This study compares a three‐phase three‐level voltage source inverter with an intermediate dc–dc boost converter and a quasi‐Z‐source inverter in terms of passive elements values and dimensions, semiconductor stresses, and overall efficiency. A comparative analysis was conducted with relative parameters to evaluate converter parameters for any application. The equations obtained were confirmed by simulation and experimental setup. Field of application has been discussed.

Shoot-through control methods for qZSI-based dc/dc converters are presented and studied. The major goal was to increase efficiency. A new modulation technique, pulse width modulation (PWM) with shifted shoot-through, is compared with the conventional PWM shoot-through control method. The new method reduces switching frequency of bottom side transistors and inherently features partial soft switching. Previous studies have shown that the biggest drawback of PWM control with shoot-through is unequal switching frequencies of transistors. One solution to that problem could be signal swapping that has been proposed by the authors of this paper. All control methods are first simulated and then experimentally verified on a test prototype.

The aim of the presented investigation is to explore the time gap between an anomaly appearance in continuously measured parameters of the device and a failure, related to the end of the remaining resource of the device-critical component. In this investigation, we propose a recurrent neural network to model the time series of the parameters of the healthy device to detect anomalies by comparing the predicted values with the ones actually measured. An experimental investigation was performed on SCADA estimates received from different wind turbines with failures. A recurrent neural network was used to predict the temperature of the gearbox. The comparison of the predicted temperature values and the actual measured ones showed that anomalies in the gearbox temperature could be detected up to 37 days before the failure of the device-critical component. The performed investigation compared different models that can be used for temperature time-series modeling and the influence of selected input features on the performance of temperature anomaly detection.

This paper discusses realization possibilities of the buck mode in the novel magnetically integrated quasi-Z-source series resonant converter (qZSSRC) with secondary resonance. Our aim was to achieve higher power conversion efficiency at different power levels and dc voltage gains of the converter. The phase-shift modulation (PSM) was comprehensively compared with the asymmetrical pulsewidth modulation (PWM). Both control techniques were evaluated for the case of the discontinuous current through the resonant network, which made their realization more challenging. The operating principle of the qZSSRC in the buck mode with two compared control techniques was explained by means of steady-state analysis. To verify the theoretical assumptions, a 250-W prototype of the photovoltaic module integrated converter was assembled and tested. It was experimentally confirmed that in contrast to the PSM, the asymmetrical PWM for the buck mode control of the qZSSRC will lead to higher power conversion efficiency at different power levels and dc voltage gains of the converter, except the operating points close to the boundary with the normal mode of the converter.

Digital twins (DTs) have been implemented in various applications, including wind turbine generators (WTGs). They are used to create virtual replicas of physical turbines, which can be used to monitor and optimize their performance. By simulating the behavior of physical turbines in real time, DTs enable operators to predict potential failures and optimize maintenance schedules, resulting in increased reliability, safety, and efficiency. WTGs rely on accurate wind speed measurements for safe and efficient operation. However, physical wind speed sensors are prone to inaccuracies and failures due to environmental factors or inherent issues, resulting in partial or missing measurements that can affect the turbine’s performance. This paper proposes a DT-based sensing methodology to overcome these limitations by augmenting the physical sensor platform with virtual sensor arrays. A test bench of a direct drive WTG based on a permanent magnet synchronous generator (PMSG) was prepared, and its mathematical model was derived. MATLAB/Simulink was used to develop the WTG virtual model based on its mathematical model. A data acquisition system (DAS) equipped with an ActiveX server was used to facilitate real-time data exchange between the virtual and physical models. The virtual sensor was then validated and tuned using real sensory data from the physical turbine model. The results from the developed DT model showed the power of the DT as a virtual sensor in estimating wind speed according to the generated power.