Design and optimization of control parameters based on direct-drive permanent magnet synchronous generator for wind power system

Sun, L, Gong, C and Han, F 2013, 'Design and optimization of control parameters based on direct-drive permanent magnet synchronous generator for wind power system', in Xing Zhu, Zhihong Man (ed.) Proceedings of the 8th IEEE Conference on Industrial Electronics and Applications, Melbourne, Australia, 19-21 June 2013, pp. 1238-1243.


Document type: Conference Paper
Collection: Conference Papers

Title Design and optimization of control parameters based on direct-drive permanent magnet synchronous generator for wind power system
Author(s) Sun, L
Gong, C
Han, F
Year 2013
Conference name ICIEA 2013
Conference location Melbourne, Australia
Conference dates 19-21 June 2013
Proceedings title Proceedings of the 8th IEEE Conference on Industrial Electronics and Applications
Editor(s) Xing Zhu, Zhihong Man
Publisher IEEE
Place of publication Piscataway NJ, USA
Start page 1238
End page 1243
Total pages 6
Abstract The direct-drive permanent magnet synchronous generator (DDPMSG) for wind power system uses a back-to-back double PWM converter. PI controller based on decoupling control strategies is used to control generator side converter and grid side converter. But the parameters of the PI controller are difficult to obtain correctly. Though manual tuning method is applied to regulate the parameters, the method would waste a lot of time and greatly depend on the experience. The paper analyses the mathematical model of direct-drive permanent magnet synchronous wind power generation system. It presents a particle swarm optimization (PSO) method for determining the parameters of PI controller for PMSG to improve the control ability. PSO is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. Under the condition of wind speed mutation, the simulation results of PMSG system after PI parameter optimization show that the PI control with PSO algorithm can fit the real value. The PSO controller has fast convergence rate, strong adaptability and good dynamic performance.
Subjects Energy Generation, Conversion and Storage Engineering
Keyword(s) PMSG
manual tuning method
practical swarm optimization algorithm
parameter optimization
DOI - identifier 10.1109/ICIEA.2013.6566556
Copyright notice © 2013 by IEEE
ISBN 9781467363204
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