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Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm

Year 2021, Volume: 9 Issue: 6 - ICAIAME 2021, 95 - 111, 31.12.2021

Enes Kaymaz , Uğur Güvenç , Mehmet Kenan Döşoğlu

https://doi.org/10.29130/dubited.1015460

Abstract

Low-frequency oscillations due to unpredictable disturbances in an interconnected power grid are a serious threat to the stability of the power system. Reliable operation of a modern power system, when exposed to sudden disturbances, is crucial, and the safe operation of the system is directly related to success in damping oscillations. Power System Stabilizer (PSS) devices have been used to reduce fluctuations caused by short-time disturbances in power systems. These devices provide additional damping torque components to the generators as an auxiliary control device of the excitation system. Due to the non-linearity of electrical power systems, it is significant to design multi-machine power systems with optimum PSS parameters under critical conditions. In this paper, the PSS design problem was solved using the Runge Kutta Algorithm (RUN). The PSS design problem was considered an optimization problem in which an eigenvalue-based objective function has developed, and the proposed RUN method was tested in a WSCC 3-machine 9-bus test system using the linearized Heffron-Phillips model. In the linearized model, system stability has been enhanced by shifting the eigenvalues to the stability regions. When the results obtained from the test system are examined, it has seen that the proposed RUN is the most effective method in terms of system stability.

Keywords

Power system stabilizer Runge Kutta algorithm Eigenvalue Heffron-Phillips model.

References

  • [1] R. Devarapalli, B. Bhattacharyya and J.K. Saw, “Controller Parameter Tuning of A Single Machine Infinite Bus System with Static Synchronous Compensator Using Antlion Optimization Algorithm for The Power System Stability Improvement,” Advanced Control for Applications: Engineering and Industrial Systems, vol. 2, no. 3, pp. e45, 2020.
  • [2] P. Kundur, “Power system stability,” Power system stability and control, Mc-Graw Hill, New York 1994.
  • [3] D. Mondal, A. Chakrabarti and A. Sengupta, Power system small signal stability analysis and control, Academic Press, 2020.
  • [4] R. Devarapalli and B. Bhattacharyya, “A hybrid modified grey wolf optimization‐sine cosine algorithm‐based power system stabilizer parameter tuning ın a multimachine power system,” Optimal Control Applications and Methods, vol. 41, no. 4, pp. 1143-1159, 2020.
  • [5] F.Alias and M. Singh “Damping sensitivity analysis and optimized battery controller for small-signal stability enhancement in wind penetrated networks,” Sustainable Energy, Grids and Networks, vol. 26, no. 100441, 2021.
  • [6] R.A. Ramos, A.C.P. Martins and N.G. Bretas, “An improved methodology for the design of power system damping controllers,” IEEE Transactions on Power Systems, vol. 20 no. 4, pp. 1938–1945, 2005.
  • [7] M.A Hannan, N.N. Islam, A. Mohamed, M.S.H. Lipu, P.J. Ker, M.M. Rashid and H. Shareef, “Artificial ıntelligent based damping controller optimization for the multi-machine power system: A Review,” IEEE Access, vol. 6, pp. 39574-39594, 2018.
  • [8] F.P. Demello, and C. Concordia, “Concepts of synchronous machine stability as affected by excitation control,” IEEE Transactions on power apparatus and systems, vol. 88, no. 4, pp. 316-329, 1969.
  • [9] M.J. Gibbard, “Coordinated design of multimachine power system stabilisers based on damping torque concepts,” IEE Proceedings - Generation, Transmission and Distribution., vol. 135, no. 4, pp. 276.1988.
  • [10] P. Kundur, M. Klein, G.J. Rogers and M.S. Zywno, “Application of power system stabilizers for enhancement of overall system stability,” IEEE Transactions on Power Systems, vol. 4, no. 2, pp. 614–626, 1989.
  • [11] Y.L. Abdel-Magid and M.A. Abido, “ Optimal multiobjective design of robust power system stabilizers using genetic algorithms,” IEEE Transactions on Power Systems, vol. 18, no. 3, pp. 1125–1132, 2003.
  • [12] R. Gupta, B. Bandyopadhyay and A.M. Kulkarnii, “Design of power system stabilizer for single machine system using robust fast output sampling feedback technique,” Electric Power Systems Research, vol. 65, no. 3, pp. 247-257, 2003.
  • [13]. I. Yazici and A. Özdemir, “Observer-based model following discrete sliding mode pss for single machine system,” European Transactions on Electrical Power, vol. 22, no. 3, pp. 378-390,2012.
  • [14] M. Aldeen, “Multimachine power system stabilizer design based on new LQR approach,” IEE Proceedings - Generation, Transmission and Distribution, vol. 142 ,no. 5, pp. 494,1995.
  • [15] H.S. Ko, K.Y Lee and H.C. Kim, “An intelligent based LQR controller design to power system stabilization,” Electric Power Systems Research, vol.71, no. 1, pp. 1-9, 2004.
  • [16] T. Yang, “Applying H∞ optimization method to power system stabilizer design part 1: single-machine infinite-bus systems,” International Journal of Electrical Power & Energy Systems, vol. 19, no. 1, pp. 29-35, 1997.
  • [17] S.F. Hardiansyah and J. Irisawa, “ A robust H∞ power system stabilizer design using reduced-order models,” International Journal of Electrical Power & Energy Systems, vol. 28, no. 1, pp. 21-28, 2006.
  • [18] P. Hoang and K. Tomsovic K. “Design and analysis of an adaptive fuzzy power system stabilizer,” IEEE Transactions on Energy Conversion, vol. 11, no. 2, pp. 455-461,1996.
  • [19] N. Ghadimi “ A new hybrid algorithm based on optimal fuzzy controller in multimachine power system,” Complexity, vol. 21, no. 1, pp.78-93, 2015.
  • [20] M.A Abido “Pole placement technique for pss and tcsc-based stabilizer design using simulated annealing,” International Journal of Electrical Power & Energy Systems, vol. 22, no. 8, pp. 543-554, 2000.
  • [21] P. Zhao, W. Yao, S.Wang , J. Wen and S. Cheng, “ Decentralized nonlinear synergetic power system stabilizers design for power system stability enhancement,” International Transactions on Electrical Energy Systems, vol. 24, no. 9, pp. 1356-1368, 2014.
  • [22] A. Ghosh, G. Ledwich, O.P. Malik, and G.S. Hope, “ power system stabilizer based on adaptive control techniques,” IEEE Transactions on Power Apparatus and Systems, vol. PAS-103, no.8, pp. 1983-1989, 1984.
  • [23] G. Naresh, M.R. Raju, K. Ravindra and S.V.L. Narasimham, “ Optimal design of multimachine power system stabilizer using genetic algorithm,” Innovative Systems Design and Engineering, vol. 2, no. 4, pp. 54–70, 2011. [24] H. Alkhatib and J. Duveau “ Dynamic genetic algorithms for robust design of multimachine power system stabilizers,” International Journal of Electrical Power & Energy Systems, vol. 45, pp. 242–251, 2013.
  • [25] MA. Abido, “ Optimal design of power-system stabilizers using particle swarm optimization,” IEEE Transactions on Energy Conversion, vol. 17, no. 3, pp. 406-413, 2002.
  • [26] H.E. Mostafa, M.A El-Sharkawy, A.A Emary and K. Yassin K, “ Design and allocation of power system stabilizers using the particle swarm optimization technique for an interconnected power system,” International Journal of Electrical Power & Energy Systems vol. 34, no. 1, pp. 57–65, 2012.
  • [27] M.A. Abido, “A novel approach to conventional power system stabilizer design using tabu search,” International Journal of Electrical Power & Energy Systems, vol. 21 no. 6, pp. 443-454,1999.
  • [28] E. Ali, “Optimization of power system stabilizers using bat search algorithm,” International Journal of Electrical Power & Energy Systems, vol. 61, pp. 683–690, 2014.
  • [29] D. Sambariya and R. Prasad, “ Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm,” International Journal of Electrical Power & Energy Systems vol. 61, pp. 229–238, 2014.
  • [30] S.A. Elazim and E. Ali, “ Optimal power system stabilizers design via cuckoo search algorithm,” International Journal of Electrical Power & Energy Systems, vol. 75, pp. 99–107, 2016.
  • [31] M. Mohammadi and N. Ghadimi, “ Optimal location and optimized parameters for robust power system stabilizer using honeybee mating optimization,” Complexity vol. 21, no. 1, 242–258, 2015.
  • [32] M. Singh, R.N. Patel and D.D Neema, “Robust tuning of excitation controller for stability enhancement using multi-objective metaheuristic firefly algorithm,” Swarm and Evolutionary Computation, vol. 2, no. 44, pp. 136-147, 2019.
  • [33] B.Dasu. M.Sivakumar and R. Srinivasarao, “ Interconnected multi-machine power system stabilizer design using whale optimization algorithm,” Protection and Control of Modern Power Systems, vol. 4, no. 1(2), 2019.
  • [34] A. Farah, T. Guesmi, H. Hadj Abdallah and A. Ouali, “A novel chaotic teaching–learning-based optimization algorithm for multi-machine power system stabilizers design problem,” International Journal of Electrical Power & Energy Systems, vol. 77, pp. 197–209, 2016.
  • [35] I. Ahmadianfar, A.A. Heidari, A.H. Gandomi, X. Chu and H. Chen, “RUN beyond the metaphor: an efficient optimization algorithm based on runge kutta method,” Expert Systems with Applications, 115079, 2021.
  • [36] S.Ekinci and B. Hekimoğlu, “ HPA algoritması ile çok makinalı güç sistemi kararlı kılıcısı tasarımı,” Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, c. 32, s. 4, ss. 1271-1286, 2017.
  • [37] P.W. Sauer, M.A. Pai, and J.H. Chow, Power system dynamics and stability: with synchrophasor measurement and power system toolbox, John Wiley & Sons, 2017.
  • [38] S. Mirjalili, “ The ant lion optimizer” Advances in Engineering Software, vol. 83, pp. 80–98, 2015.

Runge Kutta Algoritması Kullanılarak Güç Sistemi Kararlı Kılıcısı Parametrelerinin Ayarlanması

Year 2021, Volume: 9 Issue: 6 - ICAIAME 2021, 95 - 111, 31.12.2021

Enes Kaymaz , Uğur Güvenç , Mehmet Kenan Döşoğlu

https://doi.org/10.29130/dubited.1015460

Abstract

Enterkonnekte bir güç şebekesindeki öngörülemeyen bozulmalardan kaynaklanan düşük frekanslı salınımlar, güç sisteminin kararlılığı için ciddi bir tehdittir. Modern bir güç sisteminin ani kesintilere maruz kaldığında güvenilir şekilde çalışması çok önemlidir ve sistemin güvenli çalışması, salınımların sönümlenmesindeki başarı ile doğrudan ilişkilidir. Güç Sistemi Kararlı Kılıcıları (GSKK), güç sistemlerinde kısa süreli kesintilerden kaynaklanan dalgalanmaları azaltmak amacıyla kullanılmaktadır. Bu cihazlar, uyarma sisteminin yardımcı bir kontrol cihazı olarak, generatörlere ilave sönümleme torku bileşenleri sağlar. Elektrik güç sistemlerinin doğrusal olmaması nedeniyle, kritik koşullar altında en uygun PSS parametrelerine sahip çok makineli güç sistemleri tasarlamak önemlidir. Bu çalışmada, GSKK tasarım problemi Runge Kutta Algoritması (RUN) kullanılarak çözülmüştür. GSKK tasarım problemi, öz değer tabanlı bir amaç fonksiyonunun geliştirildiği bir optimizasyon problemi olarak düşünülmüş ve önerilen RUN yöntemi, doğrusallaştırılmış Heffron-Phillips modeli kullanılarak WSCC 3-makineli 9-baralı sistemde test edilmiştir. Doğrusallaştırılmış modelde, öz değerler kararlılık bölgelerine kaydırılarak sistem kararlılığı arttırılmıştır. Test sisteminden elde edilen sonuçlar incelendiğinde önerilen RUN yönteminin sistem kararlılığı açısından en etkili yöntem olduğu görülmüştür.

Keywords

Güç Sistemi Kararlı Kılıcısı Runge Kutta Algoritması Özdeğer Heffron-Phillips modeli

References

  • [1] R. Devarapalli, B. Bhattacharyya and J.K. Saw, “Controller Parameter Tuning of A Single Machine Infinite Bus System with Static Synchronous Compensator Using Antlion Optimization Algorithm for The Power System Stability Improvement,” Advanced Control for Applications: Engineering and Industrial Systems, vol. 2, no. 3, pp. e45, 2020.
  • [2] P. Kundur, “Power system stability,” Power system stability and control, Mc-Graw Hill, New York 1994.
  • [3] D. Mondal, A. Chakrabarti and A. Sengupta, Power system small signal stability analysis and control, Academic Press, 2020.
  • [4] R. Devarapalli and B. Bhattacharyya, “A hybrid modified grey wolf optimization‐sine cosine algorithm‐based power system stabilizer parameter tuning ın a multimachine power system,” Optimal Control Applications and Methods, vol. 41, no. 4, pp. 1143-1159, 2020.
  • [5] F.Alias and M. Singh “Damping sensitivity analysis and optimized battery controller for small-signal stability enhancement in wind penetrated networks,” Sustainable Energy, Grids and Networks, vol. 26, no. 100441, 2021.
  • [6] R.A. Ramos, A.C.P. Martins and N.G. Bretas, “An improved methodology for the design of power system damping controllers,” IEEE Transactions on Power Systems, vol. 20 no. 4, pp. 1938–1945, 2005.
  • [7] M.A Hannan, N.N. Islam, A. Mohamed, M.S.H. Lipu, P.J. Ker, M.M. Rashid and H. Shareef, “Artificial ıntelligent based damping controller optimization for the multi-machine power system: A Review,” IEEE Access, vol. 6, pp. 39574-39594, 2018.
  • [8] F.P. Demello, and C. Concordia, “Concepts of synchronous machine stability as affected by excitation control,” IEEE Transactions on power apparatus and systems, vol. 88, no. 4, pp. 316-329, 1969.
  • [9] M.J. Gibbard, “Coordinated design of multimachine power system stabilisers based on damping torque concepts,” IEE Proceedings - Generation, Transmission and Distribution., vol. 135, no. 4, pp. 276.1988.
  • [10] P. Kundur, M. Klein, G.J. Rogers and M.S. Zywno, “Application of power system stabilizers for enhancement of overall system stability,” IEEE Transactions on Power Systems, vol. 4, no. 2, pp. 614–626, 1989.
  • [11] Y.L. Abdel-Magid and M.A. Abido, “ Optimal multiobjective design of robust power system stabilizers using genetic algorithms,” IEEE Transactions on Power Systems, vol. 18, no. 3, pp. 1125–1132, 2003.
  • [12] R. Gupta, B. Bandyopadhyay and A.M. Kulkarnii, “Design of power system stabilizer for single machine system using robust fast output sampling feedback technique,” Electric Power Systems Research, vol. 65, no. 3, pp. 247-257, 2003.
  • [13]. I. Yazici and A. Özdemir, “Observer-based model following discrete sliding mode pss for single machine system,” European Transactions on Electrical Power, vol. 22, no. 3, pp. 378-390,2012.
  • [14] M. Aldeen, “Multimachine power system stabilizer design based on new LQR approach,” IEE Proceedings - Generation, Transmission and Distribution, vol. 142 ,no. 5, pp. 494,1995.
  • [15] H.S. Ko, K.Y Lee and H.C. Kim, “An intelligent based LQR controller design to power system stabilization,” Electric Power Systems Research, vol.71, no. 1, pp. 1-9, 2004.
  • [16] T. Yang, “Applying H∞ optimization method to power system stabilizer design part 1: single-machine infinite-bus systems,” International Journal of Electrical Power & Energy Systems, vol. 19, no. 1, pp. 29-35, 1997.
  • [17] S.F. Hardiansyah and J. Irisawa, “ A robust H∞ power system stabilizer design using reduced-order models,” International Journal of Electrical Power & Energy Systems, vol. 28, no. 1, pp. 21-28, 2006.
  • [18] P. Hoang and K. Tomsovic K. “Design and analysis of an adaptive fuzzy power system stabilizer,” IEEE Transactions on Energy Conversion, vol. 11, no. 2, pp. 455-461,1996.
  • [19] N. Ghadimi “ A new hybrid algorithm based on optimal fuzzy controller in multimachine power system,” Complexity, vol. 21, no. 1, pp.78-93, 2015.
  • [20] M.A Abido “Pole placement technique for pss and tcsc-based stabilizer design using simulated annealing,” International Journal of Electrical Power & Energy Systems, vol. 22, no. 8, pp. 543-554, 2000.
  • [21] P. Zhao, W. Yao, S.Wang , J. Wen and S. Cheng, “ Decentralized nonlinear synergetic power system stabilizers design for power system stability enhancement,” International Transactions on Electrical Energy Systems, vol. 24, no. 9, pp. 1356-1368, 2014.
  • [22] A. Ghosh, G. Ledwich, O.P. Malik, and G.S. Hope, “ power system stabilizer based on adaptive control techniques,” IEEE Transactions on Power Apparatus and Systems, vol. PAS-103, no.8, pp. 1983-1989, 1984.
  • [23] G. Naresh, M.R. Raju, K. Ravindra and S.V.L. Narasimham, “ Optimal design of multimachine power system stabilizer using genetic algorithm,” Innovative Systems Design and Engineering, vol. 2, no. 4, pp. 54–70, 2011. [24] H. Alkhatib and J. Duveau “ Dynamic genetic algorithms for robust design of multimachine power system stabilizers,” International Journal of Electrical Power & Energy Systems, vol. 45, pp. 242–251, 2013.
  • [25] MA. Abido, “ Optimal design of power-system stabilizers using particle swarm optimization,” IEEE Transactions on Energy Conversion, vol. 17, no. 3, pp. 406-413, 2002.
  • [26] H.E. Mostafa, M.A El-Sharkawy, A.A Emary and K. Yassin K, “ Design and allocation of power system stabilizers using the particle swarm optimization technique for an interconnected power system,” International Journal of Electrical Power & Energy Systems vol. 34, no. 1, pp. 57–65, 2012.
  • [27] M.A. Abido, “A novel approach to conventional power system stabilizer design using tabu search,” International Journal of Electrical Power & Energy Systems, vol. 21 no. 6, pp. 443-454,1999.
  • [28] E. Ali, “Optimization of power system stabilizers using bat search algorithm,” International Journal of Electrical Power & Energy Systems, vol. 61, pp. 683–690, 2014.
  • [29] D. Sambariya and R. Prasad, “ Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm,” International Journal of Electrical Power & Energy Systems vol. 61, pp. 229–238, 2014.
  • [30] S.A. Elazim and E. Ali, “ Optimal power system stabilizers design via cuckoo search algorithm,” International Journal of Electrical Power & Energy Systems, vol. 75, pp. 99–107, 2016.
  • [31] M. Mohammadi and N. Ghadimi, “ Optimal location and optimized parameters for robust power system stabilizer using honeybee mating optimization,” Complexity vol. 21, no. 1, 242–258, 2015.
  • [32] M. Singh, R.N. Patel and D.D Neema, “Robust tuning of excitation controller for stability enhancement using multi-objective metaheuristic firefly algorithm,” Swarm and Evolutionary Computation, vol. 2, no. 44, pp. 136-147, 2019.
  • [33] B.Dasu. M.Sivakumar and R. Srinivasarao, “ Interconnected multi-machine power system stabilizer design using whale optimization algorithm,” Protection and Control of Modern Power Systems, vol. 4, no. 1(2), 2019.
  • [34] A. Farah, T. Guesmi, H. Hadj Abdallah and A. Ouali, “A novel chaotic teaching–learning-based optimization algorithm for multi-machine power system stabilizers design problem,” International Journal of Electrical Power & Energy Systems, vol. 77, pp. 197–209, 2016.
  • [35] I. Ahmadianfar, A.A. Heidari, A.H. Gandomi, X. Chu and H. Chen, “RUN beyond the metaphor: an efficient optimization algorithm based on runge kutta method,” Expert Systems with Applications, 115079, 2021.
  • [36] S.Ekinci and B. Hekimoğlu, “ HPA algoritması ile çok makinalı güç sistemi kararlı kılıcısı tasarımı,” Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, c. 32, s. 4, ss. 1271-1286, 2017.
  • [37] P.W. Sauer, M.A. Pai, and J.H. Chow, Power system dynamics and stability: with synchrophasor measurement and power system toolbox, John Wiley & Sons, 2017.
  • [38] S. Mirjalili, “ The ant lion optimizer” Advances in Engineering Software, vol. 83, pp. 80–98, 2015.
There are 37 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Enes Kaymaz 0000-0002-4774-0773

Uğur Güvenç 0000-0002-5193-7990

Mehmet Kenan Döşoğlu 0000-0001-8804-7070

Publication Date December 31, 2021
Published in Issue Year 2021 Volume: 9 Issue: 6 - ICAIAME 2021

Cite

APA Kaymaz, E., Güvenç, U., & Döşoğlu, M. K. (2021). Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm. Duzce University Journal of Science and Technology, 9(6), 95-111. https://doi.org/10.29130/dubited.1015460
AMA Kaymaz E, Güvenç U, Döşoğlu MK. Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm. DUBİTED. December 2021;9(6):95-111. doi:10.29130/dubited.1015460
Chicago Kaymaz, Enes, Uğur Güvenç, and Mehmet Kenan Döşoğlu. “Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm”. Duzce University Journal of Science and Technology 9, no. 6 (December 2021): 95-111. https://doi.org/10.29130/dubited.1015460.
EndNote Kaymaz E, Güvenç U, Döşoğlu MK (December 1, 2021) Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm. Duzce University Journal of Science and Technology 9 6 95–111.
IEEE E. Kaymaz, U. Güvenç, and M. K. Döşoğlu, “Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm”, DUBİTED, vol. 9, no. 6, pp. 95–111, 2021, doi: 10.29130/dubited.1015460.
ISNAD Kaymaz, Enes et al. “Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm”. Duzce University Journal of Science and Technology 9/6 (December 2021), 95-111. https://doi.org/10.29130/dubited.1015460.
JAMA Kaymaz E, Güvenç U, Döşoğlu MK. Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm. DUBİTED. 2021;9:95–111.
MLA Kaymaz, Enes et al. “Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm”. Duzce University Journal of Science and Technology, vol. 9, no. 6, 2021, pp. 95-111, doi:10.29130/dubited.1015460.
Vancouver Kaymaz E, Güvenç U, Döşoğlu MK. Tuning the Parameters of Power System Stabilizer Using Runge Kutta Algorithm. DUBİTED. 2021;9(6):95-111.
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