In this paper, a four-leg matrix converter is proposed as the power conversion core for aircraft ground power unit (GPU) applications. This structure allows easy management of unbalanced and nonlinear loads with minimal disruption of the power supply operation. A hybrid repetitive-traditional control system is proposed to regulate the output voltage of the GPU. This solution reduces the steady-state tracking error, maintaining fast dynamic characteristics, and increases the stability of the converter compared to conventional approaches. Simulations and experimental results from a 7.5-KW converter prototype are presented to verify the operation of the proposed configuration and to prove the effectiveness of the solution.

In the post-industrial digital-economy, motors powering manufacturing have been replaced by computers powering ecommerce - with significant financial losses attributable to poor power quality (PQ). At the same time, increasing penetration of distributed generation and constant power loads complicate the job for the electric utilities to deliver high-quality electrical power. Traditionally, voltage source converters provide PQ compensation; the backbone of these converters, however, are large electrolytic capacitors (e-caps), which have well-known failure rates. A D-STATCOM that does not use e-caps was shown to increase the converter service life and increase the reliability of the power system; finite control set model predictive control (MPC) was shown to achieve high fidelity tracking for multi-objective cost functions. However, high fidelity (to achieve low total harmonic distortion) results in high switching frequency, which increases losses and device stresses, and reduces the overall converter reliability. This paper improves the capacitorless D-STATCOM by investigating an adaptive MPC that trades-off high-fidelity performance and switching frequency, subject to IEEE 519 THD standards, to achieve good-enough performance. The method is verified experimentally in a 7.5 kVA D-STATCOM hardware prototype. The results show a reduction in switching frequency by over 30% compared with the MPC methods that prioritize high-fidelity alone.

Distributed Energy Resources (DERs) have disrupted the traditional electrical system. Grid-connected photovoltaic (PV) systems deliver electric energy closer to the consumer, shifting the paradigm from centralized to distributed generation. The impact of the stochastic PV output power gives rise to potentially rapid voltage fluctuations. Reactive power compensation is needed to regulate the voltage profile to meet the relevant standards. Traditional approaches like switched capacitors cannot provide reactive power that is continuously adjustable at short time scales. This paper examines an alternative distribution static synchronous compensator (D-STATCOM) based on a matrix converter (MC) for the low voltage distribution networks with high PV penetration. This technology can extend service life by using inductors for energy storage. The converter being studied provides ancillary services, including reactive power support; the impact on reliability, operational constraints, and electrical behavior is demonstrated. The contribution of this paper is a detailed analysis and impact study of the capacitor-less D-STATCOM in high PV penetration distribution networks. The significance of this paper is that it studies the behavior of the power electronics converter and its interaction with the power systems without assuming or neglecting details of either. Compensation effects and reliability comparisons between the proposed capacitorless D-STATCOM and the incumbent D-STATCOM technology are also studied in this paper.

Induction motors are critical to industrial operations but are prone to mechanical and electrical faults. This paper introduces a new dataset for comprehensive fault diagnosis of three-phase induction motors, featuring synchronized multi-sensor data collection. Real-time measurements of vibration, voltage, and current were captured from a 0.2 kW squirrel cage induction motor using high-resolution sensors, with all signals sampled at 50 kHz. Fault scenarios, including phase removal and mechanical misalignments, were simulated to capture diverse motor behaviors. The dataset, organized into ten distinct CSV files covering various operational states, provides a rich resource for developing and testing fault detection algorithms. A Random Forest classifier trained on this dataset achieved an accuracy of 99.82%, demonstrating its suitability for real-time fault diagnosis and predictive maintenance applications. Unlike existing datasets, this collection offers synchronized electrical and mechanical sensor data, enabling advanced cross-sensor fault analysis. The dataset is publicly available and aims to support researchers in advancing machine learning approaches for motor health monitoring.

This paper presents a D-STATCOM for reactive power compensation in a distribution system that uses inductive energy storage element connected to the grid via a matrix converter (MC). The MC is controlled using model predictive controller (MPC) technique. The D-STATCOM will provide load compensation without using electrolytic capacitors. Electrolytic capacitors have well-known failure modes. Therefore, reactive power compensators that use a voltage-source inverter (VSI) with electrolytic capacitors as energy storage involve periodic replacement and monitoring constantly. Consequently, this will incur an increase in the cost of the traditional approaches of load compensation significantly. MC system controlled using MPC provides reactive power compensation by controlling the output inductors and the input reactive power. Therefore, the proposed compensator which is based on MC and inductive energy storage has a longer expected service life and more reliability compared with VSI based compensators.