In this study, a robust fault-tolerant predictive current control (RFT-PCC) algorithm based on a composite observer is proposed for permanent magnet synchronous motors (PMSMs), which can eliminate the influence of motor parameter perturbation and permanent magnet demagnetization. First, the effects of the parameter perturbation and permanent magnet demagnetization on the current vector are analyzed based on the conventional predictive current control. The composite observer based on the sliding mode observer and the Luenberger observer is then designed to observe the compensation voltage and current prediction value of the next time simultaneously. Finally, an RFT-PCC method is developed. The proposed RFT-PCC is able to effectively enhance robustness against parameter perturbation and permanent magnet demagnetization by adding compensation voltage. The current prediction value of the next time is used to replace the sampled current in RFT-PCC to compensate for the influence of the one-step delay. Comparative simulations and experimentations verify that the proposed RFT-PCC can improve the robustness while maintaining quick dynamic response of the current control loops.

The permanent magnet synchronous motor (PMSM) has become a core component of electromechanical energy conversion in the modern industrial field. In order to expand the application of the PMSM in the field of high power traction, a robust predictive torque control (R-PTC) strategy for the N-segment three-phase PMSM (N*3-phase PMSM) is proposed in this paper. Firstly, the output characteristics of the N*3-phase PMSM are illustrated with the finite element analysis method, and the mathematical model is established. Then, the six-segment three-phase PMSM predictive control system driven by six parallel inverters is designed to generate the required torque. Further, the influence of the parameter mismatch on the predicted torque and stator flux is taken into consideration based on the conventional predictive torque control (PTC). Finally, a novel R-PTC method with the proportional controller is developed for the N*3-phase PMSM, which can effectively improve accuracy and robustness of predictive control performance under parameters mismatch. Simulation and experimental results verify that, compared with the conventional PTC, the proposed R-PTC method can make the predicted stator flux and torque value accurately track its reference values while achieving lower stator flux and torque ripple.

A hierarchical active power control (HAPC) scheme based on alternating direction method of multipliers (ADMM) is proposed for doubly fed induction generator (DFIG) wind farms with distributed energy storage systems (ESSs). The wind farm controllers optimizes the active power references for DFIG wind turbines (WTs) and ESSs inside the wind farm, and the aim is to minimize fatigue loads by minimizing variations of thrust force and shaft torque of WTs while tracking the dispatch command from the transmission system operator (TSO). Moreover, ESSs management is considered. The hierarchical solution method based on ADMM with fast convergence is used to solve the model predictive control(MPC) problem in a hierarchical manner without loss of optimality of the primal problem. With the ADMM, given that the control task is distributed to WT controllers, the computation burden of the central wind farm controller can be efficiently reduced. A wind farm with 10 DFIG WTs was used to validate the control performance of the proposed HAPC scheme.

This paper proposes a novel topology of voltage balance circuit for ALL-DC offshore wind farm with series-connected wind turbine. In the proposed topology, adjacent wind turbines are connected by a voltage balance circuit in parallel, and these wind turbines can both achieve the maximum power point tracking (MPPT) and balance the terminal voltages when the wind speeds of wind turbines are unequal. With the current compensation of voltage balance circuit, this topology can ensure the normal operation of wind farm even if some wind turbines are outage. Furthermore, the double loop controller for the voltage balance circuit is designed which does not require the communication among wind turbines, and the stability analysis is implemented and discussed for tuning the control parameters. The simulation model and the RT-Lab experiment are set up to verify the validity of the proposed topology under unequal wind speeds. Simulation and experiment results confirm the superior performance of the proposed topology with low costs, high fault tolerance and high efficiency.

An ADMM-based hierarchical optimal active power control (HOAPC) scheme is proposed for synthetic inertial response of large-scale wind farms. The proposed scheme coordinates active power outputs of wind turbines (WTs) inside the wind farm during the synthetic inertial response process, aiming to minimize the differences in the rotor speed of the WTs and the wind energy loss caused by the decrease in the rotor speed of the WTs. The optimal control is formulated based on the model predictive control (MPC) according to the local WT wind conditions. A hierarchical solution method based on the alternating direction method of multipliers (ADMM) is developed to efficiently solve the MPC-based optimization problem without the loss of optimality. With the HOAPC, the wind farm controller guarantees the rotor speed stability of WTs inside the wind farm and reduces the wind energy losses during the synthetic inertial response process. Moreover, the optimization problem is decomposed into several optimization subproblems which are solved in parallel. As such, the computation burden of the wind farm central controller is significantly reduced, and protection of the information privacy of the wind farm is improved. A wind farm with 100 WTs was used to validate the proposed HOAPC scheme.