DocumentCode :
647701
Title :
A quadratic robust optimization model for automatic voltage control on wind farm side
Author :
Tao Ding ; Qinglai Guo ; Hongbin Sun ; Bin Wang ; Fengda Xu
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
fYear :
2013
fDate :
21-25 July 2013
Firstpage :
1
Lastpage :
5
Abstract :
Connecting high penetration of wind power into power grid usually makes voltage fluctuate, due to the volatile nature of wind power injection. This paper therefore proposes a quadratic robust optimization model to guarantee the voltage of each wind unit within the security region, no matter how the wind power varies. Based on the wind power prediction, the prediction error is regarded as uncertainties, and the robust solution can be found by regulating the reactive power equipment and each wind unit using the duality filter method. In the proposed model, linearized derivation instead of original non-linear expressions in the objective function and constraints has been utilized. Furthermore, inner loop iterative method is introduced to reduce the linearized error, which divides the optimal voltage control into multiple steps with piecewise values and updates the sensitivity at each step, according to different wind farm size and condition. A test system with 36 wind units has been simulated, and the result using Monte Carlo simulation. Comparison with traditional method shows the effectiveness of proposed method.
Keywords :
Monte Carlo methods; iterative methods; nonlinear control systems; power grids; quadratic programming; reactive power; voltage control; wind power plants; Monte Carlo simulation; automatic voltage control; duality filter method; inner loop iterative method; nonlinear expression; optimal voltage control; power grid; quadratic robust optimization model; reactive power equipment; voltage fluctuation; wind farm; wind power injection; Gold; Integrated optics; Laboratories; MATLAB; Uncertainty; automatic voltage control; duality filter; inner loop iteration; robust optimization; wind power;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location :
Vancouver, BC
ISSN :
1944-9925
Type :
conf
DOI :
10.1109/PESMG.2013.6672225
Filename :
6672225
Link To Document :
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