_fullStr Use of scalable fuzzy time series methods to predict electrical demand
title_full_unstemmed Use of scalable fuzzy time series methods to predict electrical demand
title_sort use of scalable fuzzy time series methods to predict electrical demand
publishDate 2023
url http://sedici.unlp.edu.ar/handle/10915/155439
work_keys_str_mv AT rubioleonjosemiguel useofscalablefuzzytimeseriesmethodstopredictelectricaldemand
AT rubiocienfuegosjosemanuel useofscalablefuzzytimeseriesmethodstopredictelectricaldemand
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