Search

Silicon (Si)-based semiconductor devices have long dominated the power electronics industry and are used in almost every application involving power conversion. Examples of these include metal-oxide-semiconductor field-effect transistors (MOSFETs), insulated-gate bipolar transistors (IGBTs), gate turn-off (GTO), thyristors, and bipolar junction transistor (BJTs). However, for many applications, power device requirements such as higher blocking voltage capability, higher switching frequencies, lower switching losses, higher temperature withstand, higher power density in power converters, and enhanced efficiency and reliability have reached a stage where the present Si-based power devices cannot cope with the growing demand and would usually require large, costly cooling systems and output filters to meet the requirements of the application. Wide bandgap (WBG) power semiconductor materials such as silicon carbide (SiC), gallium nitride (GaN), and diamond (Dia) have recently emerged in the commercial market, with superior material properties that promise substantial performance improvements and are expected to gradually replace the traditional Si-based devices in various power electronics applications. WBG power devices can significantly improve the efficiency of power electronic converters by reducing losses and making power conversion devices smaller in size and weight. The aim of this paper is to highlight the technical and market potential of WBG semiconductors. A detailed short-term and long-term analysis is presented in terms of cost, energy impact, size, and efficiency improvement in various applications, including motor drives, automotive, data centers, aerospace, power systems, distributed energy systems, and consumer electronics. In addition, the paper highlights the benefits of WBG semiconductors in power conversion applications by considering the current and future market trends. [ABSTRACT FROM AUTHOR]

Distributed solar photovoltaic (PV) generation is growing rapidly around the world. However, unlike conventional synchronous generators, PV systems do not have any rotating masses to deliver inertia to support the grid frequency. The paper presents a detailed modeling of a new converter configuration and control scheme to enable PV systems to adjust the real power output and contribute to the grid frequency regulation. The proposed topology consists of a two-stage converter without an energy storage system. A DC-DC buck converter is used instead of a DC-DC boost converter, and this simplifies the control scheme which aims to keep the PV generator power in the right side of the P-V characteristic and can be varied in the range from near-zero to the maximum power. The proposed control scheme combines robust and nonlinear sliding mode theory with fuzzy logic. The PV system is connected to a low inertia microgrid and its ability to contribute to frequency regulation is assessed for different controls. The proposed converter and its control are validated experimentally on a 3-kW PV system using OPAL-RT real-time simulator and tested under varying temperature, solar irradiance, and partial shading conditions. The results show that with the proposed circuit, the operating point is always on the right side of the P-V characteristic irrespective of the operating mode. Furthermore, the proposed control scheme provides PV generators with a fast and effective inertial response to support the grid and enhance its stability during contingencies. [ABSTRACT FROM AUTHOR]

Most utilities across the world already have demand response (DR) programs in place to incentivise consumers to reduce or shift their electricity consumption from peak periods to off‐peak hours usually in response to financial incentives. With the increasing electrification of vehicles, emerging technologies such as vehicle‐to‐grid (V2G) and vehicle‐to‐home (V2H) have the potential to offer a broad range of benefits and services to achieve more effective management of electricity demand. In this way, electric vehicles (EV) become distributed energy storage resources and can conceivably, in conjunction with other electricity storage solutions, contribute to DR and provide additional capacity to the grid when needed. Here, an effective DR approach for V2G and V2H energy management using Reinforcement Learning (RL) is proposed. Q‐learning, an RL strategy based on a reward mechanism, is used to make optimal decisions to charge or delay the charging of the EV battery pack and/or dispatch the stored electricity back to the grid without compromising the driving needs. Simulations are presented to demonstrate how the proposed DR strategy can effectively manage the charging/discharging schedule of the EV battery and how V2H and V2G can contribute to smooth the household load profile, minimise electricity bills and maximise revenue. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of power quality, and the degradation of the current waveform in the distribution network which results directly from the proliferation of the nonlinear loads. We propose to use a five-level neutral point clamped (NPC) inverter topology for the implementation of the shunt active filter (SAPF). The aim of the SAPF is to inject harmonic currents in phase opposition at the connection point. The identification of harmonics is based on the pq method. A neuro-fuzzy controller based on ANFIS (adaptive neuro fuzzy inference system) is designed for the SAPF. The simulation study is carried out using MATLAB/Simulink and the results show a significant improvement in the quality of energy and a reduction in total harmonic distortion (THD) in accordance with IEC standard, IEEE-519, IEC 61000, EN 50160. [ABSTRACT FROM AUTHOR]

This paper presents different control strategies for a variable-speed wind energy conversion system (WECS), based on a doubly fed induction generator. Direct Torque Control (DTC) with Space-Vector Modulation is used on the rotor side converter. This control method is known to reduce the fluctuations of the torque and flux at low speeds in contrast to the classical DTC, where the frequency of switching is uncontrollable. The reference for torque is obtained from the maximum power point tracking technique of the wind turbine. For the grid-side converter, a fuzzy direct power control is proposed for the control of the instantaneous active and reactive power. Simulation results of the WECS are presented to compare the performance of the proposed and classical control approaches. [ABSTRACT FROM AUTHOR]

Summary: The paper proposes a new sliding mode power control strategy for a wound‐field synchronous generator‐based variable speed wind energy conversion systems to maximize the power extracted from the wind turbine. The proposed controller can handle the inherent nonlinearities in wind energy conversion systems and the randomness of the wind speed as well as the uncertainties of the model and external disturbances. To reduce the chattering phenomenon that characterizes conventional sliding mode control, a sigmoid function with a variable boundary layer is proposed. The adaptive switching gains are adjusted on‐line by using a fuzzy logic‐based technique. Several simulation scenarios were performed to evaluate the performance of the proposed control scheme. The results demonstrate that this controller provides excellent response characteristics, is robust against parameter variations, and free from chattering phenomenon as compared with the conventional sliding mode control. [ABSTRACT FROM AUTHOR]

Thoracic electrical impedance tomography (EIT) is a noninvasive, radiation-free monitoring technique whose aim is to reconstruct a cross-sectional image of the internal spatial distribution of conductivity from electrical measurements made by injecting small alternating currents via an electrode array placed on the surface of the thorax. The purpose of this paper is to discuss the fundamentals of EIT and demonstrate the principles of mechanical ventilation, lung recruitment, and EIT imaging on a comprehensive physiological model, which combines a model of respiratory mechanics, a model of the human lung absolute resistivity as a function of air content, and a 2-D finite-element mesh of the thorax to simulate EIT image reconstruction during mechanical ventilation. The overall model gives a good understanding of respiratory physiology and EIT monitoring techniques in mechanically ventilated patients. The model proposed here was able to reproduce consistent images of ventilation distribution in simulated acutely injured and collapsed lung conditions. A new advisory system architecture integrating a previously developed data-driven physiological model for continuous and noninvasive predictions of blood gas parameters with the regional lung function data/information generated from absolute EIT (aEIT) is proposed for monitoring and ventilator therapy management of critical care patients. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for the compensation of nonlinear friction in a robot joint structure based on a fuzzy local modeling technique. To enhance the tracking performance of the robot joint, a dynamic model is derived from the local physical properties of friction. The model is the basis of a precompensator taking into account the dynamics of the overall corrected system by means of a minor loop. The proposed structure does not claim to faithfully reproduce complex phenomena driven by friction. However, the linearity of the local models simplifies the design and implementation of the observer, and its estimation capabilities are improved by the nonlinear integral gain. The controller can then be robustly synthesized using linear matrix inequalities to cancel the effects of inexact friction compensation. Experimental tests conducted on a robot joint with a high level of friction demonstrate the effectiveness of the proposed fuzzy observer-based control strategy for tracking system trajectories when operating in zero-velocity regions and during motion reversals. [ABSTRACT FROM AUTHOR]

A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (β) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal β observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting. [ABSTRACT FROM AUTHOR]