In order to study the contribution of each harmonic to the output torque and axial torque of the axial magnetic gear with Halbach permanent magnet arrays (HAMG), torque and axial force calculation formulas of the HAMG are proposed based on the air-gap flux density distribution of the HAMG. Because of the difference of the air-gap flux densities at different radii, two simplified torque and axial force calculation formulas are proposed and compared. To improve the torque capability of the HAMG, parametric analysis of eight dimensional parameters is firstly conducted. By parametric analysis, six parameters such as the inner radius have been found to have obvious impact on the output torque and output torque density of the HAMG. The optimization using Maxwell software is then executed for maximizing the output torque density of the HAMG. The output torque density of the optimized HAMG is improved from 78.1 kNm/m3 to 93.3 kNm/m3 with an increase of 19%. Furthermore, spectrum analysis is also presented to illustrate the significant output torque improvement based on the torque calculation formulas.

The ESS is considered as an effective tool for enhancing the flexibility and controllability of a wind farm, and the optimal control scheme of a wind farm with distributed ESSs is vital to the stable operation of wind power generation. In this paper, a coordinated active and reactive power control strategy based on model predictive control (MPC) is proposed for doubly fed induction generator (DFIG)-based wind farm (WF) with distributed energy storage systems (ESSs). The proposed control scheme coordinates the active and reactive power output among DFIG wind turbines (WTs), grid-side converters (GSCs), and distributed ESSs inside the WF, and the aim is to decrease fatigue loads of WTs, make the WT terminal voltage inside the extent practicable, and take the WF economic operation into consideration. Moreover, the best reactive power references of DFIG stator and GSC are produced independently based on their dynamics. At last, the control scheme generates optimal power references for all ESS to make the SOC of each ESS converge to their average state. With the distributed ESSs, the WF controller regulates the WTs inside WF more flexibly. A WF composed of 10 DFIG WTs was utilized to verify the control performance of the proposed coordinated active and reactive power control strategy.

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In this study, a coordinated voltage control strategy based on model predictive control (MPC) is proposed for offshore radial DC-connected wind farms. Two control modes are designed in this strategy. In the economic operation mode, the wind farm controller generates optimal active power references as well as bus voltage references of medium-voltage collector for DC-connected wind turbine (DCWT) systems and high-voltage DC/DC converters, where the goal is to minimize power losses inside the wind farm and ensure that voltages are within a feasible range, all while tracking the power references. In the voltage control mode, the main control objective for the wind farm controller is to minimize voltage deviations from the rated voltage. With the MPC, the control objective and operation constraints can be explicitly represented in the optimization problem while considering the dynamic response of the DCWT system. In addition, a sensitivity coefficient calculation method for radial DC-connected wind farms is developed to improve computational efficiency. Finally, DC-connected wind farms with 20 wind turbines are used to demonstrate the performance of the proposed strategy.

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