Cuckoo optimization algorithm via Grey Wolf Optimizer for usage in engineering optimization and optimal power flow with renewable energy sources

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Cuckoo optimization algorithm via Grey Wolf Optimizer for usage in engineering optimization and optimal power flow with renewable energy sources

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Cuckoo optimization algorithm via Grey Wolf Optimizer for usage in engineering optimization and optimal power flow with renewable energy sources

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Scientific reports

ISSN

2045-2322

e-ISSN

2045-2322

Svazek periodika

15

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

37

Strana od-do

"Article Number: 37629"

Kód UT WoS článku

001604675000036

EID výsledku v databázi Scopus

2-s2.0-105020269957