Constrained Multiple Model Predictive Control Design for Offshore Floating Wind Turbines

Abbasi, Milad | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53374 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Sadati, Nasser
  7. Abstract:
  8. Wind energy is one of the fastest-growing renewable energy sources around the world. Nowadays, the use of offshore wind turbines has increased due to the high and uniform wind at sea, as well as resolving environmental issues such as making noise and sound pollution. Advances in wind energy technology has been effective in wind turbine control systems. Because the offshore wind turbines are affected by the turbulent wind and wave profiles, the control system should be designed to increase the output power quality, as well as alleviating the mechanical loads on different parts of the turbine. In this research, multiple model predictive control method is used to control offshore wind turbines, while taking the constraints on input signals into account. Given that the nonlinear dynamics of the wind turbine system changes with parameters such as wind speed, it is shown that a designed controller based on a single model obtained at an operating point, may not guarantee the performance and stability over the whole range of wind speed. Therefore, the operational region of the wind turbine is divided into different subregions and in each subregion, the model predictive controller is designed based on the linear model obtained from the FAST. ubsequently, the models are considered collectively and the closest model to the system is identified and then, the control action is formed by a weighted sum of the local controllers outputs. The 5 MW offshore wind turbine developed by the National Renewable Energy Laboratory (NREL) is utilized to test the performance of the proposed control method
  9. Keywords:
  10. Wind Energy ; Offshore Wind Turbine ; Multimodel Predictive Control (MMPC) ; Dynamic Loads ; Model-Free Control ; Offshore Renewable Energy

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