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PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-ilhamlı Algoritma

Yıl 2019, Cilt: 22 Sayı: 2, 453 - 460, 01.06.2019
https://doi.org/10.2339/politeknik.417765

Öz

Güç sistemi kararlı kılıcısı (PSS),
düşük frekanslı salınımların bastırılması için etkili bir araçtır. Bu makalede,
tek makinalı sonsuz baralı (TMSB) şebeke için Oransal İntegral Türevsel (PID)
PSS'nin optimal tasarımında yeni bir algoritma kullanılmıştır. Kontrolör
tasarım problemi, bir optimizasyon problemine dönüştürüldü ve kontrolörün PID
parametreleri, güçlü bir optimizasyon metodu olan böbrek-ilhamlı algoritma (KA)
kullanılarak ayarlandı. Yeni tasarımlanmış PIDPSS'in verimliliği, diferansiyel
evrim (DE) ve yapay arı kolonisi algoritması (ABC) tabanlı PIDPSS tasarım
yöntemlerine kıyaslanarak büyük ve küçük arızalar altındaki TMSB'ye uygulandı.
Lineer olmayan zaman domeni simülasyon sonuçları, önerilen KA tabanlı
kontrolörün (KA-PIDPSS) diğer yöntemlere göre daha mükemmel bir sönümleme
performansı sağladığını göstermektedir.

Kaynakça

  • [1] Guesmi T., Alshammari B.M., “An improved artificial bee colony algorithm for robust design of power system stabilizers”, Engineering Computations, 34(7): 2131-2153, (2017).
  • [2] Rogers G., “Power System Oscillations”, Kluwer Academic Publishers, Boston, (2000).
  • [3] Ghasemi A., Shayeghi H. and Alkhatib H., “Robust design of multimachine power system stabilizers using fuzzy gravitational search algorithm”. International Journal of Electrical Power & Energy Systems, 51: 190-200, (2013).
  • [4] Chow J.H. and Sanchez-Gasca J.J., “Pole-placement designs of power system stabilizers”, IEEE Transactions on Power Systems, 4(1): 271-277, (1989).
  • [5] Sebaa K. and Boudour M., “Optimal locations and tuning of robust power system stabilizer using genetic algorithms”, Electric Power Systems Research, 79(2): 406-416, (2009)
  • [6] Hassan L.H., Moghavvemi M., Almurib H.A., Muttaqi K.M. and Ganapathy V.G., “Optimization of power system stabilizers using participation factor and genetic algorithm” International Journal of Electrical Power & Energy Systems, 55: 668-679, (2014).
  • [7] Ekinci S. and Demiroren A., “PSO based PSS design for transient stability enhancement”, IU-Journal of Electrical & Electronics Engineering, 15(1): 1855-1862, (2015).
  • [8] Labdelaoui H., Boudjema F. and Boukhetala D., “A multiobjective tuning approach of power system stabilizers using particle swarm optimization”, Turkish Journal of Electrical Engineering & Computer Sciences, 24(5): 3898-3909, (2016).
  • [9] Sun Z., Wang N., Srinivasan D. and Bi Y., “Optimal tunning of type-2 fuzzy logic power system stabilizer based on differential evolution algorithm”, International Journal of Electrical Power & Energy Systems, 62: 19-28, (2014).
  • [10] Sambariya D.K. and Prasad R., “Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm” International Journal of Electrical Power & Energy Systems, 61: 229-238, (2014).
  • [11] Abd-Elazim S.M. and Ali E.S., “Power system stability enhancement via bacteria foraging optimization algorithm” Arabian Journal for Science and Engineering, 38(3): 599-611, (2013).
  • [12] Eke İ., Taplamacıoğlu M.C., Kocaarslan İ., “Design of robust power system stabilizer based on Artificial Bee Colony Algorithm”, Journal of the Faculty of Engineering and Architecture of Gazi University, 26(3): 683-690, (2011).
  • [13] Ekinci S. and Demiroren A., “Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm”, Turkish Journal of Electrical Engineering & Computer Sciences, 24(3): 1532-1546, (2016).
  • [14] Hameed K.A. and Palani S., “Robust design of power system stabilizer using harmony search algorithm”, Automatika, 55(2): 162-169, (2014).
  • [15] Elazim S.A. and Ali E.S., “Optimal power system stabilizers design via cuckoo search algorithm”, International Journal of Electrical Power & Energy Systems, 75: 99-107, (2016).
  • [16] Ekinci S., Hekimoğlu B., “Multi-machine power system stabilizer design via HPA algorithm”, Journal of the Faculty of Engineering and Architecture of Gazi University, 32(4): 1271-1285, (2017).
  • [17] Islam N.N., Hannan M.A., Shareef H. and Mohamed A., “An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system”, Neurocomputing, 237: 175-184, (2017).
  • [18] Farah A., Guesmi T. and Abdallah H.H., “A new method for the coordinated design of power system damping controllers”, Engineering Applications of Artificial Intelligence, 64: 325-339, (2017).
  • [19] Jaddi N.S., Alvankarian J. and Abdullah S., “Kidney-inspired algorithm for optimization problems”, Communications in Nonlinear Science and Numerical Simulation, 42: 358-369, (2017).
  • [20] Taqi M.K. and Ali R., “Obka-Fs: An Oppositional-Based Binary Kidneyinspired Search Algorithm for Feature Selection”, Journal of Theoretical and Applied Information Technology, 95(1): 9-23, (2017).
  • [21] Liang Y., Niu D., Wang H. and Chen H., “Assessment Analysis and Forecasting for Security Early Warning of Energy Consumption Carbon Emissions in Hebei Province, China”, Energies, 10(3): 391, (2017).
  • [22] Hall J.E. “Guyton and Hall textbook of medical physiology”, Elsevier Health Sciences, (2015).
  • [23] Jaddi N.S. and Abdullah S., “Optimization of neural network using kidney-inspired algorithm with control of filtration rate and chaotic map for real-world rainfall forecasting”, Engineering Applications of Artificial Intelligence, 67: 246-259, (2018).
  • [24] Sauer P.W., Pai M.A., Chow, J.H., “Power System Dynamics and Stability: With Synchrophasor Measurement and Power System Toolbox”, Hoboken, NJ, USA: IEEE Press, Wiley, (2017).
  • [25] Mondal D., Chakrabarti A., Sengupta A., “Power System Small Signal Stability Analysis and Control”, Academic Press, London, (2014).
  • [26] Dorf R.C., Bishop R.H., “Modern Control Systems”, Prentice Hall, (2010).
  • [27] Shayeghi H., Shayanfar H.A., Asefi S. and Younesi A., “Optimal Tuning and Comparison of Different Power System Stabilizers Using Different Performance Indices Via Jaya Algorithm”, In Proceedings of the International Conference on Scientific Computing (CSC), 34-40, (2016).

Kidney-inspired Algorithm for Determination of PID Power System Stabilizer Parameters

Yıl 2019, Cilt: 22 Sayı: 2, 453 - 460, 01.06.2019
https://doi.org/10.2339/politeknik.417765

Öz

Power system stabilizer (PSS) is an operative tool for
the suppression of low frequency oscillations. In this article, a novel
algorithm is used for the optimal design of Proportional Integral Derivative
(PID) PSS for a single machine infinite bus (SMIB) network. The controller
design problem is converted to an optimization problem and the PID parameters
of controller are tuned by using kidney-inspired algorithm (KA) which is a
powerful optimization method. The efficiency of the newly designed PIDPSS is
applied to the SMIB under large and small disturbances in comparison with the
differential evolution (DE) and artificial bee colony algorithm (ABC) based
PIDPSS design methods. Nonlinear time-domain simulation results show that the
proposed KA based controller (KA-PIDPSS) gives an excellent damping performance
compared to other methods.

Kaynakça

  • [1] Guesmi T., Alshammari B.M., “An improved artificial bee colony algorithm for robust design of power system stabilizers”, Engineering Computations, 34(7): 2131-2153, (2017).
  • [2] Rogers G., “Power System Oscillations”, Kluwer Academic Publishers, Boston, (2000).
  • [3] Ghasemi A., Shayeghi H. and Alkhatib H., “Robust design of multimachine power system stabilizers using fuzzy gravitational search algorithm”. International Journal of Electrical Power & Energy Systems, 51: 190-200, (2013).
  • [4] Chow J.H. and Sanchez-Gasca J.J., “Pole-placement designs of power system stabilizers”, IEEE Transactions on Power Systems, 4(1): 271-277, (1989).
  • [5] Sebaa K. and Boudour M., “Optimal locations and tuning of robust power system stabilizer using genetic algorithms”, Electric Power Systems Research, 79(2): 406-416, (2009)
  • [6] Hassan L.H., Moghavvemi M., Almurib H.A., Muttaqi K.M. and Ganapathy V.G., “Optimization of power system stabilizers using participation factor and genetic algorithm” International Journal of Electrical Power & Energy Systems, 55: 668-679, (2014).
  • [7] Ekinci S. and Demiroren A., “PSO based PSS design for transient stability enhancement”, IU-Journal of Electrical & Electronics Engineering, 15(1): 1855-1862, (2015).
  • [8] Labdelaoui H., Boudjema F. and Boukhetala D., “A multiobjective tuning approach of power system stabilizers using particle swarm optimization”, Turkish Journal of Electrical Engineering & Computer Sciences, 24(5): 3898-3909, (2016).
  • [9] Sun Z., Wang N., Srinivasan D. and Bi Y., “Optimal tunning of type-2 fuzzy logic power system stabilizer based on differential evolution algorithm”, International Journal of Electrical Power & Energy Systems, 62: 19-28, (2014).
  • [10] Sambariya D.K. and Prasad R., “Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm” International Journal of Electrical Power & Energy Systems, 61: 229-238, (2014).
  • [11] Abd-Elazim S.M. and Ali E.S., “Power system stability enhancement via bacteria foraging optimization algorithm” Arabian Journal for Science and Engineering, 38(3): 599-611, (2013).
  • [12] Eke İ., Taplamacıoğlu M.C., Kocaarslan İ., “Design of robust power system stabilizer based on Artificial Bee Colony Algorithm”, Journal of the Faculty of Engineering and Architecture of Gazi University, 26(3): 683-690, (2011).
  • [13] Ekinci S. and Demiroren A., “Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm”, Turkish Journal of Electrical Engineering & Computer Sciences, 24(3): 1532-1546, (2016).
  • [14] Hameed K.A. and Palani S., “Robust design of power system stabilizer using harmony search algorithm”, Automatika, 55(2): 162-169, (2014).
  • [15] Elazim S.A. and Ali E.S., “Optimal power system stabilizers design via cuckoo search algorithm”, International Journal of Electrical Power & Energy Systems, 75: 99-107, (2016).
  • [16] Ekinci S., Hekimoğlu B., “Multi-machine power system stabilizer design via HPA algorithm”, Journal of the Faculty of Engineering and Architecture of Gazi University, 32(4): 1271-1285, (2017).
  • [17] Islam N.N., Hannan M.A., Shareef H. and Mohamed A., “An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system”, Neurocomputing, 237: 175-184, (2017).
  • [18] Farah A., Guesmi T. and Abdallah H.H., “A new method for the coordinated design of power system damping controllers”, Engineering Applications of Artificial Intelligence, 64: 325-339, (2017).
  • [19] Jaddi N.S., Alvankarian J. and Abdullah S., “Kidney-inspired algorithm for optimization problems”, Communications in Nonlinear Science and Numerical Simulation, 42: 358-369, (2017).
  • [20] Taqi M.K. and Ali R., “Obka-Fs: An Oppositional-Based Binary Kidneyinspired Search Algorithm for Feature Selection”, Journal of Theoretical and Applied Information Technology, 95(1): 9-23, (2017).
  • [21] Liang Y., Niu D., Wang H. and Chen H., “Assessment Analysis and Forecasting for Security Early Warning of Energy Consumption Carbon Emissions in Hebei Province, China”, Energies, 10(3): 391, (2017).
  • [22] Hall J.E. “Guyton and Hall textbook of medical physiology”, Elsevier Health Sciences, (2015).
  • [23] Jaddi N.S. and Abdullah S., “Optimization of neural network using kidney-inspired algorithm with control of filtration rate and chaotic map for real-world rainfall forecasting”, Engineering Applications of Artificial Intelligence, 67: 246-259, (2018).
  • [24] Sauer P.W., Pai M.A., Chow, J.H., “Power System Dynamics and Stability: With Synchrophasor Measurement and Power System Toolbox”, Hoboken, NJ, USA: IEEE Press, Wiley, (2017).
  • [25] Mondal D., Chakrabarti A., Sengupta A., “Power System Small Signal Stability Analysis and Control”, Academic Press, London, (2014).
  • [26] Dorf R.C., Bishop R.H., “Modern Control Systems”, Prentice Hall, (2010).
  • [27] Shayeghi H., Shayanfar H.A., Asefi S. and Younesi A., “Optimal Tuning and Comparison of Different Power System Stabilizers Using Different Performance Indices Via Jaya Algorithm”, In Proceedings of the International Conference on Scientific Computing (CSC), 34-40, (2016).
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Serdar Ekinci

Baran Hekimoğlu Bu kişi benim

Ethem Uysal Bu kişi benim

Yayımlanma Tarihi 1 Haziran 2019
Gönderilme Tarihi 10 Şubat 2018
Yayımlandığı Sayı Yıl 2019 Cilt: 22 Sayı: 2

Kaynak Göster

APA Ekinci, S., Hekimoğlu, B., & Uysal, E. (2019). PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-ilhamlı Algoritma. Politeknik Dergisi, 22(2), 453-460. https://doi.org/10.2339/politeknik.417765
AMA Ekinci S, Hekimoğlu B, Uysal E. PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-ilhamlı Algoritma. Politeknik Dergisi. Haziran 2019;22(2):453-460. doi:10.2339/politeknik.417765
Chicago Ekinci, Serdar, Baran Hekimoğlu, ve Ethem Uysal. “PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-Ilhamlı Algoritma”. Politeknik Dergisi 22, sy. 2 (Haziran 2019): 453-60. https://doi.org/10.2339/politeknik.417765.
EndNote Ekinci S, Hekimoğlu B, Uysal E (01 Haziran 2019) PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-ilhamlı Algoritma. Politeknik Dergisi 22 2 453–460.
IEEE S. Ekinci, B. Hekimoğlu, ve E. Uysal, “PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-ilhamlı Algoritma”, Politeknik Dergisi, c. 22, sy. 2, ss. 453–460, 2019, doi: 10.2339/politeknik.417765.
ISNAD Ekinci, Serdar vd. “PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-Ilhamlı Algoritma”. Politeknik Dergisi 22/2 (Haziran 2019), 453-460. https://doi.org/10.2339/politeknik.417765.
JAMA Ekinci S, Hekimoğlu B, Uysal E. PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-ilhamlı Algoritma. Politeknik Dergisi. 2019;22:453–460.
MLA Ekinci, Serdar vd. “PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-Ilhamlı Algoritma”. Politeknik Dergisi, c. 22, sy. 2, 2019, ss. 453-60, doi:10.2339/politeknik.417765.
Vancouver Ekinci S, Hekimoğlu B, Uysal E. PID Güç Sistemi Kararlı Kılıcısı Parametrelerinin Belirlenmesi için Böbrek-ilhamlı Algoritma. Politeknik Dergisi. 2019;22(2):453-60.
 
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