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| Improved Nonparametric Predictive Current Control for Standalone Brushless Doubly-Fed Induction Generators |
| Xu Wei1, Chen Junjie1, Liu Yi1, Huang Shoudao2, Gao Jian2, Huang Cheng3 |
1. State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan 430074 China;
2. College of Electrical and Information Engineering Hunan University Changsha 410082 China;
3. Hubei Huanyee Electromagnetic Equipment Engineering Technology Co. Ltd Wuhan 430205 China |
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Abstract As a new type of AC induction machine, the brushless doubly fed induction generator (BDFIG) can be used for grid-connected and standalone power generation. Model predictive current control (PMCC) has attracted much attention due to its intuitive concept and fast dynamic response. However, due to its heavy dependence on the model parameters, the practical application of MPCC in the BDFIG is not satisfactory. In order to overcome this problem, this paper proposes an improved nonparametric predictive current control (NPCC) method, which uses the detected machine information instead of system parameters to predict the current change. Simulation and experimental results show that this method not only keeps the fast dynamic response performance of MPCC, but also is not affected by the change of machine parameters, which means that it is with strong robustness.
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Received: 30 June 2020
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2021, Vol. 36 
