A new methodology for reducing carbon emissions using multi-renewable energy systems and artificial intelligence
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F24%3A50021678" target="_blank" >RIV/62690094:18450/24:50021678 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2210670724005468?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2210670724005468?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.scs.2024.105721" target="_blank" >10.1016/j.scs.2024.105721</a>
Alternative languages
Result language
angličtina
Original language name
A new methodology for reducing carbon emissions using multi-renewable energy systems and artificial intelligence
Original language description
Microgrid cost management is a significant difficulty because the energy generated by microgrids is typically derived from a variety of renewable and non-renewable sources. Furthermore, in order to meet the requirements of freed energy markets and secure load demand, a link between the microgrid and the national grid is always preferred. For all of these reasons, in order to minimize operating expenses, it is imperative to design a smart energy management unit to regulate various energy resources inside the microgrid. In this study, a smart unit idea for multi-source microgrid operation and cost management is presented. The proposed unit utilizes the Improved Artificial Rabbits Optimization Algorithm (IAROA) which is used to optimize the cost of operation based on current load demand, energy prices and generation capacities. Also, a comparison between the optimization outcomes obtained results is implemented using Honey Badger Algorithm (HBA), and Whale Optimization Algorithm (WOA). The results prove the applicability and feasibility of the proposed method for the demand management system in SMG. The price after applying HBA is 6244.5783 (ID). But after applying the Whale Optimization Algorithm, the cost is found 4283.9755 (ID), and after applying the Artificial Rabbits Optimization Algorithm, the cost is found 1227.4482 (ID). By comparing the proposed method with conventional method, the whale optimization algorithm saved 31.396 % per day, and the proposed artificial rabbit's optimization algorithm saved 80.3437 % per day. From the obtained results the proposed algorithm gives superior performance.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20102 - Construction engineering, Municipal and structural engineering
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sustainable Cities and Society
ISSN
2210-6707
e-ISSN
2210-6715
Volume of the periodical
114
Issue of the periodical within the volume
November
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
20
Pages from-to
"Article Number: 105721"
UT code for WoS article
001295634600001
EID of the result in the Scopus database
2-s2.0-85201114451