Determination of Power System Stabilizer Parameters in Short Circuit Fault Analysis of Multi-Machine Test System with Electric Fish Optimization

Burak Kaya; İbrahim Eke

Makale detayları

Determination of Power System Stabilizer Parameters in Short Circuit Fault Analysis of Multi-Machine Test System with Electric Fish Optimization

Yazarlar:

Burak Kaya | İbrahim Eke

Yayıncı:

Kirikkale University

Ana Başlıklar:

Electrical Energy Transmission | Networks and Systems

Dergi:

International Journal of Engineering Research and Development Vol.16 Issue 2, pp.530-549

Belge Tipi:

Makale

Yayın Tarihi:

6/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001314833

pISSN:

1308-5506

Anahtar kelimeler:

Özet:

 In this article, the multi-machine testing system MMTS is proposed to be used in determining the parameters of conventional Power System Stabilizer PSS using Electric Fish Optimization EFO, which is a maintenance for the stability of oscillations in cases of short circuit faults of a power system. The problem of PSS parameters based on the error and time domain was used as the optimal parameters solution in dampening the rotor speed change ω instability on the MATLABPower Pss application by minimizing the intended capacity with the EFO team. The results of the performance results of the conventional Power System Stabilizer PSS in different short circuit fault situations recorded in the EFO solution result record. It has been observed that the PSS calculated with the EFO system dampens the instability of the rotor speed change ω in power processes, and that the functioning of the system is better in the performance of PSS and system PSS processes applied by the Artificial Bee Colony Algorithm ABC.

 In this article, the multi-machine testing system MMTS is proposed to be used in determining the parameters of conventional Power System Stabilizer PSS using Electric Fish Optimization EFO, which is a maintenance for the stability of oscillations in cases of short circuit faults of a power system. The problem of PSS parameters based on the error and time domain was used as the optimal parameters solution in dampening the rotor speed change ω instability on the MATLABPower Pss application by minimizing the intended capacity with the EFO team. The results of the performance results of the conventional Power System Stabilizer PSS in different short circuit fault situations recorded in the EFO solution result record. It has been observed that the PSS calculated with the EFO system dampens the instability of the rotor speed change ω in power processes, and that the functioning of the system is better in the performance of PSS and system PSS processes applied by the Artificial Bee Colony Algorithm ABC.

 In this article, the multi-machine testing system MMTS is proposed to be used in determining the parameters of conventional Power System Stabilizer PSS using Electric Fish Optimization EFO, which is a maintenance for the stability of oscillations in cases of short circuit faults of a power system. The problem of PSS parameters based on the error and time domain was used as the optimal parameters solution in dampening the rotor speed change ω instability on the MATLABPower Pss application by minimizing the intended capacity with the EFO team. The results of the performance results of the conventional Power System Stabilizer PSS in different short circuit fault situations recorded in the EFO solution result record. It has been observed that the PSS calculated with the EFO system dampens the instability of the rotor speed change ω in power processes, and that the functioning of the system is better in the performance of PSS and system PSS processes applied by the Artificial Bee Colony Algorithm ABC.

 Bu makale, çok makinalı test sisteminin MMTS bir güç sisteminin kısa devre arızası durumlarında salınımlarında kararlılık oluşması için bir sezgisel optimizasyon algoritması olan Elektrik Balığı Optimizasyonu EFO kullanarak geleneksel Güç Sistemi Dengeleyicisi PSS parametrelerinin belirlenmesinde kullanılması önerilmiştir. Hata ve zaman tanım bölgesi tabanlı PSS parametrelerine ait problemin, tasarlanan amaç fonksiyonları EFO tekniği ile minimum hale getirilerek rotor hız değişim ω kararsızlığının MATLABPower Pss uygulaması üzerinde sönümlenmesinde optimal parametreleri çözüm olarak kullanılmıştır. EFO optimizasyonu sonucu parametreleri belirlenen geleneksel Güç Sistemi Dengeleyicisinin PSS farklı kısa devre hataları durumlarındaki performans sonuçları incelenmiştir. EFO tekniği ile hesaplanmış PSSin güç sisteminde rotor hız değişimi ω kararsızlığını sönümlendirdiği, sistemin performansının Yapay Arı Kolonisi Algoritması ABC uygulanan PSS ve sistemde PSS kullanılmayan durumlar dikkate alındığında daha iyi olduğu gözlemlenmiştir.

Makale detayları

Determination of Power System Stabilizer Parameters in Short Circuit Fault Analysis of Multi-Machine Test System with Electric Fish Optimization

Yazarlar:

Burak Kaya | İbrahim Eke

Yayıncı:

Kirikkale University

Ana Başlıklar:

Electrical Energy Transmission | Networks and Systems

Dergi:

International Journal of Engineering Research and Development Vol.16 Issue 2, pp.530-549

Belge Tipi:

Makale

Yayın Tarihi:

6/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001314833

pISSN:

1308-5506

MATLAB

Power PSS

Power System Stabilizer

Rotor Speed Variation

Electric Fish Algorithm

MMTSMATLAB

Power PSS

Güç Sistemi Dengeleyicisi

Rotor Hız Değişimi

Elektrik Balıkları Algoritması

MMTS

Sayı

Makale detayları

Yazarlar: Burak Kaya | İbrahim Eke

Yayıncı: Kirikkale University

Ana Başlıklar: Electrical Energy Transmission | Networks and Systems

Dergi: International Journal of Engineering Research and Development Vol.16 Issue 2, pp.530-549

Belge Tipi: Makale

Yayın Tarihi: 6/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001314833

pISSN: 1308-5506

Sayı

Yazarlar:

Burak Kaya | İbrahim Eke

Yayıncı:

Kirikkale University

Ana Başlıklar:

Electrical Energy Transmission | Networks and Systems

Dergi:

International Journal of Engineering Research and Development Vol.16 Issue 2, pp.530-549

Belge Tipi:

Makale

Yayın Tarihi:

6/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001314833

pISSN:

1308-5506