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Reduction of Electrical
Losses Analysis on Distribution Systems with Distributed
Generation and Energy Storage Systems
N.M.
Neto, M. R. C. Albertini, W. B. De Melo, M. V. B. Mendonça,
A. J. P. R. Júnior, F. A. M. Moura and J. R. Camacho
2019/07/15
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Abstract
The increasing use of distributed generation
in the Electric Power Systems has brought these several problems, since
the controllers of these systems must take into account one more variable
for any decisions. Within this context, there was a special emphasis on
the use of electric energy storage systems to reduce losses, with the
allocation of them as a load at the overgeneration points and to reduce
system losses at peak demand points. This article presents an analysis
of the distributed generation to compare the electrical losses using electrical
energy storage. The technique used to estimate the electric energy generation
of a photovoltaic system in one day, according to temperature and irradiation
data, was the application of artificial neural networks. Thus, the storage
element appropriate to the demand and generation levels was first defined
and the OpenDSS tool was used to perform the study of the load flow and
to measure the effect of the use of these storage systems in the IEEE
37 bus network. Using energy storage in this application has
proved to be advantageous, reducing the losses of active power at the
peaks and reducing over-generation during the day, measured as crucial
for the future of the distribution.
| Published in: Renewable Energy
& Power Quality Journal (RE&PQJ, Nº. 17) |
| Pages: 251-256 |
Date of Publication: 2019/07/15 |
| ISSN: 2172-038X |
Date of Current Version:2019/04/10 |
| REF: 279-19 |
Issue Date: July 2019 |
| DOI:10.24084/repqj17.279 |
Publisher: EA4EPQ |
Authors and affiliations
N.M. Neto1, M. R. C. Albertini1, W. B. De Melo1, M.
V. B. Mendonça1, A. J. P. R. Júnior1, F. A. M.
Moura1 and J. R. Camacho2
Electrical Engineering Department, 1. Universidade Federal do Triângulo
Mineiro, Uberaba - Minas Gerais, Brazil
Electrical Engineering Faculty, 2. Universidade Federal de Uberlândia,
Uberlândia - Minas Gerais, Brazil
Key words
Technical losses, energy storage system, distributed generation,
artificial neural network, openDSS.
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