Probabilistic Algorithm based on 2m+1 Point Estimate Method Edgeworth considering Voltage Confidence Intervals for Optimal PV Generation

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorGecad Polytechnic of Porto-
Autor(es): dc.creatorBautista, Luis Gustavo Cordero-
Autor(es): dc.creatorSoares, Joao-
Autor(es): dc.creatorBaquero, John Fredy Franco-
Autor(es): dc.creatorVale, Zita-
Data de aceite: dc.date.accessioned2025-08-21T18:08:45Z-
Data de disponibilização: dc.date.available2025-08-21T18:08:45Z-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PMAPS53380.2022.9810644-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/240554-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/240554-
Descrição: dc.descriptionPhotovoltaic (PV) systems widespread into distribution networks due to its environmentally friendly source of energy, cost-competitive option and system support benefits. However, traditional distribution networks were not designed to operate under a high penetration of intermittent generation posing technical challenges for grid operation and planning. Therefore, probabilistic tools become suitable to cater for uncertainties in generation and demand, thus, leading to a more realistic network representation. Furthermore, the need for harvesting potential energy in an uncertain environment are essential for an efficient grid operation. In this context, this work proposes a probabilistic algorithm based on 2m+1 Point Estimate Method Edgeworth to tackle technical issues considering voltage confidence levels that is used for maximizing PV generation. Tests in a IEEE 33 buses radial distribution system using the proposed probabilistic algorithm yields higher accuracy of cost probability distribution, voltage confidence intervals and a faster computational time when compared to Monte Carlo simulation.-
Descrição: dc.descriptionSão Paulo State University Dep. of Electrical Engineering-
Descrição: dc.descriptionGecad Polytechnic of Porto-
Descrição: dc.descriptionSão Paulo State University Dep. of Electrical Engineering-
Idioma: dc.languageen-
Relação: dc.relation2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subject2m+1 Point Estimate Method Edgeworth-
Palavras-chave: dc.subjectOptimal Probability PV Generation-
Palavras-chave: dc.subjectProbabilistic Algorithm Optimization-
Palavras-chave: dc.subjectVoltage Confidence Intervals-
Título: dc.titleProbabilistic Algorithm based on 2m+1 Point Estimate Method Edgeworth considering Voltage Confidence Intervals for Optimal PV Generation-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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