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dc.contributor.authorWestgaard, Sjur
dc.contributor.authorFleten, Stein-Erik
dc.contributor.authorNegash, Ahlmahz
dc.contributor.authorBotterud, Audun
dc.contributor.authorBogaard, Katinka
dc.contributor.authorVerling, Trude Haugsvær
dc.date.accessioned2021-03-16T09:43:15Z
dc.date.available2021-03-16T09:43:15Z
dc.date.created2020-11-27T09:37:04Z
dc.date.issued2020
dc.identifier.issn0360-5442
dc.identifier.urihttps://hdl.handle.net/11250/2733557
dc.description.abstractThis paper uses quantile regression to demonstrate how electricity price distributions are linked to fundamental supply and demand variables. It investigates the California electricity market (zone SP15) for selected trading hours using data from January 8, 2013 to September 24, 2016. The approach quantifies a non-linear relationship between the fundamentals and electricity prices, just as predicted by the merit order curve. Natural gas, greenhouse gas allowance prices and load all have a positive effect on electricity prices, with the effect increasing with the quantiles. In contrast, solar production and wind production both have a negative effect on electricity prices. The effect of solar production increases with quantiles, whereas the effect of wind production decreases with quantiles. This paper also includes a stress testing case study in which a producer faces the risk of high solar and wind production, and investigates the effect on the lower tail of the price distribution. Overall, the results demonstrate how the proposed approach can be a helpful risk management tool for participants in the electricity market.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titlePerforming price scenario analysis and stress testing using quantile regression: A case study of the Californian electricity marketen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.volume214en_US
dc.source.journalEnergyen_US
dc.identifier.doi10.1016/j.energy.2020.118796
dc.identifier.cristin1853236
dc.relation.projectNorges forskningsråd: 296205en_US
dc.description.localcode© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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