This article investigates a fault ride-through capability for grid-connected permanent magnet vernier generator (PMVG)-based wind turbine system (WTS) using coordinated active and reactive power control strategy. To do this, the generator peak current and speed limitation schemes are proposed for the machine-side converter to satisfy grid code requirements during grid fault conditions. At the same time, the reactive power control is implemented on the grid-side converter to meet the reactive current requirement of the grid code. And then, to suppress the DC-link power unbalance during grid fault conditions, an efficient variable exponential reaching law-based sliding mode control is designed. Further, the coordinated control schemes are employed to ensure the stable DC-link voltage and maintain the converter's maximum peak current during grid faults. Finally, the proposed control methods demonstrate their superiority through simulations on 5-kW PMVG, 1.5 MW PMSG-based WTS, and its application potential is shown through the experimental prototype of a 5-kW PMVG-based WTS.

This study is concerned with the problem of maximum power extraction for a permanent magnet vernier generator (PMVG)-based wind energy conversion system (WECS) using the Q-learning maximum power point tracking (MPPT) algorithm with the finite-time control (FTC) scheme. To do this, the model-free sensorless reinforcement Q-learning algorithm-based MPPT method is firstly proposed. At this time, the reward and learning rate are updated by the Q-values for each state-action pair. Next, the proposed learning algorithm is used to construct an optimal speed–power curve for achieving the fast and steady MPPT operation for the WECS using the learned action values. Besides, the wind-speed change detection algorithm is added to the proposed method so that the PMVG-based WECS can work in various wind speed conditions. And then, the FTC method is proposed to track the reference speed of PMVG which support to achieving the maximum power extraction, and Lyapunov stability theory is derived to ensure the overall system's stability. Finally, the simulation and experimental results from the 5 kW PMVG-based WECS are presented to demonstrate the applicability and superiority of the proposed control method.

The power system network grows yearly with a large number of nonlinear power generation systems. In this scenario, accurate modeling, control, and monitoring of interface systems and energy conversion systems are critical to the reliability and performance of the overall power system. In this trend, the permanent magnet synchronous generator (PMSG)-based wind turbine systems (WTS) equipped with a full-rated converter significantly contribute to the development of new and renewable energy generation. The various components and control systems involved in operating these systems introduce higher complexity, uncertainty, and highly nonlinear control challenges. To deal with this, state estimation remains an ideal and reliable procedure in the relevant control of the entire WTS. In essence, state estimation can be useful in control procedures, such as low-voltage ride-through operation, active power regulation, stator fault diagnosis, maximum power point tracking, and sensor faults, as it reduces the effects of noise and reveals all hidden variables. However, many advanced studies on state estimation of PMSG-based WTS deal with real-time information of operating variables through filters and observers, analysis, and summary of these strategies are still lacking. Therefore, this article aims to present a review of state-of-the-art estimation methods that facilitate advances in wind energy technology, recent power generation trends, and challenges in nonlinear modeling. This review article enables readers to understand the current trends in state estimation methods and related issues of designing control, filtering, and state observers. Finally, the conclusion of the review demonstrates the direction of future research.

Over the last few years, improving power extraction from the wind energy conversion system (WECS) under varying wind speeds has become a complex task. The current study presents the optimum maximum power point tracking (MPPT) control approach integrated with neural network (NN)-based rotor speed control and pitch angle control to extract the maximum power from the WECS. So, this study presents a reference model adaptive control (RMAC) for a direct-drive (DD) permanent magnet vernier generator (PMVG)-based WECS under real wind speed conditions. Initially, the RMAC-based rotor speed tracking control is presented with adaptive terms, which tracks a reference model that guarantees the expected exponential decay of rotor speed error trajectory. Then, to reduce the wind speed measurement errors, a recurrent neural network (RNN)-based training model is presented. Moreover, the asymptotic stability of the proposed control method is mathematically proven by Lyapunov theory. In addition, the pitch angle control is presented to efficiently operate the rotor speed within the allowable operating range. Eventually, the proposed control system demonstrates its effectiveness through simulation and experimentation using a prototype of 5 kW DD PMVG-based WECS. After that, the comparative results affirm the superiority of the proposed control method over existing control methods.

This paper proposes a novel simple reactive power control strategy for the active load balancer (ALB) in three-phase four-wire distribution systems. The proposed reactive power control strategy may be applicable for adjustment of the source-side power factor under the balanced load condition. Only dc capacitor voltage control is used in the proposed control strategy. Therefore, the calculation blocks of the active and reactive components of the load currents are not necessary. The authors, thus, offer the simplest control strategy to control reactive power under the balanced load condition on three-phase four-wire distribution feeders. The basic principle of dc-capacitor-voltage-control-based reactive power control strategy is discussed in detail and then confirmed by digital computer simulation. A prototype experimental system was constructed and tested. Experimental results demonstrate that balanced source currents with reactive power control are achieved on three-phase four-wire distribution feeders. These experimental results also demonstrate that controlling the reactive power reduces the required power rating of the ALB compared with that of the conventional unity power factor control strategy.

This study presents a fast terminal synergetic control (FTSC) scheme to investigate the nonlinear control problem of permanent magnet vernier generator (PMVG)-based variable-speed wind energy conversion systems (WECSs). In wind turbines, better speed tracking and fast dynamic behavior is required to achieve the maximum power extraction. To do this, the FTSC method is firstly proposed to improve the dynamic performance of tracking the speedby, addressing the turbulent wind and uncertainties in the PMVG system, which improves the wind energy extraction efficiency and alleviates mechanical stress over the turbine. Next, the closed-loop FTSC with a macro variable and novel reaching law is presented to enhance the convergence of the speed error signal when it is far from equilibrium in finite time. At this time, the controller’s output is a zero chattering generator torque reference that can operate the system in both below- and above-rated wind conditions, in addition to pitch control. Then, the proposed control method is verified for its effectiveness in energy capture through numerical simulation and experimental verification of a 5 kW direct drive PMVG-based WECS. Finally, comparative results confirm the better performance of the proposed system under transients than other controllers considered in this analysis.