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dc.contributor.authorAbrell, Jan-
dc.contributor.authorKunz, Friedrich-
dc.date.accessioned2019-07-22T13:38:07Z-
dc.date.available2019-07-22T13:38:07Z-
dc.date.issued2014-12-17-
dc.identifier.issn1566-113Xde_CH
dc.identifier.issn1572-9427de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/17621-
dc.description.abstractIn northern Europe, wind energy has become a dominate renewable energy source, due to natural conditions and national support schemes. However, the uncertainty about wind generation affects existing network infrastructure and power production planning of generators, which cannot be fully diminished by wind forecasts. In this paper we develop a stochastic electricity market model to analyze the impact of uncertain wind generation on the different electricity markets as well as network congestion management. Stochastic programming techniques are used to incorporate uncertain wind generation. The technical characteristics of transporting electrical energy as well as power plants are explicitly taken into account. The consecutive clearing of the electricity markets is incorporated by a rolling planning procedure reflecting the market regime of European markets. The model is applied to the German electricity system covering one week. Two different approaches of considering uncertain wind generation are analyzed and compared to a deterministic approach. The results reveal that the flexibility of generation dispatch is increased either by using more flexible generation technologies or by operating rather inflexible technologies under part-load conditions.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofNetworks and Spatial Economicsde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectElectricity marketde_CH
dc.subjectStochasticityde_CH
dc.subjectTransmission networkde_CH
dc.subjectUnit commitmentde_CH
dc.subjectRenewable energyde_CH
dc.subject.ddc333.79: Energiede_CH
dc.titleIntegrating intermittent renewable wind generation : a stochastic multi-market electricity model for the european electricity marketde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitZentrum für Energie und Umwelt (CEE)de_CH
dc.identifier.doi10.1007/s11067-014-9272-4de_CH
zhaw.funding.euNode_CH
zhaw.issue1de_CH
zhaw.originated.zhawNode_CH
zhaw.pages.end147de_CH
zhaw.pages.start117de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume15de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.author.additionalNode_CH
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Abrell, J., & Kunz, F. (2014). Integrating intermittent renewable wind generation : a stochastic multi-market electricity model for the european electricity market. Networks and Spatial Economics, 15(1), 117–147. https://doi.org/10.1007/s11067-014-9272-4
Abrell, J. and Kunz, F. (2014) ‘Integrating intermittent renewable wind generation : a stochastic multi-market electricity model for the european electricity market’, Networks and Spatial Economics, 15(1), pp. 117–147. Available at: https://doi.org/10.1007/s11067-014-9272-4.
J. Abrell and F. Kunz, “Integrating intermittent renewable wind generation : a stochastic multi-market electricity model for the european electricity market,” Networks and Spatial Economics, vol. 15, no. 1, pp. 117–147, Dec. 2014, doi: 10.1007/s11067-014-9272-4.
ABRELL, Jan und Friedrich KUNZ, 2014. Integrating intermittent renewable wind generation : a stochastic multi-market electricity model for the european electricity market. Networks and Spatial Economics. 17 Dezember 2014. Bd. 15, Nr. 1, S. 117–147. DOI 10.1007/s11067-014-9272-4
Abrell, Jan, and Friedrich Kunz. 2014. “Integrating Intermittent Renewable Wind Generation : A Stochastic Multi-Market Electricity Model for the European Electricity Market.” Networks and Spatial Economics 15 (1): 117–47. https://doi.org/10.1007/s11067-014-9272-4.
Abrell, Jan, and Friedrich Kunz. “Integrating Intermittent Renewable Wind Generation : A Stochastic Multi-Market Electricity Model for the European Electricity Market.” Networks and Spatial Economics, vol. 15, no. 1, Dec. 2014, pp. 117–47, https://doi.org/10.1007/s11067-014-9272-4.


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