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Determining Selection of Recloser Clusters to Automate Power Grids via Integer Programming and Statistical Current AnalysisVIEIRA, F. H. T. , VAZ, R. R. C. , FRANCO, R. A. P. , CARNEIRO, M. L. , ARAUJO, S. G.
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power system planning, power demand, power system analysis computing, load flow, power distribution lines
power(18), distribution(17), systems(11), optimal(6), networks(6), energy(6), algorithm(5), system(4), smart(4), placement(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2019-05-31
Volume 19, Issue 2, Year 2019, On page(s): 91 - 96
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.02012
Web of Science Accession Number: 000475806300012
SCOPUS ID: 85066333632
This work presents a methodology for the deployment of Self-Healing systems in distribution grids in order to decrease continuity indexes such as the Equivalent Duration of Interruption per Consumer Unit. The proposed methodology consists in choosing feeders to receive Self-Healing system based on their performances in relation to the Equivalent Duration of Interruption per Consumer Unit. To this end, this methodology addresses current in the conductors and the number of consumers. In order to determine recloser cluster priorities, it is proposed to consider statistical analysis of current values by Decision theory and Binary Linear Programming. The results show that the application of the proposed methodology for determining recloser cluster priorities and cluster selection has great impact on the system operation since it is related to the number of served consumers, failure rates and compensation for the system.
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