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A neural network controller and a simple circuit of SVPWM technique to increase five-level VSC STATCOM performance during voltage sag and swell
International Journal of Power Electronics and Drive Systems · Vol. 15 No. 3 (2024) · hlm. 1478–1489
- ISSN
- 2722-256X, 2088-8694
- Terbit
- 2024-09-01
- Penerbit
- Institute of Advanced Engineering and Science
- Bahasa
- eng
Abstrak
The most critical disturbance faced in the electrical distribution systems is power service interruptions due to voltage sag or swell which results in economic losses on the user’s side. To compensate voltage sag or swell, advanced custom power devices are used and one of such devices is the static synchronous compensation (STATCOM). This paper presents the implementation of 5-level voltage source converter (VSC) STATCOM using a neural network (NN) and a simplified space vector pulse width modulation (SVPWM) circuit. The primary objective of the NN controller and SVPWM circuit is to enhance the performance and response time of the STATCOM system, specifically in terms of improving voltage and power factor (PF) when faced with voltage sag or swell. The performance of STATCOM was examined within the context of the IEEE 3-bus system. The investigation focused on two scenarios: a single-line-to-ground fault resulting in voltage sag, and the sudden connection of a capacitive load leading to voltage swell. The findings unequivocally demonstrated the efficacy of the STATCOM with a NN controller in comparison to a conventional controller. The utilization of the NN controller resulted in notable improvements in voltage and PF within a remarkably short time frame of 0.02 seconds.
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- University of Kuala Lumpur
- Universiti Malaysia Pahang Al-Sultan Abdullah
- Universiti Putra Malaysia
- Universiti Sains Malaysia
- University of Technology Malaysia
- Universitas Ahmad Dahlan
- Hohai University
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| Rekan penulis | Organisasi | Artikel bersama |
|---|---|---|
| Tole Sutikno | Universitas Ahmad Dahlan | 18 |
| Awang Jusoh | University of Technology Malaysia | 18 |
| Ibrahim Alhamrouni | University of Kuala Lumpur | 5 |
| Mohamed A. Omran | Universiti Malaysia Pahang Al-Sultan Abdullah | 4 |
| Mohamed A Omran | Universiti Malaysia Pahang Al-Sultan Abdullah | 4 |
| Mohamed Asghaiyer Omran | Universiti Sains Malaysia | 3 |
| Izzeldin. I. Ibrahim | Universiti Sains Malaysia | 3 |
| Nik Rumzi Nik Idris | University of Technology Malaysia | 2 |
| Dahaman Ishak | Universiti Sains Malaysia | 2 |
| Khalid Adam | Universiti Malaysia Pahang Al-Sultan Abdullah | 1 |
| Younis Ibrahim | Hohai University | 1 |
| Iftikhar Abid | Advanced Photon Source | 1 |
| R. Ismail | University of Kuala Lumpur | 1 |
| Bazilah Ismail | University of Kuala Lumpur | 1 |
| M. R. Bin Hamzah | University of Kuala Lumpur | 1 |
| Azhar Khairuddin | University of Technology Malaysia | 1 |
| Mohd Khairil Rahmat | University of Kuala Lumpur | 1 |
| Farouk Ismail | University of Kuala Lumpur | 1 |
| Lilik Jamilatul Awalin | Universitas Airlangga | 1 |
| Muhammad Iskandar Iskandar | University of Kuala Lumpur | 1 |
| M. A. Hairullah | University of Kuala Lumpur | 1 |
| Nihal Omar | University of Kuala Lumpur | 1 |
| Yonis M. Buswig | Universiti Malaysia Sarawak | 1 |
| Mazin Mustafa Mahdi | Afiliasi tidak diketahui | 1 |
| Ekhlas Mhawi Thajeel | Universiti Malaysia Pahang Al-Sultan Abdullah | 1 |
| Taha Ahmed Hussein | Northern Technical University | 1 |
| Jawad Hasan Alkhateeb | Prince Mohammad bin Fahd University | 1 |
| Osaj Emmanuel | Afiliasi tidak diketahui | 1 |
| Mohammad Lutfi Othman | Universiti Putra Malaysia | 1 |
| Hashim Hizam | Universiti Putra Malaysia | 1 |
| Ishak b. Aris | Universiti Putra Malaysia | 1 |
| Noor Izzri Abdul Wahab | Universiti Putra Malaysia | 1 |
| Musa Mohammed Gujja | Universiti Sains Malaysia | 1 |
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