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Simulation Analysis of Control System in an Innovative Magnetically-Saturated Controllable Reactor

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DOI: 10.4236/jpee.2014.24054    3,098 Downloads   3,680 Views   Citations

ABSTRACT

Controllable saturation reactors are widely used in reactive power compensation. The control system of controllable saturation reactor determines adaption speed, accuracy, and stability. First, an innovative type of controllable saturation reactor is introduced. After that the control system is designed, and a self-tuning algorithm in PID controller is proposed in the paper. The algorithm tunes PID parameters automatically with different error signals caused by varied loads in power system. Then the feasibility of the above algorithm is verified by Simulink module of Matlab software. The results of simulation indicate that the control system can efficiently reduce adaption time and overshoot.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Jin, X. , Zhang, G. and Guo, R. (2014) Simulation Analysis of Control System in an Innovative Magnetically-Saturated Controllable Reactor. Journal of Power and Energy Engineering, 2, 403-410. doi: 10.4236/jpee.2014.24054.

References

[1] Wang, H. (2007) Steady-State Analysis of Power Systems (3rd Version). China Electric Power Press, Beijing.
[2] Tian, M.X., Li, Q.F. and Wang, S.H. (2002) An Equivalent Physical Model and a Mathematical Model of the Controlled Saturable Rreactor. Transactions of China Electrotechnical Society, 17, 18-21.
[3] Feng, G.H., Wang, F.X. and Jin, W. (2001) Design Principles of Magnetically Controlled Reactor. Electrical Machines and Systems, 2001. Proceedings of the 5th International Conference on IEEE, 1, 212-214.
[4] Zhang, G.Q. and Li, K. (2012) High-Voltage Single Phase Controlled Saturable Rreactor.
[5] Astrom Karl, J. and Hagglund, T. (2006) Advancaed PID Control. ISA.
[6] Shen, Y.F., Wu, S.J. and Deng, F.L. (2002) A Survey of Intelligent PID Control. Industrial Instrumentation & Automation, 6, 11-24.
[7] Man, K.F., Chen, G.R. and Kwong, S. (2001) An Optimal Fuzzy PID Controller. IEEE Transactions on Industrial Electronics, 48, 757-765.
[8] Cao, J.-Y., Liang, J. and Cao, B.-G. (2005) Optimization of Fractional Order PID Controllers Based on Genetic Algorithms. Proceedings of 2005 International Conference, Guangzhou, 18-21 August 2005, 9, 5686-5689.
[9] S.-J. Li and Y.-X. Liu (2011) An Improved Approach to Nonlinear Dynamical System Identification Using PID Neural Networks. International Journal of Nonlinear Sciences and Numerical Simulation, 7, 177-182.

  
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