cris.boxmetadata.label.title
Aggregator units allocation in low voltage distribution networks with penetration of photovoltaic systems
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.september 2021
cris.boxmetadata.label.accesslevel
metadata only access
cris.boxmetadata.label.resourcetype
journal article
cris.boxmetadata.label.authors
Palate B.O.
Guedes T.P.
Grilo-Pavani A.
Padilha-Feltrin A.
Federal University of ABC
cris.boxmetadata.label.publisher
Elsevier Ltd
cris.boxmetadata.label.abstract
The aggregator units are essential in implementing smart grids since they are responsible for connecting smart meters installed on the consumers and ensuring exchanging information with the utility control centers. This paper presents a methodology to allocate these aggregators in low voltage distribution systems with solar photovoltaic generation. The proposed method is composed of two stages. In the first one, the aggregators are allocated considering the minimization of the distance to the remote terminal unit and their installation costs using a method based on Particle Swarm Optimization. In the second stage, the smart meters are connected to each allocated aggregator using a graph method. These connections are performed, taking into account a function, which depends on the distance between the meters and the load density within the aggregator coverage area. The proposed methodology was tested using a 400 V low voltage distribution system with 45 residential loads and 12 photovoltaic generators. The results showed that the proposal allocates aggregators at points where the consumer groups' load curves into the aggregator coverage area are better characterized. The values of the average voltage profile and the system's power losses in each aggregator coverage area presented an excellent match with values obtained with the test system without installing aggregators. From this characterization, it is possible to get useful information for operational planning and expansion planning of low voltage networks with photovoltaic generators by aggregation areas.
cris.boxmetadata.label.volume
130
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Ingeniería eléctrica, Ingeniería electrónica Biorremediación, Biotecnologías de diagnóstico en la gestión ambiental
cris.boxmetadata.label.doi
cris.boxmetadata.label.scopusidentifier
2-s2.0-85110422108
cris.boxmetadata.label.source
International Journal of Electrical Power and Energy Systems
cris.boxmetadata.label.containerissn
0142-0615
cris.boxmetadata.label.sponsor
This work was supported by São Paulo Research Foundation (FAPESP) under grants: 2015/21972-6, 2019/00466-6; and by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) -Finance Code 001, and by CNPq under the grant: 310299/2020-9, 440088/2019-4, 422044/2018-0, and by Instituto Nacional de Ciência e Tecnologia de Energia Elétrica - Brazil (INCT-INERGE), and by ENEL under the grant: PEE-00390-1062/2017 - P&D-00390-1083-2020_UFABC, ANEEL 001-2016.
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