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ISSN:
2315-4462 (Print); 2373-3594 (Online)
Abbreviated Title:
Int. J Smart Grid Clean Energy
Frequency:
Quarterly
Editor-in-Chief:
Prof. Danny Sutanto
DOI:
10.12720/sgce
APC:
500 USD
Indexed by:
Inspec (IET),
CNKI
, Crossref, Google Scholar,
etc
.
E-mail:
ijsgce@ejournal.net
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 .... [
Read More
]
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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2021
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Vol. 10, No. 3, July 2021
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A Techno-economic feasibility study of a green energy initiative for a university campus
Author(s): Riad Chedid, Ahmad Sawwas
Departement of Electrical Engineering, Universitas Indonesia, Depok 16424, Indonesia
International Journal of Smart Grid and Clean Energy
, vol. 10, no. 3, July 2021: pp. 203-214
Digital Object Identifier: 10.12720/sgce.10.3.203-214
Abstract
: This paper proposes a novel methodology to redesign the power supply of a university campus characterized by a heavy reliance on diesel generators due to the grid unreliable power supply. The optimized design aims to phase out diesel generators and replace them with a hybrid clean energy system composed of photovoltaics and a battery storage system. A Genetic Algorithm approach is used to optimally size such a system, whereas the optimized energy dispatch is achieved through a rule-based energy management system. The study reveals that the implementation of clean technologies yields significant reduction in the system’s operational cost. The impact of major parameters influencing the economics of the proposed system is assessed through a sensitivity analysis conducted over a 10-year period.
Keywords
: Energy economics, genetic algorithm, microgrid optimal design, rule-based energy management system
Full Paper.pdf
Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
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