Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case

The penetration of renewable generation has grown since the electricity sector has been deregulated. To account for that, this paper proposes a methodology to estimate the downward effect of renewable generation participation upon the day-ahead electricity market prices, since such an effect is quit...

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Detalhes bibliográficos
Autores: Sánchez de la Nieta, Agustín, Contreras, Javier
Formato: artículo
Fecha de publicación:2020
País:España
Recursos:Universidad Loyola Andalucía
Repositorio:Brújula
OAI Identifier:oai:repositorio.uloyola.es:20.500.12412/6758
Acesso em linha:https://hdl.handle.net/20.500.12412/6758
Access Level:acceso abierto
Palavra-chave:Day-ahead electricity market
Merit order
Renewable energy
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spelling Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish caseSánchez de la Nieta, AgustínContreras, JavierDay-ahead electricity marketMerit orderRenewable energyThe penetration of renewable generation has grown since the electricity sector has been deregulated. To account for that, this paper proposes a methodology to estimate the downward effect of renewable generation participation upon the day-ahead electricity market prices, since such an effect is quite intuitive observing the merit order of the generating units. The European Electricity Market Matching Algorithm (EMMA) is currently based on Euphemia (Price Coupling of Regions), though there are several differences among countries across Europe. The new algorithm proposed uses market orders, which include aggregate hourly orders such as aggregate supply and demand curves. These orders are simple orders and the marginal price is affected by complex orders, especially by the minimum income condition (MIC) used in the Iberian Electricity Market and considered in our proposed algorithm. A case study of the Spanish day-ahead electricity market is evaluated for 2015, for which a daily generation sample is composed of 16 days in 2015. The sample is created following the characteristics of thermal production, renewable production and inframarginal production. The conclusions are drawn comparing the simulations of the real marginal prices and the new marginal prices after incorporating renewable generation participation into the aggregate demand curve at the maximum price.2020info:eu-repo/semantics/articlehttps://hdl.handle.net/20.500.12412/6758reponame:Brújulainstname:Universidad Loyola AndalucíaIngléshttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uloyola.es:20.500.12412/67582026-06-24T12:48:37Z
dc.title.none.fl_str_mv Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
title Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
spellingShingle Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
Sánchez de la Nieta, Agustín
Day-ahead electricity market
Merit order
Renewable energy
title_short Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
title_full Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
title_fullStr Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
title_full_unstemmed Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
title_sort Quantifying the effect of renewable generation on day–ahead electricity market prices: The Spanish case
dc.creator.none.fl_str_mv Sánchez de la Nieta, Agustín
Contreras, Javier
author Sánchez de la Nieta, Agustín
author_facet Sánchez de la Nieta, Agustín
Contreras, Javier
author_role author
author2 Contreras, Javier
author2_role author
dc.subject.none.fl_str_mv Day-ahead electricity market
Merit order
Renewable energy
topic Day-ahead electricity market
Merit order
Renewable energy
description The penetration of renewable generation has grown since the electricity sector has been deregulated. To account for that, this paper proposes a methodology to estimate the downward effect of renewable generation participation upon the day-ahead electricity market prices, since such an effect is quite intuitive observing the merit order of the generating units. The European Electricity Market Matching Algorithm (EMMA) is currently based on Euphemia (Price Coupling of Regions), though there are several differences among countries across Europe. The new algorithm proposed uses market orders, which include aggregate hourly orders such as aggregate supply and demand curves. These orders are simple orders and the marginal price is affected by complex orders, especially by the minimum income condition (MIC) used in the Iberian Electricity Market and considered in our proposed algorithm. A case study of the Spanish day-ahead electricity market is evaluated for 2015, for which a daily generation sample is composed of 16 days in 2015. The sample is created following the characteristics of thermal production, renewable production and inframarginal production. The conclusions are drawn comparing the simulations of the real marginal prices and the new marginal prices after incorporating renewable generation participation into the aggregate demand curve at the maximum price.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.12412/6758
url https://hdl.handle.net/20.500.12412/6758
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Brújula
instname:Universidad Loyola Andalucía
instname_str Universidad Loyola Andalucía
reponame_str Brújula
collection Brújula
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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