Frequency stability improvement in EV-integrated power systems using optimized fuzzy-sliding mode control and real-time validation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10257441" target="_blank" >RIV/61989100:27240/25:10257441 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27730/25:10257441

Výsledek na webu

<a href="https://www.nature.com/articles/s41598-025-89025-w" target="_blank" >https://www.nature.com/articles/s41598-025-89025-w</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-025-89025-w" target="_blank" >10.1038/s41598-025-89025-w</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Frequency stability improvement in EV-integrated power systems using optimized fuzzy-sliding mode control and real-time validation

Popis výsledku v původním jazyce

The rapid growth in power demand, integration of renewable energy sources (RES), and intermittent uncertainties have significantly challenged the stability and reliability of interconnected power systems. The integration of electric vehicles (EVs), with their bidirectional power flow, further exacerbates the frequency fluctuation in the power system. So, to mitigate the frequency &amp; power deviations as well as to stabilize the power system integrated with distributed generators (DGs) and EVs, robust &amp; intelligent control strategies are indispensable. This study dedicates a novel Fuzzy-Sliding Mode Controller (FSMC) utilized for load frequency control (LFC). First, the dynamic response has been evaluated by using a Sliding Mode Controller (SMC), showcasing its robustness against external disturbances and parameter uncertainties. Second, to enhance the performance, fuzzy logic is integrated with SMC, leveraging its adaptability to create the FSMC controller. This FSMC has achieved the superiority by handling non-linearities, communication delays and parameter variations in the system. A significant contribution like the design and tuning of the controllers using a Modified Gannet Optimization Algorithm (MGOA) has been established. The potential of MGOA over GOA has been corroborated by convergence speed and precision through benchmark functions. Furthermore, the paper extensively analyzes the impact of EV integration to the frequency and tie-line power dynamics under varying regulation capacities and uncertain operating conditions. Comparative studies demonstrate that the MGOA-tuned FSMC achieves faster settling times, reduced overshoot, and improved stability metrics compared to conventional and state-of-the-art methods. Finally, the MATLAB-based simulation results are validated through real-time implementation on the OPAL-RT 4510 platform, confirming the robustness and practicality of the proposed methodology in addressing modern power system challenges involving high renewable penetration and EV integration.

Název v anglickém jazyce

Frequency stability improvement in EV-integrated power systems using optimized fuzzy-sliding mode control and real-time validation

Popis výsledku anglicky

The rapid growth in power demand, integration of renewable energy sources (RES), and intermittent uncertainties have significantly challenged the stability and reliability of interconnected power systems. The integration of electric vehicles (EVs), with their bidirectional power flow, further exacerbates the frequency fluctuation in the power system. So, to mitigate the frequency &amp; power deviations as well as to stabilize the power system integrated with distributed generators (DGs) and EVs, robust &amp; intelligent control strategies are indispensable. This study dedicates a novel Fuzzy-Sliding Mode Controller (FSMC) utilized for load frequency control (LFC). First, the dynamic response has been evaluated by using a Sliding Mode Controller (SMC), showcasing its robustness against external disturbances and parameter uncertainties. Second, to enhance the performance, fuzzy logic is integrated with SMC, leveraging its adaptability to create the FSMC controller. This FSMC has achieved the superiority by handling non-linearities, communication delays and parameter variations in the system. A significant contribution like the design and tuning of the controllers using a Modified Gannet Optimization Algorithm (MGOA) has been established. The potential of MGOA over GOA has been corroborated by convergence speed and precision through benchmark functions. Furthermore, the paper extensively analyzes the impact of EV integration to the frequency and tie-line power dynamics under varying regulation capacities and uncertain operating conditions. Comparative studies demonstrate that the MGOA-tuned FSMC achieves faster settling times, reduced overshoot, and improved stability metrics compared to conventional and state-of-the-art methods. Finally, the MATLAB-based simulation results are validated through real-time implementation on the OPAL-RT 4510 platform, confirming the robustness and practicality of the proposed methodology in addressing modern power system challenges involving high renewable penetration and EV integration.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

<a href="/cs/project/TN02000025" target="_blank" >TN02000025: Národní centrum pro energetiku II</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

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

US - Spojené státy americké

Počet stran výsledku

36

Strana od-do

nestránkováno

Kód UT WoS článku

001424375700004

EID výsledku v databázi Scopus

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