Predictive Control and Simulation for Variable-Pitch Wind Turbines

S.X. Wang; Z.X. Li; D.X. Sun; X.X. Xie

doi:10.4028/www.scientific.net/AMR.562-564.1012

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 562-564Predictive Control and Simulation for...

Predictive Control and Simulation for Variable-Pitch Wind Turbines

Abstract:

In order to avoid the limitations of traditional mechanism modeling method, a neural network (NN) model of variable - pitch wind turbine is built by the NN modeling method based on field data. Then considering that from wind turbine’s startup to grid integration, the generator speed must be controlled to rise to the synchronous speed smoothly and precisely, a neural network model predictive control (NNMPC) strategy based on the small-world optimization algorithm (SWOA) is proposed. Simulation results show that the strategy can forecast the change of generator rotational speed based on the wind speed disturbance, making the controller act ahead to eliminate the impact of system delay. Furthermore, the system output can track the reference trajectory well, making sure that the system can connect the electricity grid steadily.

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Periodical:

Advanced Materials Research (Volumes 562-564)

Pages:

1012-1015

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.562-564.1012

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Online since:

August 2012

Authors:

S.X. Wang, Z.X. Li, D.X. Sun, X.X. Xie

Keywords:

Model Predictive Control (MPC), Neural Network Identification, Small-World Optimization Algorithm, Variable-Pitch Wind Turbines

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