Optimum Frequency Droop Control of Islanded Micro-grid Using PID-PSO Controller
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The voltage and frequency are two of the important parameters to ensure the safe operation of a micro-grid, particularly in the event of island operation. This paper presents a method to control the frequency of the synchronous generator in islanded micro-grid operation. The DC motor has been utilized as the prime mover of generator. The main objective of this paper is to control the DC motor speed rotation which will consequently control the output frequency. The PID controller has been used and the coefficients of PID controller have been tuned by Ziegler-Nichols (Z-N) and Particle Swarm Optimization (PSO) methods. This is to minimize the transient response of the DC motor speed control which are rise time, settling time and overshoot time. The results show the PID-PSO algorithm has better response in terms of settling and overshoot times as compared to the Z-N and Genetic Algorithm (GA) methods.
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A. M. Bollman, “An Experimental Study of Frequency Droop Control in a Low-Inertia Microgrid,” Faculty of Electrical & Computer Engineering, University of Illinois at Urbana-Champaign, Thesis, 2009.
M.Shamshiri, C. K.Gan, and C. W. Tan, "A review of recent development in smart grid and micro-grid laboratories", IEEE Conference on International Power Engineering and Optimization Techniques, Melaka, Malaysia, 2012 (pp. 367-372).
H.S.Hwang, J.N. Choi, W. H. Lee, and J.K. Kim. "A tuning algorithm for the PID controller utilizing fuzzy theory." IEEE International Joint Conference on Neural Networks, IJCNN'99, vol. 4, pp. 2210-2215, 1999.
J. Srinivas, Control systems and mechatronics. Alpha Science, 2007.
B. Nagaraj, S. Subha, and B. Rampriya, “Tuning algorithms for PID controller using soft computing techniques,” Int. J. Comput. Sci. Netw. Secur. IJCSNS, vol. 8, no. 4, pp. 278–281, 2008.
G. H. Cohen and G. A. Coon, “Theoretical investigations of retarded control,” Trans. Am. Soc. Mech. Eng., vol. 75, pp. 827–834, 1953.
M. Zhuang and D. Atherton, “Automatic tuning of optimum PID controllers,” IEE Proc. Control Theory Appl., vol. 140, no. 3, 1993.
D. W. Pessen, “A new look at PID-controller tuning,” J. Dyn. Syst. Meas. Control, vol. 116, no. 3, pp. 553–557, 1994.
M. Morari and Z. Evanghelos, Robust process control. Prentice-Hall, 1989, p. 488.
W. Ho, C. Hang, and L. Cao, “Tuning of PID controllers based on gain and phase margin specifications,” Automatica, vol. 31, no. 3, pp. 3–8, 1995.
J. G. Ziegler and N. B. Nichols, “Optimum Settings for Automatic Controllers,” trans. ASME 64.11, 1942.
P. Wang and D. Kwok, “Optimal design of PID process controllers based on genetic algorithms,” Control Eng. Pract., vol. 2, no. 4, pp. 641–648, 1994.
E. Alfaro-Cid, E. W. McGookin, and D. J. Murray-Smith, “GA-optimised PID and pole placement real and simulated performance when controlling the dynamics of a supply ship,” IEE Proc. Control Theory Appl., vol. 153, no. 2, 2006.
Chun-Liang Lin, J. Horn-Yong, and S. Niahn-Chung, “GA-based multiobjective PID control for a linear brushless DC motor,” IEEE/ASME Trans. Mechatronics, vol. 8, no. 1, pp. 56–65, 2003.
Y. Wang, N. Watson, and H. Chong, “Modified genetic algorithm approach to design of an optimal PID controller for AC–DC transmission systems,” Electr. power energy Syst., vol. 24, pp. 59–69, 2002.
R. A. Krohling and J. P. Rey, “Design of optimal disturbance rejection PID controllers using genetic algorithms,” IEEE Trans. Evol. Comput., vol. 5, no. 1, pp. 78–82, 2001.
R. Krohling, H. Jaschek, and J. Rey, “Designing PI/PID controllers for a motion control system based on genetic algorithms,” Int. Symp. Intell. Control. Proc. 12th IEEE, pp. 125–130, 1997.
A. Sharaf and A. El-Gammal, “A novel efficient PSO-self regulating PID controller for hybrid PV-FC-diesel-battery micro grid scheme for village/resort electricity utilization,” in Electric Power and Energy Conference (EPEC), IEEE, 2010, pp. 1–6.
J. Kennedy and R. Eberhart, “A discrete binary version of the particle swarm algorithm,” in International Conference on Cybernetics and Simulation, IEEE, 1997, pp. 4–8.
Y. del Valle, G. K. Venayagamoorthy, S. Mohagheghi, J.-C. Hernandez, and R. G. Harley, “Particle swarm optimization: basic concepts, variants and applications in power systems,” IEEE Trans. Evol. Comput., vol. 12, no. 2, pp. 171–195, 2008.
M. Shamshiri, C. K. Gan, K. Jusoff, I. J. Hasan, M. Ruddin, M. Yusoff, E. Engineering, M. Utem, H. T. Jaya, D. Tunggal, and T. Jaya, “Using Particle Swarm Optimization Algorithm in the Distribution System Planning,” Aust. J. Basic Appl. Sci., vol. 7, no. 3, pp. 85–92, 2013.
Hasan, I.J., Gan, C.K., Shamshiri, M., Bugis, I.B., Ab Ghani, M.R., Losses reduction and voltage improvement using optimum capacitor allocation by PSO in power distribution networks, (2013) International Review on Modelling and Simulations (IREMOS), 6 (4), pp. 1219-1226.
K. Ang, G. Chong, and Y. Li, “PID control system analysis, design, and technology,” IEEE Trans. Control Syst. Technol., vol. 13, no. 4, pp. 559–576, 2005.
B. Allaoua, B. Gasbaoui, and B. Mebarki, “Setting up PID DC motor speed control alteration parameters using particle swarm optimization strategy,” Leonardo Electron. J. Pract. Technol., no. 14, pp. 19–32, 2009.
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