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Journals / Turkish Journal of Electrical Engineering and Computer Science / 2014 / Cilt: 22 - Sayı: 3

Control of SVC based on the sliding mode control method

Ercan KÖSE
Hakan KIZMAZ
Kadir ABACI
Saadettin AKSOY
Pages
605–619
Publication Date
2014-05-16
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that the GA sliding mode controller method is more effective than the ZNPI, GAPID, and LASMC controllers in voltage stability enhancement.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:A genetic algorithm (GA)-based sliding mode controller is proposed to improve the voltage stability of a power system with a static var compensator.
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Key Findings & Data:The proposed controller is examined for improving the load bus voltage, which changes under different demanding powers, and its performance for transient analysis is compared with the Ziegler--Nichols proportional-integral (ZNPI), Lyapunov-based sliding mode control (LASMC), and GA-based proportional-integral-derivative (GAPID) controllers.
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Conclusion & Impact:The results show that the GA sliding mode controller method is more effective than the ZNPI, GAPID, and LASMC controllers in voltage stability enhancement.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Genetic algorithm · sliding mode controller · static var compensator

Abstract

A genetic algorithm (GA)-based sliding mode controller is proposed to improve the voltage stability of a power system with a static var compensator. The proposed controller is examined for improving the load bus voltage, which changes under different demanding powers, and its performance for transient analysis is compared with the Ziegler--Nichols proportional-integral (ZNPI), Lyapunov-based sliding mode control (LASMC), and GA-based proportional-integral-derivative (GAPID) controllers. The dynamic equations, consisting of a 2-bus nonlinear system, are converted to a mathematical description of sliding mode techniques. The optimum values of the sliding mode controller and proportional-integral-derivative (PID) coefficients that are required are calculated using the GA technique. Output voltage performances are obtained based on the demanding powers, which are at a constant variation. In this process, sliding mode, ZNPI, GAPID, and LASMC controllers are preferred in order to control the system. The results show that the GA sliding mode controller method is more effective than the ZNPI, GAPID, and LASMC controllers in voltage stability enhancement.

Özet

A genetic algorithm (GA)-based sliding mode controller is proposed to improve the voltage stability of a power system with a static var compensator. The proposed controller is examined for improving the load bus voltage, which changes under different demanding powers, and its performance for transient analysis is compared with the Ziegler--Nichols proportional-integral (ZNPI), Lyapunov-based sliding mode control (LASMC), and GA-based proportional-integral-derivative (GAPID) controllers. The dynamic equations, consisting of a 2-bus nonlinear system, are converted to a mathematical description of sliding mode techniques. The optimum values of the sliding mode controller and proportional-integral-derivative (PID) coefficients that are required are calculated using the GA technique. Output voltage performances are obtained based on the demanding powers, which are at a constant variation. In this process, sliding mode, ZNPI, GAPID, and LASMC controllers are preferred in order to control the system. The results show that the GA sliding mode controller method is more effective than the ZNPI, GAPID, and LASMC controllers in voltage stability enhancement.

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Cite This Article

KÖSE, E., KIZMAZ, H., ABACI, K., AKSOY, S. (2014). Control of SVC based on the sliding mode control method. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 22 - Sayı: 3, 605–619. https://ajindex.com/articles/188459

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References (13)

  1. C. Jaipradidthan, “Adaptive neuro-fuzzy SVC for multimachine hybrid power system stability improvement with a long of double circuit transmission lines”, International Symposium on Neural Networks, pp. 668–673, 2005.
  2. A. Albakkar, O.P. Malik, “Adaptive neuro-fuzzy FACTS controller for transient stability enhancement”, 16th National power System Conference, pp. 237–242, 2010.
  3. M. Sridhar, K. Vaisakh, K. Murthy, “Adaptive PSO based tuning of PID-fuzzy and SVC-PI controllers for dynamic stability enhancement: a comparative analysis”, 2nd International Conference on Emerging Trends in Engineering and Technology, pp. 985–990, 2009.
  4. J. Wang, C. Fu, Y. Zhang, “SVC control system based on instantaneous reactive power theory and fuzzy PID”, IEEE Transactions on Industrial Electronics, Vol. 55, pp. 1658–1665, 2008.
  5. M.J. Laufenberg, M.A. Pai, K.R. Padiyar, “Hopf bifurcation control in power systems with static var compensators”, Electric Power and Energy Systems, Vol. 19, pp. 339–347, 1997.
  6. P. Kundur, Power System Stability and Control, New York, McGraw-Hill, 1993.
  7. J.R. Smith, D.A. Pierre, I. Sadighi, M.H. Nehrir, J.F. Hauer, “A supplementary adaptive var unit controller for power system damping”, IEEE Transactions on Power Systems, Vol. 4, pp. 1017–1023, 1989.
  8. L.F. Li, K.P. Liu, M. Li, “Intelligent control strategy of SVC”, IEEE/PES Transmission and Distribution Conference & Exhibition: Asia and Pacific, 2005.
  9. J. Lu, M.H. Nehrir, D.A. Pierre, “A fuzzy logic-based adaptive damping controller for static VAR compensator”, Electric Power Systems Research, Vol. 68, pp. 113–118, 2004.
  10. N. Karpagam, D. Devaraj, “Fuzzy logic control of static var compensator for power system damping”, International Journal of Electrical and Electronics Engineering, Vol. 28, pp. 625–631, 2009.
  11. J. Tie-zheng, C. Chen, C. Guo-yun, “Nonlinear optimal predictive controller for static var compensator to power system damping and to maintain voltage”, Frontiers of Electrical and Electronic Engineering in China, Vol. 4, pp. 380 −384, 2006.
  12. Y. Wang, H. Chen, R. Zhou, “A nonlinear controller design for SVC to improve power system voltage stability”, Electrical Power and Energy Systems, Vol. 22, pp. 463–470, 2000.
  13. R. Yan, Z.Y. Dong, T.K. Saha, J. Ma, “Nonlinear robust adaptive SVC controller design for power systems”, Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, pp. 1–7, 200 J.J. Slotine, W. Li, Applied Nonlinear Control, Englewood Cliffs, NJ,