Power quality improvement and energy management in hybrid microgrids using a dual-optimization approach
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F25%3A10258892" target="_blank" >RIV/61989100:27730/25:10258892 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.nature.com/articles/s41598-025-20001-0" target="_blank" >https://www.nature.com/articles/s41598-025-20001-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-025-20001-0" target="_blank" >10.1038/s41598-025-20001-0</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Power quality improvement and energy management in hybrid microgrids using a dual-optimization approach
Popis výsledku v původním jazyce
Energy Management (EM) in hybrid Microgrids (MGs) is essential for coordinating Renewable Energy Sources (RESs) and Hybrid Energy Storage Systems (HESSs) to ensure Power Quality (PQ), stable operation, and efficient power flow. Existing optimization-prediction approaches often address these issues in isolation or require high computational overhead, limiting their real-time applicability. To overcome these challenges, this paper proposes a novel dual-optimization framework combining the Artificial Lemming Algorithm (ALA) with the Temporal Kolmogorov-Arnold Network (TKAN), referred to as ALA-TKAN. Unlike conventional methods, ALA-TKAN integrates metaheuristic-based optimization of power flow and HESS scheduling with sequence-aware forecasting of load and renewable generation, enabling proactive and coordinated EM under dynamic conditions. Implemented in MATLAB, the proposed method demonstrates superior performance compared with state-of-the-art techniques such as PDO-MACNN, BWO, PSO, ANN, and MRA-FLC, achieving minimal power loss (2.9 MW), highest efficiency (99.2%), lowest energy cost (0.8 $/Wh), and reduced THD (1.4%). These results confirm the novelty and practical potential of ALA-TKAN as a unified, computationally efficient strategy for PQ enhancement and reliable operation of hybrid MGs.
Název v anglickém jazyce
Power quality improvement and energy management in hybrid microgrids using a dual-optimization approach
Popis výsledku anglicky
Energy Management (EM) in hybrid Microgrids (MGs) is essential for coordinating Renewable Energy Sources (RESs) and Hybrid Energy Storage Systems (HESSs) to ensure Power Quality (PQ), stable operation, and efficient power flow. Existing optimization-prediction approaches often address these issues in isolation or require high computational overhead, limiting their real-time applicability. To overcome these challenges, this paper proposes a novel dual-optimization framework combining the Artificial Lemming Algorithm (ALA) with the Temporal Kolmogorov-Arnold Network (TKAN), referred to as ALA-TKAN. Unlike conventional methods, ALA-TKAN integrates metaheuristic-based optimization of power flow and HESS scheduling with sequence-aware forecasting of load and renewable generation, enabling proactive and coordinated EM under dynamic conditions. Implemented in MATLAB, the proposed method demonstrates superior performance compared with state-of-the-art techniques such as PDO-MACNN, BWO, PSO, ANN, and MRA-FLC, achieving minimal power loss (2.9 MW), highest efficiency (99.2%), lowest energy cost (0.8 $/Wh), and reduced THD (1.4%). These results confirm the novelty and practical potential of ALA-TKAN as a unified, computationally efficient strategy for PQ enhancement and reliable operation of hybrid MGs.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20200 - Electrical engineering, Electronic engineering, Information engineering
Návaznosti výsledku
Projekt
—
Návaznosti
O - Projekt operacniho programu
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Scientific Reports
ISSN
2045-2322
e-ISSN
—
Svazek periodika
15
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
19
Strana od-do
1-10
Kód UT WoS článku
001596688500045
EID výsledku v databázi Scopus
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