Electricity Spot Price Forecast by Modelling Supply and Demand Curve

Detalhes bibliográficos
Autor(a) principal: Pinhão, Miguel
Data de Publicação: 2022
Outros Autores: Fonseca, Miguel, Covas, Ricardo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/143863
Resumo: Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This research received no external funding
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spelling Electricity Spot Price Forecast by Modelling Supply and Demand Curveelectricityelectricity priceelectricity price forecastmarket curvestime-seriesvector auto regressionMathematics(all)Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This research received no external fundingElectricity price forecasting has been a booming field over the years, with many methods and techniques being applied with different degrees of success. It is of great interest to the industry sector, becoming a must-have tool for risk management. Most methods forecast the electricity price itself; this paper gives a new perspective to the field by trying to forecast the dynamics behind the electricity price: the supply and demand curves originating from the auction. Given the complexity of the data involved which include many block bids/offers per hour, we propose a technique for market curve modeling and forecasting that incorporates multiple seasonal effects and known market variables, such as wind generation or load. It is shown that this model outperforms the benchmarked ones and increases the performance of ensemble models, highlighting the importance of the use of market bids in electricity price forecasting.CMA - Centro de Matemática e AplicaçõesDM - Departamento de MatemáticaRUNPinhão, MiguelFonseca, MiguelCovas, Ricardo2022-09-20T22:25:48Z2022-06-112022-06-11T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article20application/pdfhttp://hdl.handle.net/10362/143863eng2227-7390PURE: 46646945https://doi.org/10.3390/math10122012info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:22:41Zoai:run.unl.pt:10362/143863Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:51:10.754398Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Electricity Spot Price Forecast by Modelling Supply and Demand Curve
title Electricity Spot Price Forecast by Modelling Supply and Demand Curve
spellingShingle Electricity Spot Price Forecast by Modelling Supply and Demand Curve
Pinhão, Miguel
electricity
electricity price
electricity price forecast
market curves
time-series
vector auto regression
Mathematics(all)
title_short Electricity Spot Price Forecast by Modelling Supply and Demand Curve
title_full Electricity Spot Price Forecast by Modelling Supply and Demand Curve
title_fullStr Electricity Spot Price Forecast by Modelling Supply and Demand Curve
title_full_unstemmed Electricity Spot Price Forecast by Modelling Supply and Demand Curve
title_sort Electricity Spot Price Forecast by Modelling Supply and Demand Curve
author Pinhão, Miguel
author_facet Pinhão, Miguel
Fonseca, Miguel
Covas, Ricardo
author_role author
author2 Fonseca, Miguel
Covas, Ricardo
author2_role author
author
dc.contributor.none.fl_str_mv CMA - Centro de Matemática e Aplicações
DM - Departamento de Matemática
RUN
dc.contributor.author.fl_str_mv Pinhão, Miguel
Fonseca, Miguel
Covas, Ricardo
dc.subject.por.fl_str_mv electricity
electricity price
electricity price forecast
market curves
time-series
vector auto regression
Mathematics(all)
topic electricity
electricity price
electricity price forecast
market curves
time-series
vector auto regression
Mathematics(all)
description Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This research received no external funding
publishDate 2022
dc.date.none.fl_str_mv 2022-09-20T22:25:48Z
2022-06-11
2022-06-11T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/143863
url http://hdl.handle.net/10362/143863
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2227-7390
PURE: 46646945
https://doi.org/10.3390/math10122012
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 20
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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