Frequency stability improvement in EV-integrated power systems using optimized fuzzy-sliding mode control and real-time validation
The result's identifiers
Result code in 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>
Alternative codes found
RIV/61989100:27730/25:10257441
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Frequency stability improvement in EV-integrated power systems using optimized fuzzy-sliding mode control and real-time validation
Original language description
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 & power deviations as well as to stabilize the power system integrated with distributed generators (DGs) and EVs, robust & 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.
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
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
<a href="/en/project/TN02000025" target="_blank" >TN02000025: National Centre for Energy II</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
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
US - UNITED STATES
Number of pages
36
Pages from-to
nestránkováno
UT code for WoS article
001424375700004
EID of the result in the Scopus database
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