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Modeling maximum day-ahead market price using circular statistical methods

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dc.contributor.authorMartins, Ana Alexandra
dc.contributor.authorLagarto, João
dc.contributor.authorSousa, Jorge A. M.
dc.date.accessioned2017-11-29T15:00:41Z
dc.date.available2017-11-29T15:00:41Z
dc.date.issued2017
dc.description.abstractElectricity day-ahead market price and traded quantity present a distinct pattern between peak and off-peak hours, following a pattern that tends to repeat over a 24-hour time cycle. The cyclic nature of these variables enables the use of circular statistics. Circular statistics is a set of techniques for modelling the random nature of directional data, which are typically expressed as angular measurements, which can be used to analyze any kind of data that are cyclic in nature, such as time-of-day data measured on a 24h clock. In this study, the circular statistical methods are used for analyzing the maximum values of day-ahead market price in the Iberian Electricity Market (MIBEL). The data considered in this study refer to the hourly price of electricity observed in the MIBEL, for Portugal and Spain. Also, variables that have influence on the electricity market prices such as demand, production by technology, namely hydro, coal, CCGT and Special Regime Production (production from CHP, wind, photovoltaic, small hydro, etc.) and the strategic behavior of market participants are also analyzed using circular statistics methods. The analysis performed allowed to conclude that circular statistical methods are a powerful tool to understand market price behavior.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMARTINS, Ana; LAGARTO, João; SOUSA, Jorge A. M. - Modeling maximum day-ahead market price using circular statistical methods. In Proceedings of the 3rd International Conference on Energy and Environment: bringing together Engineering and Economics. Porto, Portugal: Universidade do Porto, 2017. Pp. 475-482pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.21/7625
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectCircular statisticspt_PT
dc.subjectDay-ahead marketpt_PT
dc.subjectIberian electricity marketpt_PT
dc.subjectMarket pricept_PT
dc.titleModeling maximum day-ahead market price using circular statistical methodspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FCEC%2F50021%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00066%2F2013/PT
oaire.citation.conferencePlacePorto, Portugal, June, 2017pt_PT
oaire.citation.endPage482
oaire.citation.startPage475
oaire.citation.title3rd International Conference on Energy and Environment: bringing together Engineering and Economicspt_PT
oaire.fundingStream5876
oaire.fundingStream5876
person.familyNameMartins
person.familyNameLagarto
person.familyNameSousa
person.givenNameAna Alexandra
person.givenNameJoão
person.givenNameJorge A. M.
person.identifier2750231
person.identifier.ciencia-id2016-88BF-5D0B
person.identifier.ciencia-id0512-2920-3C9E
person.identifier.ciencia-idF816-08E3-B045
person.identifier.orcid0000-0003-3733-6619
person.identifier.orcid0000-0002-7047-6210
person.identifier.orcid0000-0002-1110-6586
person.identifier.ridM-1020-2015
person.identifier.scopus-author-id34969159800
person.identifier.scopus-author-id24758947600
person.identifier.scopus-author-id55940825700
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublication174bfcee-266b-483c-bc13-f187a886014d
relation.isAuthorOfPublication69325e43-1f4e-4c1c-8c69-159ac3f93066
relation.isAuthorOfPublication.latestForDiscovery174bfcee-266b-483c-bc13-f187a886014d
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