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A Novel PSO Based Fuzzy Controller for Robust Operation of Solid-State Transfer Switch and Fast Load Transfer in Power Systems

وحدة تحكم ضبابية جديدة قائمة على PSO للتشغيل القوي لمفتاح نقل الحالة الصلبة ونقل الحمل السريع في أنظمة الطاقة
Authors: Glorria Sebastian; M. A. Hannan; Ali Q. Al-Shetwi; Pin Jern Ker; M. S. Abd. Rahman 0001; Muhamad Bin Mansor; Kashem M. Muttaqi;

A Novel PSO Based Fuzzy Controller for Robust Operation of Solid-State Transfer Switch and Fast Load Transfer in Power Systems

Abstract

Cet article propose un nouveau contrôleur de logique floue (FLC) basé sur un algorithme d'optimisation d'essaim de particules (PSO) pour améliorer les performances du commutateur de transfert automatique à semi-conducteurs (SST) en ce qui concerne le temps de transfert. La technique proposée génère des fonctions d'appartenance adaptatives (MF) de l'erreur de tension et du taux de changement de l'erreur de tension pour l'entrée et la sortie sur la base de la fonction de mise en forme formulée par le PSO. Une fonction de mise en forme optimale du FLC basée sur le PSO (PSOF) est en outre utilisée pour régler et minimiser l'erreur absolue moyenne (MAE) pour améliorer les performances du transfert de charge dans une courte durée. Les résultats obtenus à partir du PSOF proposé sont comparés à ceux obtenus avec le FLC conventionnel pour valider le contrôleur développé. On observe que le contrôleur optimisé PSOF proposé peut transférer la charge plus rapidement que le contrôleur FLC conventionnel. La précision du PSOF développé est illustrée et étudiée via des tests de simulation pour les SST dans le système IEEE 9-bus. On peut conclure que le contrôleur PSOF est meilleur que le seul contrôleur flou dans tous les cas testés en termes de temps de transfert.

Este documento propone un nuevo controlador de lógica difusa (FLC) basado en el algoritmo de optimización de enjambre de partículas (PSO) para mejorar el rendimiento del interruptor automático de transferencia de estado sólido (SST) con respecto al tiempo de transferencia. La técnica propuesta genera funciones de pertenencia adaptativa (MF) de error de voltaje y tasa de cambio de error de voltaje para entrada y salida en función de la función de aptitud formulada por el PSO. Una función de aptitud FLC (PSOF) óptima basada en PSO se emplea además para ajustar y minimizar el error absoluto medio (MAE) para mejorar el rendimiento de la transferencia de carga en una corta duración. Los resultados obtenidos del PSOF propuesto se comparan con los obtenidos con el FLC convencional para validar el controlador desarrollado. Se observa que el controlador optimizado PSOF propuesto puede transferir la carga más rápido que el controlador FLC convencional. La precisión del PSOF desarrollado se ilustra e investiga a través de pruebas de simulación para SST en el sistema IEEE 9-bus. Se puede concluir que el controlador PSOF es mejor que el único controlador difuso en todos los casos probados en términos de tiempo de transferencia.

This paper proposes a novel particle swarm optimization (PSO) algorithm based fuzzy logic controller (FLC) for improving the performance of automatic solid-state transfer switch (SSTS) with respect to transfer time.The proposed technique generates adaptive membership functions (MFs) of voltage error and rate of change of voltage error for input and output based on the fitness function formulated by the PSO.An optimal PSO-based FLC (PSOF) fitness function is further employed to tune and minimize the mean absolute error (MAE) to improve the performance of the load transfer in a short duration.Results obtained from the proposed PSOF are compared with those obtained with the conventional FLC to validate the developed controller.It is observed that the proposed PSOF optimized controller can transfer the load faster than the conventional FLC controller.The accuracy of the developed PSOF is illustrated and investigated via simulation tests for SSTS in the IEEE 9-bus system.It can be concluded that the PSOF controller is better than the only fuzzy controller in all tested cases in terms of transfer time.

تقترح هذه الورقة وحدة تحكم منطقية ضبابية قائمة على خوارزمية تحسين سرب الجسيمات الجديدة (PSO) لتحسين أداء مفتاح نقل الحالة الصلبة التلقائي (SSTS) فيما يتعلق بوقت النقل. تولد التقنية المقترحة وظائف عضوية تكيفية (MFs) لخطأ الجهد ومعدل تغيير خطأ الجهد للإدخال والإخراج بناءً على وظيفة اللياقة التي صاغها PSO. يتم استخدام وظيفة لياقة FLC (PSOF) المثلى القائمة على PSO لضبط وتقليل متوسط الخطأ المطلق (MAE) لتحسين أداء نقل الحمل في فترة قصيرة. تتم مقارنة النتائج التي تم الحصول عليها من PSOF المقترح مع تلك التي تم الحصول عليها مع FLC التقليدي للتحقق من صحة وحدة التحكم المطورة. لوحظ أن وحدة التحكم المحسنة PSOF المقترحة يمكنها نقل الحمل بشكل أسرع من وحدة تحكم FLC التقليدية. يتم توضيح دقة PSOF المطورة والتحقيق فيها عبر اختبارات المحاكاة لـ SSTS في نظام IEEE 9 - bus. يمكن استنتاج أن وحدة تحكم PSOF أفضل من وحدة التحكم الضبابية فقط في جميع الحالات التي تم اختبارها من حيث الوقت.

Keywords

Artificial intelligence, fuzzy control, Energy Engineering and Power Technology, Fitness function, optimization algorithm, Control (management), Quantum mechanics, Engineering, Maximum power transfer theorem, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), Electrical and Electronic Engineering, Biology, Energy, Transfer function, Particle swarm optimization, Physics, Controller (irrigation), power system faults, Power System Stability and Control Analysis, Voltage, Power (physics), Computer science, Agronomy, TK1-9971, Fuzzy logic, Approximation error, Algorithm, Genetic algorithm, Control and Systems Engineering, Electrical engineering, load transfer, Physical Sciences, Control and Synchronization in Microgrid Systems, Electrical engineering. Electronics. Nuclear engineering, Energy Storage in Power Systems, Automatic solid-state transfer switch, Power System Stability, power transfer, Voltage Stability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
gold