This study presents a self-error compensated sequential predictive control (SE-SMPC) technique for three-phase multimodular matrix converters (MMMC). Traditional model-based predictive control (MPC) methods typically require manual tuning of weighting factors and involve significant computational effort. In contrast, the SE-SMPC method addresses these limitations by prioritizing control objectives hierarchically, thereby reducing the number of switching states without sacrificing system performance. A key feature of this approach is its builtin error self-compensation mechanism, which distributes and corrects prediction errors across modules, thereby improving dynamic accuracy. Simulation results show that the proposed controller provides accurate tracking of the load current, significantly reduces the input reactive power and offers high fault tolerance in the event of module failure. In addition, it has been shown to reduce total harmonic distortion (THD) without the need to design complex cost functions. These advantages make it particularly suitable for high-efficiency AC-AC power conversion in various renewable energy applications.

This paper presents the design and simulation of a multimodular power conversion system based on voltage source inverters (VSI), composed of two parallel-connected three-phase modules driving an induction motor. A self-error-compensated predictive current control strategy is proposed to coordinate the modules, enabling dynamic current sharing and fault-tolerant operation. In the event of a failure, the control scheme incorporates the tracking error of the faulty module into the cost function of the operational one, improving performance and continuity. Simulation results demonstrate the effectiveness of the proposed method, with improved dynamic response, reduced root mean square error (RMSE), and lower total harmonic distortion (THD) under both normal and fault conditions.

This paper presents the implementation of LoRaWAN-based non-invasive temperature sensor nodes for detecting loss points in distribution networks. The primary challenges involve integrating and calibrating the electronic components, including temperature sensors, LoRaWAN modules, and digital processors, to develop a robust system for analyzing loss points using thermal measurement techniques. The system employs activation by personalization for deploying sensor nodes, which simplifies the activation process and enhances network efficiency. The data collected is securely transmitted to a network server, then analyzed on an application server to identify loss points. This methodology aims to automate the analysis and detection of losses in medium and high voltage distribution networks, offering a technologically advanced, rapidly deployable, and cost-effective solution. Initial results demonstrate the system’s effectiveness in providing accurate and timely detection of loss points, contributing to improved network efficiency and sustainability.

This paper studied the design of a predictive current control strategy with fault tolerance and reactive power minimization applied to a multi-modular topology based on indirect 2-level matrix converters fed by a six-phase generator. The control algorithm of the proposed strategy involves coupled current signals to perform error compensation between the converter modules, aiming to address potential system faults while maintaining reactive power close to zero. The results, obtained through simulation, were evaluated considering each module’s input and output currents and the final load current, as well as reactive power minimization, incorporating the obtained values of total harmonic distortion and mean squared error. The behaviour was analyzed in steady-state and transient conditions, with the system operating nominally and under fault conditions. The results demonstrate the effectiveness and good performance of the proposed strategy with the utilized topology, achieving a satisfactory response to faults through compensation and constant reactive power minimization.

A predictive current control design for a multi-modular indirect matrix converter using a three-level neutral-point clamped for the inverter side is studied. The multi-modular topology is based on two 3-Level Indirect Matrix Converter modules, and the control strategy proposal involves a single model-based predictive current control and the use of a coupled current signal. It is the interaction between the two three-phase output current of each module for error compensation between these, along with the ability to operate in failures. This article shows the results of the simulation in Matlab/Simulink of the 3-level multi-modular indirect matrix converter with coupled control, compared with an independent control for each module of the converter, in order to verify the performance obtained in terms of total harmonic distortion and mean square error. In addition, the analysis was carried out with respect to the behavior in transient, stationary state and with simulated failures for each module. The results obtained support the effectiveness of the control strategy with the proposed topology showing, with the control coupled, a decrease in the mean square error in the current signal of the final load, having a good value of total harmonic distortion and the capacity for optimal operation in the event of failures of the generation or conversion system.

Multi-phase wind generation systems are emerging as a promising technology for distributed generation systems. These systems can present unbalanced voltages or phase faults for several reasons. In this paper a modular three-phase direct matrix converter topology is used as conversion stage in a six-phase generation system to supply the desired current to a load. To achieve a reliable performance in the conversion stage, an improved predictive current control is proposed that take advantage of the modularity of the converter to enhance the behavior and to provide the capability to work continuously even under unbalance in the source or during fault operation of the generation system whilst achieving the desired tracking and power quality. The technique is compared against a classical approach to show the benefits of the proposed.

There are several control techniques for active power filter applications. This paper presents a new alternative of predictive current control for a cascade H-bridge multilevel converter, where the optimal vector selected by the predictive controller is used for a modulation stage to obtain a fixed switching frequency. Simulation results validate the proposal where almost similar results can be obtained in comparison with the traditional methods.