- Title
- Robust nonlinear model predictive control of wind turbines using uncertain wind predictions
- Creator
- Mohammadalipour Tofighi, Elham
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2019
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Efficient wind turbine control can enhance the performance of the wind turbine operation by increasing the energy yield and reducing the mechanical loads on the turbine components and subsequently reducing maintenance costs. This thesis contributes to this stream of research by investigating the performance of a nonlinear model predictive controller in reducing long-term stress and fatigue on the tower structure of wind turbines. The proposed NMPC incorporates preview wind information (obtained by a LIDAR; LIght Detection and Ranging) in the control problem formulation. The control and state constraints are included in the formulation of the controller yielding smooth handling of loads especially in non-normal operating conditions (e.g., extreme gusts). Furthermore, a specialized cost function that incorporates the classic wind turbine control objectives is implemented. Finally, the continuous-time infinite optimization problem is piece-wise discretized based on the direct single shooting method. The resulting sampled-data finite optimization problem is solved using sequential quadratic programming technique. Comprehensive simulations and analysis in this thesis demonstrate that the proposed NMPC is an effective controller in achieving wind turbine control goals. Furthermore, as the performance and efficiency of the MPC controller is strongly dependent on the accuracy of the prediction model and the quality of the measurements, a robust NMPC controller, based on the scenario-based multi-stage approach, is also proposed. Here, uncertainty in the LIDAR wind measurements is considered. Various simulations are performed and and it is demonstrated that the proposed robust NMPC is capable of handling the uncertainties caused by errors in measuring the wind propagation times.
- Subject
- wind turbine control; robust control; NMPC; nonlinear model predictive control; optimization
- Identifier
- http://hdl.handle.net/1959.13/1406261
- Identifier
- uon:35609
- Rights
- Copyright 2019 Elham Mohammadalipour Tofighi
- Language
- eng
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 10 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 69 KB | Adobe Acrobat PDF | View Details Download |