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dc.rights.licenseopenen_US
dc.contributor.authorNDAWULA, Mike Brian
dc.contributor.authorDJOKIC, Sasa
dc.contributor.authorKISUULE, Mikka
dc.contributor.authorGU, Chenghong
hal.structure.identifierESTIA - Institute of technology [ESTIA]
dc.contributor.authorHERNANDO GIL, Ignacio
ORCID: 0000-0002-6868-0685
IDREF: 257382976
dc.date.accessioned2025-01-17T09:13:27Z
dc.date.available2025-01-17T09:13:27Z
dc.date.issued2024-09
dc.identifier.issn2352-4677en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/204353
dc.description.abstractEnReliability analysis of large power networks requires accurate aggregate models of low voltage (LV) networks to allow for reasonable calculation complexity and to prevent long computational times. However, commonly used lumped load models neglect the differences in spatial distribution of demand, type of phase-connection of served customers and implemented protection system components (e.g., single-pole vs three-pole). This paper proposes a novel use of state enumeration (SE) and Monte Carlo simulation (MCS) techniques to formulate more accurate LV network reliability equivalents. The combined SE and MCS method is illustrated using a generic suburban LV test network, which is realistically represented by a reduced number of system states. This approach allows for a much faster and more accurate reliability assessments, where further reduction of system states results in a single-component equivalent reliability model with the same unavailability as the original LV network. Both mean values and probability distributions of standard reliability indices are calculated, where errors associated with the use of single-line models, as opposed to more detailed three-phase models, are quantified.
dc.language.isoENen_US
dc.subject.enAggregation
dc.subject.enLow voltage
dc.subject.enMonte Carlo simulation
dc.subject.enReliability equivalent
dc.subject.enState enumeration
dc.subject.enUnavailability
dc.title.enA novel formulation of low voltage distribution network equivalents for reliability analysis
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.segan.2024.101437en_US
dc.subject.halSciences de l'ingénieur [physics]en_US
bordeaux.journalSustainable Energy, Grids and Networksen_US
bordeaux.page101437en_US
bordeaux.volume39en_US
bordeaux.hal.laboratoriesESTIA - Rechercheen_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcehal
hal.identifierhal-04857145
hal.version1
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
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