Portfolio optimization of electricity markets participation using forecasting error in risk formulation
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Publication Date: | 2021 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Download full: | http://hdl.handle.net/10400.22/18059 |
Summary: | Recent changes in the energy sector are increasing the importance of portfolio optimization for market participation. Although the portfolio optimization problem is most popular in finance and economics, it is only recently being subject of study and application in electricity markets. Risk modeling in this domain is, however, being addressed as in the classic portfolio optimization problem, where investment diversity is the adopted measure to mitigate risk. The increasing unpredictability of market prices as reflection of the renewable generation variability brings a new dimension to risk formulation, as market participation risk should consider the prices variation in each market. This paper thereby proposes a new portfolio optimization model, considering a new approach for risk management. The problem of electricity allocation between different markets is formulated as a classic portfolio optimization problem considering market prices forecast error as part of the risk asset. Dealing with a multi-objective problem leads to a heavy computational burden, and for this reason a particle swarm optimization-based method is applied. A case study based on real data from the Iberian electricity market demonstrates the advantages of the proposed approach to increase market players’ profits while minimizing the market participation risk. |
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Portfolio optimization of electricity markets participation using forecasting error in risk formulationElectricity marketsPortfolio optimizationMulti-objective optimizationRecent changes in the energy sector are increasing the importance of portfolio optimization for market participation. Although the portfolio optimization problem is most popular in finance and economics, it is only recently being subject of study and application in electricity markets. Risk modeling in this domain is, however, being addressed as in the classic portfolio optimization problem, where investment diversity is the adopted measure to mitigate risk. The increasing unpredictability of market prices as reflection of the renewable generation variability brings a new dimension to risk formulation, as market participation risk should consider the prices variation in each market. This paper thereby proposes a new portfolio optimization model, considering a new approach for risk management. The problem of electricity allocation between different markets is formulated as a classic portfolio optimization problem considering market prices forecast error as part of the risk asset. Dealing with a multi-objective problem leads to a heavy computational burden, and for this reason a particle swarm optimization-based method is applied. A case study based on real data from the Iberian electricity market demonstrates the advantages of the proposed approach to increase market players’ profits while minimizing the market participation risk.This work has received funding from the European Union's Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066), from FEDER Funds through COMPETE program and from National Funds through FCT under projects UIDB/00760/2020 and CEECIND/01811/2017. Ricardo Faia was supported by the PhD grant SFRH/BD/133086/2017 from National Funds through FCT.ElsevierRepositório Científico do Instituto Politécnico do PortoFaia, R.Pinto, TiagoVale, ZitaCorchado, Juan Manuel20212100-01-01T00:00:00Z2021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/18059eng0142-061510.1016/j.ijepes.2020.106739metadata only accessinfo: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:RCAAP2023-03-13T13:08:26Zoai:recipp.ipp.pt:10400.22/18059Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:37:12.945748Repositório 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 |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation |
title |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation |
spellingShingle |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation Faia, R. Electricity markets Portfolio optimization Multi-objective optimization |
title_short |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation |
title_full |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation |
title_fullStr |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation |
title_full_unstemmed |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation |
title_sort |
Portfolio optimization of electricity markets participation using forecasting error in risk formulation |
author |
Faia, R. |
author_facet |
Faia, R. Pinto, Tiago Vale, Zita Corchado, Juan Manuel |
author_role |
author |
author2 |
Pinto, Tiago Vale, Zita Corchado, Juan Manuel |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Faia, R. Pinto, Tiago Vale, Zita Corchado, Juan Manuel |
dc.subject.por.fl_str_mv |
Electricity markets Portfolio optimization Multi-objective optimization |
topic |
Electricity markets Portfolio optimization Multi-objective optimization |
description |
Recent changes in the energy sector are increasing the importance of portfolio optimization for market participation. Although the portfolio optimization problem is most popular in finance and economics, it is only recently being subject of study and application in electricity markets. Risk modeling in this domain is, however, being addressed as in the classic portfolio optimization problem, where investment diversity is the adopted measure to mitigate risk. The increasing unpredictability of market prices as reflection of the renewable generation variability brings a new dimension to risk formulation, as market participation risk should consider the prices variation in each market. This paper thereby proposes a new portfolio optimization model, considering a new approach for risk management. The problem of electricity allocation between different markets is formulated as a classic portfolio optimization problem considering market prices forecast error as part of the risk asset. Dealing with a multi-objective problem leads to a heavy computational burden, and for this reason a particle swarm optimization-based method is applied. A case study based on real data from the Iberian electricity market demonstrates the advantages of the proposed approach to increase market players’ profits while minimizing the market participation risk. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021-01-01T00:00:00Z 2100-01-01T00:00:00Z |
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/10400.22/18059 |
url |
http://hdl.handle.net/10400.22/18059 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0142-0615 10.1016/j.ijepes.2020.106739 |
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metadata only access info:eu-repo/semantics/openAccess |
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metadata only access |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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