Probabilistic Assessment of Network Hosting Capacity

annif.suggestionselectrical power networks|distribution of electricity|renewable energy sources|production of electricity|transmission of electricity|electric power|networks (societal phenomena)|Monte Carlo methods|distribution|simulation|enen
annif.suggestions.linkshttp://www.yso.fi/onto/yso/p7753|http://www.yso.fi/onto/yso/p187|http://www.yso.fi/onto/yso/p20762|http://www.yso.fi/onto/yso/p5561|http://www.yso.fi/onto/yso/p19716|http://www.yso.fi/onto/yso/p1213|http://www.yso.fi/onto/yso/p5570|http://www.yso.fi/onto/yso/p6361|http://www.yso.fi/onto/yso/p7415|http://www.yso.fi/onto/yso/p4787en
dc.contributor.authorLagos, Athanasios-Rafail
dc.contributor.authorGatos, Andreas
dc.contributor.authorHatziargyriou, Nikos
dc.contributor.authorLaaksonen, Hannu
dc.contributor.departmentVebic-
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|-
dc.contributor.orcidhttps://orcid.org/0000-0001-9378-8500-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2024-12-05T13:30:06Z
dc.date.accessioned2025-06-25T13:54:08Z
dc.date.available2024-12-05T13:30:06Z
dc.date.issued2024-07-01
dc.description.abstractThe integration of a substantial quantity of distributed renewable energy sources (DRES) with minimum environmental impact, yet with immense uncertainty in the energy production, poses significant challenges to the distribution networks (DNs). Consequently, the evaluation and enhancement of the hosting capacity (HC) of the DNs have garnered considerable attention. This paper introduces a novel planning method for increasing the HC of a DN without necessitating expensive long-term infrastructure upgrades. A proper threshold for acceptable violations of the DN’s operating voltage limits is defined and a probabilistic method for assessing the probability of occurrence of such violations is formulated, based on Monte Carlo (MC) simulations. If the probability of violations falls below the specified threshold, approval for the integration of the examined RES is granted. This framework is a relaxation of the widely applied worst-case scenario planning methodologies for addressing uncertainties in DRES integration studies. Under this approach, the maximization of the hosting capacity is formulated as a stochastic optimization problem with chance constraints. Applying this methodology to a distribution network of Greece and comparing the outcomes with the existing methodology employed by the Hellenic Electricity Distribution Network Operator (HEDNO) reveals a significant increase in HC for a certain set of candidate buses for PV installation.-
dc.description.notification©2024 Institution of Engineering and Technology.-
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|-
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.format.extent5-
dc.format.pagerange100-104-
dc.identifier.olddbid21988
dc.identifier.oldhandle10024/18389
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/2959
dc.identifier.urnURN:NBN:fi-fe20241205100024-
dc.language.isoeng-
dc.publisherInstitution of engineering and technology-
dc.relation.conferenceCIRED-
dc.relation.funderEnergy Competence Center (ECC)-
dc.relation.funderBusiness Finland-
dc.relation.ispartofjournalIET Conference Proceedings-
dc.relation.issn2732-4494-
dc.relation.issue5-
dc.relation.urlhttps://digital-library.theiet.org/doi/10.1049/icp.2024.1888-
dc.relation.volume2024-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/18389
dc.subjecthosting capacity-
dc.subjectvoltage violations-
dc.subjectprobabilistic load flows-
dc.subjectMonte-Carlo simulation-
dc.subjectstochastic optimization-
dc.subject.disciplinefi=Sähkötekniikka|en=Electrical Engineering|-
dc.titleProbabilistic Assessment of Network Hosting Capacity-
dc.type.okmfi=A4 Artikkeli konferenssijulkaisussa|en=A4 Peer-reviewed article in conference proceeding|sv=A4 Artikel i en konferenspublikation|-
dc.type.publicationarticle-
dc.type.versionacceptedVersion-

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