Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Detalhes bibliográficos
Autor(a) principal: Eusébio, Eduardo
Data de Publicação: 2015
Outros Autores: Camus, Cristina Inês, Curvelo, Carolina
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.21/4540
Resumo: Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.
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spelling Metaheuristhic approach to the Holt-Winters optimal short term load forecastElectricity demandLoad forecastCombinatorial optimizationEvolutionary algorithmsElectricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.RCIPLEusébio, EduardoCamus, Cristina InêsCurvelo, Carolina2015-05-14T11:12:50Z2015-032015-03-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10400.21/4540engmetadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-12T08:09:47Zoai:repositorio.ipl.pt:10400.21/4540Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:54:03.756185Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Metaheuristhic approach to the Holt-Winters optimal short term load forecast
title Metaheuristhic approach to the Holt-Winters optimal short term load forecast
spellingShingle Metaheuristhic approach to the Holt-Winters optimal short term load forecast
Eusébio, Eduardo
Electricity demand
Load forecast
Combinatorial optimization
Evolutionary algorithms
title_short Metaheuristhic approach to the Holt-Winters optimal short term load forecast
title_full Metaheuristhic approach to the Holt-Winters optimal short term load forecast
title_fullStr Metaheuristhic approach to the Holt-Winters optimal short term load forecast
title_full_unstemmed Metaheuristhic approach to the Holt-Winters optimal short term load forecast
title_sort Metaheuristhic approach to the Holt-Winters optimal short term load forecast
author Eusébio, Eduardo
author_facet Eusébio, Eduardo
Camus, Cristina Inês
Curvelo, Carolina
author_role author
author2 Camus, Cristina Inês
Curvelo, Carolina
author2_role author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Eusébio, Eduardo
Camus, Cristina Inês
Curvelo, Carolina
dc.subject.por.fl_str_mv Electricity demand
Load forecast
Combinatorial optimization
Evolutionary algorithms
topic Electricity demand
Load forecast
Combinatorial optimization
Evolutionary algorithms
description Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.
publishDate 2015
dc.date.none.fl_str_mv 2015-05-14T11:12:50Z
2015-03
2015-03-01T00:00:00Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/4540
url http://hdl.handle.net/10400.21/4540
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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