Genetic algorithm type 2 fuzzy logic controller of microgrid system with a fractional-order technique DOI Creative Commons

Bouziane Maroua,

Laid Zarour,

Habib Benbouhenni

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 21, 2025

This paper presents a hybrid approach that combines genetic algorithm (GA)-optimized type-2 fuzzy logic controller (T2FLC) with fractional-order technique for enhanced control of microgrid system. The T2FLC is employed to handle the inherent uncertainties in due fluctuating renewable energy inputs and varying loads. GA optimizes parameters designed FO-T2FLC approach, ensuring optimal performance under different operational conditions. developed strategy modification development traditional as it characterized by rapid dynamic response, high durability, distinctive performance, ease application, inexpensive. Also, this does not depend on mathematical model studied system, which gives satisfactory results if system change. direct current side features photovoltaic array battery storage. In contrast, alternating section comprises multi-functional voltage source inverter integrated shunt active power filter. setup delivers connected loads network. To manage effectively; methods (direct space vector modulation) are used section. Additionally, proposed regulator bus loop, regulate reactive loops network, compensate total harmonic distortion streams. It also injects required into network enhance competence work, efficiency FO-T2FLC-GA verified using MATLAB, comparing T2FLC-GA some existing strategies such third-order sliding mode control. obtained highlight effectiveness strength improving quality reducing value, reduces value percentages estimated at 80%, 33.87%, 32.50% all cases. steady-state error, undershoot, fluctuations, overshoot link compared 1.54%, 33.04%, 25%, respectively. Compared other works, improves response time, overshoot, ripples 59.38%, 50%, 75%, respectively, approach. These could make prominent solution future industrial applications propulsion traction.

Язык: Английский

Genetic algorithm type 2 fuzzy logic controller of microgrid system with a fractional-order technique DOI Creative Commons

Bouziane Maroua,

Laid Zarour,

Habib Benbouhenni

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 21, 2025

This paper presents a hybrid approach that combines genetic algorithm (GA)-optimized type-2 fuzzy logic controller (T2FLC) with fractional-order technique for enhanced control of microgrid system. The T2FLC is employed to handle the inherent uncertainties in due fluctuating renewable energy inputs and varying loads. GA optimizes parameters designed FO-T2FLC approach, ensuring optimal performance under different operational conditions. developed strategy modification development traditional as it characterized by rapid dynamic response, high durability, distinctive performance, ease application, inexpensive. Also, this does not depend on mathematical model studied system, which gives satisfactory results if system change. direct current side features photovoltaic array battery storage. In contrast, alternating section comprises multi-functional voltage source inverter integrated shunt active power filter. setup delivers connected loads network. To manage effectively; methods (direct space vector modulation) are used section. Additionally, proposed regulator bus loop, regulate reactive loops network, compensate total harmonic distortion streams. It also injects required into network enhance competence work, efficiency FO-T2FLC-GA verified using MATLAB, comparing T2FLC-GA some existing strategies such third-order sliding mode control. obtained highlight effectiveness strength improving quality reducing value, reduces value percentages estimated at 80%, 33.87%, 32.50% all cases. steady-state error, undershoot, fluctuations, overshoot link compared 1.54%, 33.04%, 25%, respectively. Compared other works, improves response time, overshoot, ripples 59.38%, 50%, 75%, respectively, approach. These could make prominent solution future industrial applications propulsion traction.

Язык: Английский

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