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ISSN:
2315-4462 (Print); 2373-3594 (Online)
Abbreviated Title:
Int. J Smart Grid Clean Energy
Frequency:
4 issues per year
Editor-in-Chief:
Prof. Danny Sutanto
DOI:
10.12720/sgce
APC:
500 USD
Indexed by:
Inspec (IET),
CNKI
, Crossref, Google Scholar,
etc
.
Editor-in-Chief
Prof. Danny Sutanto
University of Wollongong, Australia
I am very excited to serve as the first Editor-in-Chief of the Journal of Smart Grid and Clean Energy (IJSGCE)and hope that the publication can enrich the readers’ experience .... [
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What's New
2024-03-28
March 28th, 2024 News! Vol. 13, No. 1 has been published online!
2024-01-04
IJSGCE will adopt Article-by-Article Work Flow. For the quarterly journal, each issue will be released at the end of the issue month.
2023-10-09
October 9th, 2023 News! Vol. 11, No. 4 has been published online!
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Published Issues
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2018
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Vol. 7, No. 2, April 2018
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Solving electric grid network congestion problem with batteries – An exploratory study using GIS techniques
Author(s):Vivian Sultan
Claremont Graduate University, Claremont, USA
California State University, Los Angeles, USA
International Journal of Smart Grid and Clean Energy
, vol. 7, no. 2, April 2018: pp. 117-124
ISSN: 2315-4462 (Print)
ISSN: 2373-3594 (Online)
Digital Object Identifier: 10.12720/sgce.7.2.117-124
Abstract
: The United States electric utility industry is transitioning from a one-way distribution grid to a new power grid that will accommodate bidirectional energy flow. Utility companies desire a solution for electric grid traffic congestion, which will work in synchrony with the industry’s transition towards future integrated distribution systems. This shift in the complexity of the supply side, combined with the unpredictable fluctuations in the demand side gives rise to the electric grid network congestion problem, resulting in unpredictable or planned outage.
In recent times, advent of mega size Lithium-Ion batteries has proven to be size and cost efficient to absorb and smoothen out such varying levels of demand on the supply side, thereby addressing the congestion problems effectively. However, the networks are diverse in size and complexity and for a given network, one needs to determine the optimal number and location of such battery storage farms within a network. This report explores how Geographic Information Systems (GIS) can be used to effectively determine the optimal locations of the battery farms in solving the electric grid traffic congestion problem.
Keywords
: Smart grid, DERs, battery storage, circuit capacity, optimal location
Full Paper.pdf
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