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Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10255374" target="_blank" >RIV/61989100:27240/24:10255374 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/61989100:27730/24:10255374

  • Výsledek na webu

    <a href="https://www.nature.com/articles/s41598-024-66007-y" target="_blank" >https://www.nature.com/articles/s41598-024-66007-y</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1038/s41598-024-66007-y" target="_blank" >10.1038/s41598-024-66007-y</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

  • Popis výsledku v původním jazyce

    Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as &quot;Porpoising&quot;. This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.

  • Název v anglickém jazyce

    Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

  • Popis výsledku anglicky

    Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as &quot;Porpoising&quot;. This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.

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

    <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)

Ostatní

  • Rok uplatnění

    2024

  • 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

    14

  • Číslo periodika v rámci svazku

    1

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    15

  • Strana od-do

    nestránkováno

  • Kód UT WoS článku

    001262145700132

  • EID výsledku v databázi Scopus

    2-s2.0-85197372453