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

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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