Robust Finite Control-Set Model Predictive Control for Power Quality Enhancement of a Wind System Based on the DFIG Generator

Houda El Alami, Badre Bossoufi (), Mohammed El Mahfoud, Manale Bouderbala, Btissam Majout, Paweł Skruch and Saleh Mobayen ()
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Houda El Alami: Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco
Badre Bossoufi: Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco
Mohammed El Mahfoud: Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco
Manale Bouderbala: Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco
Btissam Majout: Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco
Paweł Skruch: Department of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland
Saleh Mobayen: Graduate School of Intelligent Data Science, National Yunlin University of Science and Technology, University Road, Section 3, Douliou 640301, Taiwan

Energies, 2023, vol. 16, issue 3, 1-15

Abstract: For many academics, it has proven difficult to operate a wind energy conversion system (WECS) under changeable wind speed while also enhancing the quality of the electricity delivered to the grid. In order to increase the effectiveness and performance of the DFIG-based Wind Energy Conversion System, this research suggests an updated model predictive control technique. This study intends to regulate the generator in two ways: first, to follow the reference wind speed with high precision using the rotor side and grid side converters; second, to reduce system error. The suggested approach optimizes a value function with current magnitude errors based on the discrete mathematical model to forecast the converter’s switching state. In this system, the converter switching states are used directly as control inputs. Thus, the converter may be immediately subjected to improved control action. The key advantage of the suggested strategy over current FCS-MPC methods is error reduction. The originality of this research is in the proposal of a cost function that allows for both successful results and computation time minimization. To achieve this, the system is first presented, followed by a description of the predictive control, and then this method is applied to the rotor side control and grid side control. To demonstrate the efficacy and robustness of the suggested technique, a random wind profile was used to examine the system’s performance with a unitary power factor. This was done in order to compare the results with other controls that have been reported in the literature. The simulation results, which were conducted using a 1.5 kW DFIG in the MATLAB/Simulink environment, demonstrate that the FCS-MPC technique is highly effective in terms of speed, accuracy, stability, and output current ripple.

Keywords: wind turbine; predictive control; back-to-back power converter; doubly feed generator (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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