In order to realize sensorless control for brushless doubly-fed induction machine (BDFIM), this paper presents a model reference adaptive system (MRAS) observer, designed based on the error of the control winding current. Furthermore, a phase-locked loop (PLL) is employed to estimate the current winding position and rotor speed. Consequently, a detailed theoretical derivation proves that the MRAS observer is stable and the dynamic performance is good. Thus, it does not cause any estimated speed error in steady state. Moreover, the estimated position error is bounded and trivial, thus its effects on the sensorless control of the BDFIM are neglected. The correctness, feasibility, and robustness of the proposed sensorless control method are verified by means of experimental validation on a 30kW test rig.

A real-time algorithm for simultaneous 3D wireless power transfer to multiple moving devices with different power demands is proposed. An objective function of the weighted sum of the power transfer to the multiple moving devices is formulated. Devices with more urgent need for charging will have higher weights. The objective function is optimized in real-time. By the proposed algorithm, the wireless power transfer system transfers power as much as possible to the multiple devices based on their power demands so that the transfer distance is improved and charging time is saved. The proposed algorithm does not need to know the positions and orientations of the multiple moving devices, which is hard to be obtained in practice. The correctness and convergence of this algorithm are theoretically proved. The experimental results show that the proposed algorithm can adapt to both devices' movement and power demands variation. The convergence time of the proposed algorithm is 0.2 seconds when the devices' power demand urgencies change.

The construction and gradual installation of turbines on wind farms has been hindered by the high cost of the energy production. An effective way to minimize energy costs is via the optimal design of wind turbines and their layout, but relevant and synthetic studies are lacking. This paper proposes a method to minimize the energy cost of offshore wind farms by simultaneously optimizing the rated wind speed, the rotor radius of wind turbines and their layout. Firstly, a new, mixed mathematical formulation of the energy cost is presented, considering the Weibull distribution for wind, the characterizing parameters of wind turbines and the distance between two turbines. Secondly, to obtain the minimum energy cost, a composite optimization algorithm was developed, which consists of an iterative method and an improved particle swarm optimization algorithm. The former was used to search the minimal energy costs that relate to the design parameters of a single wind turbine, while the latter was adopted for optimizing the layout of the wind turbines iteratively. Finally, the proposed method was applied to three case studies with variable wind speed and constant wind direction. Results of the case studies show that the reduced energy cost after optimization has a range of 0–0.001 $/kWh, which confirms the effectiveness of the proposed approach. Meanwhile, the layout of the wind turbines after optimization tends to locate the two wind turbines with the biggest spacing in the wind direction, which justifies the utilization of layout optimization. Furthermore, exploring the optimally designed parameters of wind turbines revealed that the wind farms with a high mean wind speed can have a wider range of turbine capacity than those with a low wind speed, which offers more freedom for the designers when constructing offshore wind farms at wind sites with rich wind resources.

As onshore wind energy has depleted, the utilization of offshore wind energy has gradually played an important role in globally meeting growing green energy demands. However, the cost of energy (COE) for offshore wind energy is very high compared to the onshore one. To minimize the COE, implementing optimal design of offshore turbines is an effective way, but the relevant studies are lacking. This study proposes a method to minimize the COE of offshore wind turbines, in which two design parameters, including the rated wind speed and rotor radius are optimally designed. Through this study, the relation among the COE and the two design parameters is explored. To this end, based on the power-coefficient power curve model, the annual energy production (AEP) model is designed as a function of the rated wind speed and the Weibull distribution parameters. On the other hand, the detailed cost model of offshore turbines developed by the National Renewable Energy Laboratory is formulated as a function of the rated wind speed and the rotor radius. Then, the COE is formulated as the ratio of the total cost and the AEP. Following that, an iterative method is proposed to search the minimal COE which corresponds to the optimal rated wind speed and rotor radius. Finally, the proposed method has been applied to the wind classes of USA, and some useful findings have been obtained.

In the wind energy generation system, the brushless doubly-fed induction machine (BDFIM) has shown significant application potential, since it eliminates the electric brush and slip ring. However, the complicated rotor structure increases the control difficulty, especially resulting in complicated coupled terms in the current sub-system, which deteriorates the dynamic performance and reduces the system robustness. In order to address the problems caused by complex coupled terms, an internal model current control strategy is presented for the BDFIM, and an active damping term is designed for suppressing the disturbance caused by the total resistance. The proposed method simplifies the controller parameters design, and it achieves the fast-dynamic response and the good tracking performance, as well as good robustness. On the other hand, the feedforward term composed by the grid voltage is added to the internal model controller in order to suppress the disturbance when the symmetrical grid voltage sag happens. Finally, the simulation and experimental results verify the feasibility and effectiveness of the proposed method.

This article proposes a method to effectively suppress second‐harmonic current (SHC) of dual active bridge (DAB) converter, which adopts the triple‐phase shift (TPS) modulation strategy, in two‐stage single‐phase inverter system. Load current feedforward control with twice the output voltage frequency notch filter inserted is introduced to ensure the dynamic response performance. The averaged model of the system is established to analyse the influence of output impedance of front‐end DAB converter on SHC from the perspective of impedance. The proposed method does not need to consider the accuracy of the intermediate bus capacitance. Finally, an experimental prototype was established to verify the correctness and effectiveness of the proposed SHC reduction method.