dc.contributor.author | Durante, Fabrizio | |
dc.contributor.author | Gianfreda, Angelica | |
dc.contributor.author | Ravazzolo, Francesco | |
dc.contributor.author | Rossini, Luca | |
dc.date.accessioned | 2023-09-26T08:09:31Z | |
dc.date.available | 2023-09-26T08:09:31Z | |
dc.date.created | 2022-05-11T14:01:04Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Information Sciences. 2022, 590 74-89. | en_US |
dc.identifier.issn | 0020-0255 | |
dc.identifier.uri | https://hdl.handle.net/11250/3091945 | |
dc.description.abstract | This paper examines the dependence between electricity prices, demand, and renewable energy sources by means of a multivariate copula model while studying Germany, the widest studied market in Europe. The inter-dependencies are investigated in-depth and monitored over time, with particular emphasis on the tail behavior. To this end, suitable tail dependence measures are introduced to take into account a multivariate extreme scenario appropriately identified through the Kendall’s distribution function. The empirical evidence demonstrates a strong association between electricity prices, renewable energy sources, and demand within a day and over the studied years. Hence, this analysis provides guidance for further and different incentives for promoting green energy generation while considering the time-varying dependencies of the involved variables. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.subject | Copula | en_US |
dc.subject | Electricity | en_US |
dc.subject | Kendall distribution | en_US |
dc.subject | Solar and Wind | en_US |
dc.subject | Power | en_US |
dc.subject | Tail Dependence | en_US |
dc.title | A multivariate dependence analysis for electricity prices, demand and renewable energy sources | en_US |
dc.title.alternative | A multivariate dependence analysis for electricity prices, demand and renewable energy sources | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | submittedVersion | en_US |
dc.description.version | acceptedVersion | en_US |
dc.source.pagenumber | 74-89 | en_US |
dc.source.volume | 590 | en_US |
dc.source.journal | Information Sciences | en_US |
dc.identifier.doi | 10.1016/j.ins.2022.01.003 | |
dc.identifier.cristin | 2023617 | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.fulltext | preprint | |
cristin.qualitycode | 2 | |