A Novel Methodology to Estimate Probability Density Function of Voltage Sag Duration and Failure Rates on Power Distribution Systems
dc.contributor.author | Cebrian, Juan C. [UNESP] | |
dc.contributor.author | Giacomini, Jairo [UNESP] | |
dc.contributor.author | Carneiro, Carlos A. [UNESP] | |
dc.contributor.author | Silva, Gabriela B. [UNESP] | |
dc.contributor.author | Morales-Paredes, Helmo K. [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.date.accessioned | 2023-07-29T16:06:05Z | |
dc.date.available | 2023-07-29T16:06:05Z | |
dc.date.issued | 2023-01-01 | |
dc.description.abstract | Voltage sags and power interruptions are important power quality problems that affect sensitive customers, mainly because they cause annual massive economical losses to the industrial sector as a result of unexpected production process disruptions. In this sense, to propose corrective and preventive measures and improve the power quality of the distribution systems, stochastic methodologies have been proposed in the literature to estimate annual voltage sags and power interruptions. However, these methodologies, generally, use typical cumulative distribution functions of voltage sag duration (PSgD), which may not reflect the real estate of the network under study. To solve this constraint, this paper proposes a novel methodology to estimate a proper PSgD considering information of the distribution network (i.e., topology and coordination schemes of the protection system) and the stochastic behaviors of short-circuits that can affect the distribution system. Moreover, the proposed methodology allows estimating permanent failure rates and average repair time considering known or expected values of reliability indicators. The results show that this proposed methodology is capable to adapt from an initial PSgD curve to another one with fidelity, in order to achieve real values of expected annual power interruptions. | en |
dc.description.affiliation | São Paulo State University (UNESP) Institute of Science and Engineering, São Paulo | |
dc.description.affiliation | São Paulo State University (UNESP) Institute of Science and Technology, São Paulo | |
dc.description.affiliationUnesp | São Paulo State University (UNESP) Institute of Science and Engineering, São Paulo | |
dc.description.affiliationUnesp | São Paulo State University (UNESP) Institute of Science and Technology, São Paulo | |
dc.format.extent | 16863-16874 | |
dc.identifier | http://dx.doi.org/10.1109/ACCESS.2023.3243552 | |
dc.identifier.citation | IEEE Access, v. 11, p. 16863-16874. | |
dc.identifier.doi | 10.1109/ACCESS.2023.3243552 | |
dc.identifier.issn | 2169-3536 | |
dc.identifier.scopus | 2-s2.0-85148430955 | |
dc.identifier.uri | http://hdl.handle.net/11449/249672 | |
dc.language.iso | eng | |
dc.relation.ispartof | IEEE Access | |
dc.source | Scopus | |
dc.subject | Distribution networks | |
dc.subject | power interruption | |
dc.subject | probability distribution function | |
dc.subject | reliability indicators | |
dc.subject | voltage sag | |
dc.title | A Novel Methodology to Estimate Probability Density Function of Voltage Sag Duration and Failure Rates on Power Distribution Systems | en |
dc.type | Artigo | |
unesp.author.orcid | 0000-0001-8507-3791[1] | |
unesp.author.orcid | 0000-0003-1911-3948[2] | |
unesp.author.orcid | 0000-0002-0551-1243[4] | |
unesp.author.orcid | 0000-0001-8664-3573[5] | |
unesp.campus | Universidade Estadual Paulista (Unesp), Instituto de Ciência e Tecnologia, Sorocaba | pt |
unesp.department | Engenharia de Controle e Automação - ICTS | pt |