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In this paper, a distributed optimal active and reactive power control (DARPC) strategy based on the alternating direction method of multipliers (ADMM) is proposed for wind farms (WFs). The WFs operate in a distributed manner to minimize the network power loss, voltage deviations of buses from the rated voltage, and active power output deviations of WTs from their proportional distribution (PD)-based power reference. An optimization problem is formulated as a quadratic programming (QP) problem by using the linearized DistFlow model. The ADMM-based solution is used to decompose the centralized optimization problem to several subproblems which are solved in individual local controllers with exchanged information from their practical neighbor controllers. Compared with existing distributed/hierarchical optimal control, the impacts of the active power injection from the WTs are taken into consideration and optimized while meeting the dispatch command from the transmission system operator (TSO). The ADMM-based distributed solution eliminates the requirement of a central unit. Compared with convention16 al centralized optimal control, the scalability of the WFs is improved. A WF consisting of 20 WTs is simulated in MATLAB/Simulink to test the control effectiveness of the proposed DARPC strategy.

An adaptive droop-based hierarchical optimal voltage control (DHOVC) scheme is proposed for voltage-source converter high-voltage-direct-current (VSC-HVDC) connected offshore wind farms (WFs). The wind turbines (WTs) and WF side VSC (WFVSC) are coordinated to minimize the voltage deviations of buses inside the WF from the nominal voltage and mitigate reactive power (Var) fluctuations of WTs. The model predictive control (MPC) is used to improve the performance of the DHOVC scheme during a certain predictive horizon. A hierarchical solution method based on the alternating direction method of multipliers (ADMM) is developed to reduce the calculation burden of the central controller while improving the information privacy protection. During the predictive horizon, the WTs and WFVSC are coordinated to achieve the near global optimal performance without global information. A WF with 32 × 5MW WTs was used in the matlab/simulink to test the proposed DHOVC scheme.

In this study, a novel predictive torque and stator flux control (PTSF) method is proposed for N-segment three-phase PMSM (N*3-phase PMSM), which can effectively eliminate the influence of parameter mismatch on stator flux and torque. The proposed PTSF method has two loops, stator flux loop and torque loop, both implemented with robust predictive control algorithm. First, the stator flux predictive controller with parameter robustness is designed, and the sensitivity of its parameters is analyzed. In the dq stator flux space, the robust stator flux predictive control with one-step delay compensation is then proposed, which can effectively enhance robustness against parameters mismatch. Moreover, the robust torque predictive control based on unknown torque disturbance observer is developed, which can effectively strengthen the robustness against the load torque disturbance and parameter mismatch. Finally, the validity and feasibility of proposed PTSF method are verified by simulation and experiment. Excellent simulation and experimental results were achieved with respect to the stator flux tracking error, torque /flux ripple reduction, and stator current distortion over conventional predictive torque control (PTC).

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.

In this paper, a predictive stator flux control (PSFC)algorithm for permanent magnet synchronous motor (PMSM) drives is proposed, which can eliminate the influence of flux linkage parameter perturbation and rotor position error. First, the sensitivity of conventional predictive current control (PCC) to the flux linkage parameter and rotor position is analyzed. Then, the novel composite discrete time sliding mode observer (SMO) based on stator flux state is designed, which can estimate the flux linkage parameter perturbation, rotor position error and load torque simultaneously. Finally, a novel PSFC method is developed, which can enhance the robustness of PCC against flux linkage parameter perturbation and rotor position error by using composite discrete time SMO. Simulation and experimental results indicate that the proposed PSFC can achieve low stator current harmonics, low torque ripple and excellent steady-state performance under the flux linkage parameter perturbation and rotor position error.