Analysis and modelling of FC-TCR based on static VAR compensator

Pekdemir, Alperen; Yıldız, Ali Bekir

doi:10.1109/iceee2.2018.8391312

Cited by 3 publications

(2 citation statements)

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“…Ayrıca bu cihazlar güç elektroniği tabanlı olduğundan geleneksel sistemlere göre daha hızlı tepki verme özelliğine sahiptirler. Yine bu cihazlar uygun bir şekilde ayarlandığı zaman için güç sistemlerinin kararlılığının iyileştirilmesine de katkı sağlarlar [2,4]. Bu cihazlar, güç sisteminin seri empedansı, akımı, gerilimi, aktif ve reaktif gücü gibi şebeke parametrelerinin uygun kompanzasyonu yoluyla güç sisteminin denetimini sağlamaktadırlar.…”

Section: Gi̇ri̇ş (Introduction)unclassified

“…SVK sistemleri, güç elektroniği ve gömülü sistemlere dayalı cihazlardır. Bu nedenle, şebekeden çekilen veya verilen reaktif gücü hızla kontrol edebilir ve müdahale edebilirler [4]. SVK sistemleri, TKR, tristör anahtarlamalı reaktör (TAR), Sabit kapasitör-tristör kontrollü reaktör (SK-TKR), tristör anahtarlamalı kapasitör (TAK) veya TAK-TKR yapılarından oluşmaktadır.…”

Section: Gi̇ri̇ş (Introduction)unclassified

See 1 more Smart Citation

Tristör Kontrollü Reaktörün Sinirsel Bulanık Denetim Esaslı Reaktif Güç Kontrolü

Keçecioğlu

Kılıç

2019

Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım Ve Teknoloji

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In this study, the reactive power of thyristor controlled reactor (TCR) that is fundamental element of flexible ac transmission system devices is controlled using neuro-fuzzy controller. Adaptive neuro fuzzy inference system (ANFIS) is used as neuro-fuzzy control architecture. A simulation model was developed in MATLAB / Simulink environment to examine the performance of the proposed controller. Figure A. Proposed Method for Reactive Power Control of Thyristor Controlled Reactor Purpose: Conventional Proportional Integral (PI) controller is mostly used flexible AC transmission system (FACTS) devices. However, system parameter variations and non-linear system structures severely impair the performance of this controller. In this study, the neuro-fuzzy controller is used for overcome to these disadvantages. Theory and Methods: The neuro-fuzzy controller is designed for reactive power control of TCR. Adaptive neuro-fuzzy inference system (ANFIS) is used as neuro-fuzzy control architecture. In order to examine the performance of the proposed controller, two different cases are simulated in the studies. The reactive power control performance of the proposed controller is compared to two PI controllers. Results: Simulation results show that the tracking of the reference reactive power of proposed controller is more successfully than to PI controllers. The results that are obtained under the voltage disturbance condition show that, the neuro-fuzzy controller is better disturbance rejection capability than PI controllers. Conclusion: In this study, the neuro-fuzzy controller is used for reactive power control of TCR. The proposed controller for TCR is more superior than conventional PI controllers in terms of control performance parameters (rising time, settling time and overshoot) values. The proposed controller has improved the reactive power control capabilities of thyristor controlled reactor.

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Section: Gi̇ri̇ş (Introduction)unclassified