Cuckoo optimization algorithm via Grey Wolf Optimizer for usage in engineering optimization and optimal power flow with renewable energy sources
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F25%3A50022904" target="_blank" >RIV/62690094:18470/25:50022904 - isvavai.cz</a>
Result on the web
<a href="https://www.nature.com/articles/s41598-025-21515-3" target="_blank" >https://www.nature.com/articles/s41598-025-21515-3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-025-21515-3" target="_blank" >10.1038/s41598-025-21515-3</a>
Alternative languages
Result language
angličtina
Original language name
Cuckoo optimization algorithm via Grey Wolf Optimizer for usage in engineering optimization and optimal power flow with renewable energy sources
Original language description
Optimal Power Flow (OPF) is a critical challenge in electrical engineering, necessitating efficient and resilient optimization techniques for successful power distribution management. This study presents COGWO, an innovative hybrid metaheuristic that integrates the Grey Wolf Optimizer (GWO) with the Cuckoo Optimization Algorithm (COA) to enhance convergence quality and solution resilience. Before its implementation in OPF issues, the suggested technique was thoroughly verified against standard engineering problems in CEC2020, continuously surpassing several state-of-the-art methods. Subsequently, COGWO was utilized to tackle OPF issues in the IEEE 30-bus and 118-bus systems, accounting for the fluctuation of renewable energy sources (RESs), such as wind and solar, in conjunction with traditional power network configurations. The method exhibits an optimal balance between exploration and exploitation, successfully minimizing fuel costs, power loss, voltage variation, and emissions, even in the presence of intricate non-convex and non-smooth optimization functions. A comparative examination with COA, GWO, and other modern metaheuristics demonstrates the advantage of COGWO in attaining high-quality global solutions characterized by improved solution stability and convergence speed. When it comes to optimizing power systems on a grand scale, COGWO is an attractive solution due to its computational efficiency, flexibility, and resilience.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific reports
ISSN
2045-2322
e-ISSN
2045-2322
Volume of the periodical
15
Issue of the periodical within the volume
1
Country of publishing house
DE - GERMANY
Number of pages
37
Pages from-to
"Article Number: 37629"
UT code for WoS article
001604675000036
EID of the result in the Scopus database
2-s2.0-105020269957