Forecast of steady-state voltage problems considering simulation and socio-environmental information
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Paper number
2145
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
Authors
Machado Sales, Renan, Sinapsis Inovação em Energia, Brazil
Ordonha Cyrillo, Ivo, Sinapsis Inovação em Energia, Brazil
Pelegrini, Marcelo, Sinapsis Inovação em Energia, Brazil
Luz, Hector, Sinapsis Inovação em Energia, Brazil
Kagan, Nelson, ENERQ - USP, Brazil
Borges da Silva Filho, Elson, Eletrobras, Brazil
Perez Duarte, Daniel, Sinapsis Inovação em Energia, Brazil
Ordonha Cyrillo, Ivo, Sinapsis Inovação em Energia, Brazil
Pelegrini, Marcelo, Sinapsis Inovação em Energia, Brazil
Luz, Hector, Sinapsis Inovação em Energia, Brazil
Kagan, Nelson, ENERQ - USP, Brazil
Borges da Silva Filho, Elson, Eletrobras, Brazil
Perez Duarte, Daniel, Sinapsis Inovação em Energia, Brazil
Abstract
This article presents the general panorama of the use of multiple sources of information to identify consumers who could receive voltage quality different from the appropriate. It is observed that only simulations of power flow, and consequently levels of voltage, are not sufficient for a good prediction of regions and consumers out of the appropriate levels of steady-state voltage. To work around this problem, adjustments and reforms are made to the distribution networks databases, improving the assertiveness of the simulations. However, the simulations still distance themselves from the ideal model of prediction. Using spatial statistics and machine learning techniques, together with data on voltage measurements of the ANEEL product quality campaign and socio-environmental information, there is a significantly higher prediction than the one obtained only by power flow simulations. The predictive results from each model is presented and compared.
Table of content
Keywords
Publisher
AIM
Date
2019-06-03
Published in
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/749
http://dx.doi.org/10.34890/973
http://dx.doi.org/10.34890/973
ISSN
2032-9644
ISBN
978-2-9602415-0-1