Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/36091
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dc.contributor.authorBeigaitė, Rita-
dc.contributor.authorKrilavičius, Tomas-
dc.coverage.spatialDE-
dc.date.accessioned2018-05-08T07:09:25Z-
dc.date.available2018-05-08T07:09:25Z-
dc.date.issued2017-
dc.identifier.issn16130073-
dc.identifier.otherVDU02-000021475-
dc.identifier.urihttps://eltalpykla.vdu.lt/handle/1/36091-
dc.identifier.urihttp://ceur-ws.org/Vol-1856/p07.pdf-
dc.description.abstractDue to worldwide liberalization of power markets, electricity can be purchased and sold as any other commodity. The market spot price of electricity has features such as high volatility, seasonality and spikes. In order to minimize risks, maximize profits and make future plans, it is important for participants of electricity market to forecast future prices. The vast number of various methods is applied for solving this problem. However, the accuracy of forecasts is not sufficient, different approaches work differently with different countries (markets). In this paper we describe our experiments with electricity spot price data of Lithuania’s price zone in Nord Pool power market. Short-term forecasts are made by using Average, Seasonal Naïve and Exponential smoothing methods, and results are reporteden
dc.description.sponsorshipBaltijos pažangių technologijų institutas, Vilnius-
dc.description.sponsorshipInformatikos fakultetas-
dc.description.sponsorshipTaikomosios informatikos katedra-
dc.description.sponsorshipVytauto Didžiojo universitetas-
dc.format.extentp. 37-42-
dc.language.isoen-
dc.relation.ispartofCEUR workshop proceedings [electronic resource]: IVUS 2017: proceedings of the IVUS international conference on information technology, Kaunas, Lithuania, April 28, 2017. Aachen : CEUR-WS, 2017, Vol. 1856-
dc.relation.isreferencedbyScopus-
dc.rightsSutarties data 2018-05-07, nr. B000325, laisvai prieinamas interneteen_US
dc.rights.urihttp://www.sherpa.ac.uk/romeo/search.php?issn=1613-0073-
dc.subjectElectricity spot priceen
dc.subjectForecastingen
dc.subjectLithuania’s price zoneen
dc.subject.classificationStraipsnis konferencijos medžiagoje kitose duomenų bazėse / Article in conference proceedings in other databases (P1c)-
dc.subject.otherInformatika / Informatics (N009)-
dc.titleElectricity price forecasting for Nord Pool dataen
dc.typeresearch article-
dcterms.bibliographicCitation9-
dc.date.updated2020-03-25T11:48Z-
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local.typeP-
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptInformatikos fakultetas-
crisitem.author.deptTaikomosios informatikos katedra-
Appears in Collections:3. Konferencijų medžiaga / Conference materials
Universiteto mokslo publikacijos / University Research Publications
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