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Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10255753" target="_blank" >RIV/61989100:27240/24:10255753 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/61989100:27730/24:10255753

  • Výsledek na webu

    <a href="https://www.sciencedirect.com/science/article/pii/S2590123024012131" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2590123024012131</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.rineng.2024.102958" target="_blank" >10.1016/j.rineng.2024.102958</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller

  • Popis výsledku v původním jazyce

    Maintaining a stable balance between generated power and load demand is a critical challenge in modern power systems, especially with the increasing integration of renewable energy sources like photovoltaic (PV) systems. This study introduces a novel hybrid educational competition optimizer with pattern search (hECO-PS) algorithm to optimally tune a cascaded proportional-derivative with filter and proportional-integral (PDN-PI) controller for load frequency control (LFC) in a two-area power system comprising a PV system and a reheat thermal power system. The proposed hECO-PS algorithm enhances both global exploration and local exploitation capabilities, resulting in superior convergence rates and solution accuracy. The controller&apos;s performance was evaluated under various scenarios, including a 10 % step load change and solar radiation variations, demonstrating significant improvements in frequency regulation. The hECO-PS tuned PDN-PI controller achieved a minimum integral of time-weighted absolute error (ITAE) value of 0.4464, outperforming conventional methods like the modified whale optimization algorithm and sea horse algorithm, which yielded ITAE values of 2.6198 and 0.8598, respectively. Furthermore, the proposed controller reduced settling time by up to 46 % and minimized overshoot by up to 40 %. These results confirm the efficacy of the proposed approach in enhancing system stability and reliability under dynamic operating conditions, suggesting it as a promising solution for LFC in modern power systems with high renewable energy penetration.

  • Název v anglickém jazyce

    Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller

  • Popis výsledku anglicky

    Maintaining a stable balance between generated power and load demand is a critical challenge in modern power systems, especially with the increasing integration of renewable energy sources like photovoltaic (PV) systems. This study introduces a novel hybrid educational competition optimizer with pattern search (hECO-PS) algorithm to optimally tune a cascaded proportional-derivative with filter and proportional-integral (PDN-PI) controller for load frequency control (LFC) in a two-area power system comprising a PV system and a reheat thermal power system. The proposed hECO-PS algorithm enhances both global exploration and local exploitation capabilities, resulting in superior convergence rates and solution accuracy. The controller&apos;s performance was evaluated under various scenarios, including a 10 % step load change and solar radiation variations, demonstrating significant improvements in frequency regulation. The hECO-PS tuned PDN-PI controller achieved a minimum integral of time-weighted absolute error (ITAE) value of 0.4464, outperforming conventional methods like the modified whale optimization algorithm and sea horse algorithm, which yielded ITAE values of 2.6198 and 0.8598, respectively. Furthermore, the proposed controller reduced settling time by up to 46 % and minimized overshoot by up to 40 %. These results confirm the efficacy of the proposed approach in enhancing system stability and reliability under dynamic operating conditions, suggesting it as a promising solution for LFC in modern power systems with high renewable energy penetration.

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

    Results in Engineering

  • ISSN

    2590-1230

  • e-ISSN

  • Svazek periodika

    24

  • Číslo periodika v rámci svazku

    Volume 24, 2024

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    11

  • Strana od-do

    nestránkováno

  • Kód UT WoS článku

    001322157600001

  • EID výsledku v databázi Scopus

    2-s2.0-85204483136