Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/4271
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dc.contributor.authorHelena Vasconcelosen
dc.contributor.authorLeonel Magalhães Carvalhoen
dc.contributor.authorJosé Luís Meirinhosen
dc.contributor.authorOmont,Nen
dc.contributor.authorGambier Morel,Pen
dc.contributor.authorJamgotchian,Gen
dc.contributor.authorCirio,Den
dc.contributor.authorCiapessoni,Een
dc.contributor.authorPitto,Aen
dc.contributor.authorKonstantelos,Ien
dc.contributor.authorStrbac,Gen
dc.contributor.authorFerraro,Men
dc.contributor.authorBiasuzzi,Cen
dc.date.accessioned2017-12-19T18:46:42Z-
dc.date.available2017-12-19T18:46:42Z-
dc.date.issued2016en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/4271-
dc.identifier.urihttp://dx.doi.org/10.1109/pmaps.2016.7764166en
dc.description.abstractThe secure integration of renewable generation into modern power systems requires an appropriate assessment of the security of the system in real-time. The uncertainty associated with renewable power makes it impossible to tackle this problem via a brute-force approach, i.e. it is not possible to run detailed online static or dynamic simulations for all possible security problems and realizations of load and renewable power. Intelligent approaches for online security assessment with forecast uncertainty modeling are being sought to better handle contingency events. This paper reports the platform developed within the iTesla project for online static and dynamic security assessment. This innovative and open-source computational platform is composed of several modules such as detailed static and dynamic simulation, machine learning, forecast uncertainty representation and optimization tools to not only filter contingencies but also to provide the best control actions to avoid possible unsecure situations. Based on High Performance Computing (IIPC), the iTesla platform was tested in the French network for a specific security problem: overload of transmission circuits. The results obtained show that forecast uncertainty representation is of the utmost importance, since from apparently secure forecast network states, it is possible to obtain unsecure situations that need to be tackled in advance by the system operator.en
dc.languageengen
dc.relation3348en
dc.relation5366en
dc.relation4971en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.titleOnline Security Assessment with Load and Renewable Generation Uncertainty: the iTesla Project Approachen
dc.typeconferenceObjecten
dc.typePublicationen
Appears in Collections:CPES - Indexed Articles in Conferences

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