Modeling and Decoupling Control of Grid-Connected Voltage Source Inverter for Wind Energy Applications


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This paper investigates the modeling and decoupling control of grid-connected voltage source inverter (GC-VSI) for wind energy conversion system (WECS) applications. Firstly, the typical configuration and operation principle of the direct-driven grid-connected WECS are analyzed. Then, by means of input-output modeling method and instantaneous active power theory, a time domain mathematical model of the GC-VSI is set up. Besides, in order to resolve the GC-VSI active current and reactive current cross-coupling nonlinear control problem, a vector decoupling control method for the GC-VSI firing pulse generation is deduced in the dq synchronous rotating coordinates. The proposed decoupling control method can realize the active power and reactive power of the GC-VSI injected into the grid are regulated independently. Finally, the performance of the proposed GC-VSI system is evaluated by using MATLAB/Simulink simulation.



Edited by:

Zhang Yushu




J. F. Mao et al., "Modeling and Decoupling Control of Grid-Connected Voltage Source Inverter for Wind Energy Applications", Advanced Materials Research, Vol. 213, pp. 369-373, 2011

Online since:

February 2011




[1] Martin Saska, Martin Hess and Klaus Schilling: Efficient Airport Snow Shoveling by Applying AutonomousMulti-Vehicle Formations. 2008 IEEE International Conference on Robotics and Automation, May, 2008, pp.19-23.


[2] Thomas H. Cormen , Charles E. Leiserson, Ronald L. Rivest, Clifford Stein: Introduction to Algorithms, Beijing, China Machine Press, (2006).


[3] Martin Saska, Martin Hess and Klaus Schilling: Route Scheduling Approach for Airport Snow Shoveling using Formations of Autonomous Ploughs. 2008 10th Intl. Conf. on Control, Automation, Robotics and Vision, Dec. 2008, pp.390-397.


[4] Jing cun WANG, Xiao tong Zhang, Bin Chen, He ping Chen: A heuristic optimization path2finding algorithm based on Dijkst ra algorithm. Journal of Science and Technology University of Beijing, vol. 29, 2007, pp.346-349.

[5] Donald B. Johnson: Efficient algorithms for shorest paths in sparse networks. Journal of the ACM, 24(1): 1-13, (1977).

[6] T. D. Barfoot and C. M. Clark: Motion planning for formations ofmobile robots. Robotics and Autonomous Systems, vol. 46, p.65–78, February (2004).


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