Gallium nitride (GaN) is a compound semiconductor that has tremendous potential to facilitate economic growth in a semiconductor industry that is silicon-based and currently faced with diminishing returns of performance versus cost of investment. At a material level, its high electric field strength and electron mobility have already shown tremendous potential for high frequency communications and photonic applications. Advances in growth on commercially viable large area substrates are now at the point where power conversion applications of GaN are at the cusp of commercialisation. The future for building on the work described here in ways driven by specific challenges emerging from entirely new markets and applications is very exciting. This collection of GaN technology developments is therefore not itself a road map but a valuable collection of global state-of-the-art GaN research that will inform the next phase of the technology as market driven requirements evolve. First generation production devices are igniting large new markets and applications that can only be achieved using the advantages of higher speed, low specific resistivity and low saturation switching transistors. Major investments are being made by industrial companies in a wide variety of markets exploring the use of the technology in new circuit topologies, packaging solutions and system architectures that are required to achieve and optimise the system advantages offered by GaN transistors. It is this momentum that will drive priorities for the next stages of device research gathered here.
D. B. Rathnayake, Milad Akrami, Chitaranjan Phurailatpam
et al.
This paper surveys current literature on modeling methods, control techniques, protection schemes, applications, and real-world implementations pertaining to grid forming inverters (GFMIs). Electric power systems are increasingly being augmented with inverter-based resources (IBRs). While having a growing share of IBRs, conventional synchronous generator-based voltage and frequency control mechanisms are still prevalent in the power industry. Therefore, IBRs are experiencing a growing demand for mimicking the behavior of synchronous generators, which is not possible with conventional grid following inverters (GFLIs). As a solution, the concept of GFMIs is currently emerging, which is drawing increased attention from academia and the industry. This paper presents a comprehensive review of GFMIs covering recent advancements in control technologies, fault ride-through capabilities, stability enhancement measures, and practical implementations. Moreover, the challenges in adding GFMIs into existing power systems, including a seamless transition from grid-connected mode to the standalone mode and vice versa, are also discussed in detail. Recently commissioned projects in Australia, the UK, and the US are taken as examples to highlight the trend in the power industry in adding GFMIs to address issues related to weak grid scenarios. Research directions in terms of voltage control, frequency control, system strength improvement, and regulatory framework are also discussed. This paper serves as a resource for researchers and power system engineers exploring solutions to the emerging problems with high penetration of IBRs, focusing on GFMIs.
Junbo Zhao, A. Gómez-Expósito, Marcos Netto
et al.
This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.
Relaxor ferroelectrics are promising candidates for pulsed power dielectric capacitor applications because of their excellent energy-storage properties.
Tirupati U. Solanke, V. Ramachandaramurthy, J. Yong
et al.
Abstract Charging–discharging coordination between electric vehicles and the power grid is gaining interest as a de-carbonization tool and provider of ancillary services. In electric vehicle applications, the aggregator acts as the intelligent mediator between the power grid and the vehicle. In recent years, researchers have introduced the concepts of aggregated energy management, centralized-decentralized planning, and ideal charging–discharging through improved technologies and integrated energy planning. These methods have the technical ability to adapt the distribution network according to load, aggregator-controlled optimal charging–discharging, demand management systems, strategic load assessments, and management. A comprehensive review suggests that large-scale electric vehicle charging technologies for controlled charging–discharging is becoming a pitfall within the grid and distribution network. This paper reviews several controlled charging–discharging issues with respect to system performance, such as overloading, deteriorating power quality, and power loss. Thus, it highlights a new approach in the form of multistage hierarchical controlled charging–discharging. The challenges and issues faced by electric vehicle applications are also discussed from the aggregator's point of view.
Nowadays, extensive electrification of maritime transportation, represented by the seaport microgrids and all-electric ships (AESs), has been viewed as a feasible route to enhance the overall system flexibility as well as to mitigate the resulted in growing environmental issues. However, with the trend of electrification, the connections between the seaport and ships are no longer limited in the logistic-side, but also expanded to the electric-side, which makes the future maritime transportation management as a complex transportation-power multi-microgrid coordination problem. In land-based applications, multi-microgrid coordination is a relatively mature technology and already brings enormous economic and environmental benefits, but there still exists some gaps before those land-based technologies being integrated into maritime applications. In this perspective, this overview study emphasizes the characteristic of seaport microgrid and AESs, then several emerging technical challenges and the future research prospects are raised after a comprehensive literature survey.
To cope with the new transportation challenges and to ensure the safety and durability of electric vehicles and hybrid electric vehicles, high performance and reliable battery health management systems are required. The Battery State of Health (SOH) provides critical information about its performances, its lifetime and allows a better energy management in hybrid systems. Several research studies have provided different methods that estimate the battery SOH. Yet, not all these methods meet the requirement of automotive real-time applications. The real time estimation of battery SOH is important regarding battery fault diagnosis. Moreover, being able to estimate the SOH in real time ensure an accurate State of Charge and State of Power estimation for the battery, which are critical states in hybrid applications. This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Experimental validation of an online and on-board suited SOH estimation method using model-based adaptive filtering is conducted to demonstrate its real-time feasibility and accuracy.
Mohammad Saemian, Miguel Cota, Lena Sabidussi
et al.
Dielectric barrier discharge (DBD) plasma actuators (PAs) are devices used to control airflow. DBD actuators generate an electric field that accelerates ionized air particles, inducing localized flow modifications. Among other applications, they are particularly effective for enhancing cooling, for aerodynamic drag reduction, and for lift enhancement, therefore capable of improving stall characteristics. In addition, they offer several distinct advantages, such as rapid response time, low power consumption, and no moving parts. The present review paper aims to summarize the main governing equations associated with the most common phenomenological PA Computational Fluid Dynamics (CFD) models, Shyy and Suzen-Huang, as well as highlight the major applications to flat plates, wind turbine airfoils and entire wind turbines. The application of DBD plasma actuators on individual wind turbine blades, as well as dynamic horizontal and vertical axis wind turbines, is reviewed, drawing from key numerical and experimental investigations. The simulated performance of various configurations of single and multiple PAs on representative airfoils at different chordwise locations is discussed. The overall findings indicate that the chordwise location of the actuators on airfoils and their optimum spanwise placement on small and large wind turbine blades, along with the geometry and excitation parameters of the actuators, play a crucial role in their performance, affecting the boundary layer and the flow pattern. The reader shall obtain an overall idea of the most recent aerodynamic applications of PAs as well as their expected efficiency.
J. Franklin, R. K. Pongiannan, Roobaea Alroobaea
et al.
This paper analyzes Step Density Modulation (SDM) technique for high-frequency inverters in Wireless Power Transfer (WPT) systems for Electric Vehicle (EV) charging. While Pulse Density Modulation (PDM) is commonly used to control high-frequency inverters, it faces limitations in managing current ripple, leading to electromagnetic interference (EMI), reduced power transfer efficiency, and system performance degradation. Step Density Modulation is proposed as an advanced alternative to PDM, offering dynamic pulse density adjustments in discrete stages to align with inverter switching characteristics. This approach minimizes the effects of dead time, significantly reducing current ripple and total harmonic distortion (THD), thereby enhancing waveform quality and system efficiency. A comprehensive mathematical model compares current ripple magnitude, harmonic spectrum, and inverter delay time for both modulation techniques. MATLAB simulations, validated through hardware prototype implementation on a 5 kW WPT EV charger, demonstrate that SDM reduces current ripple by up to 30% and THD of 20% compared to PDM. The hardware prototype confirms smoother inverter output, improved power stability, and increased efficiency, establishing SDM as a reliable and practical solution for enhancing WPT systems in EV charging applications.
ABSTRACT The advanced sensorless technology of the permanent magnet synchronous machine (PMSM) can replace the position sensor on the machine side, however, the encoder is still the necessary feedback on the load side for a full‐closed‐loop servo system. This article proposes a sensorless drive scheme assisted by the computer vision to further replace the load side encoders, so to form a quasi‐sensorless servo system. Although the vision technology can easily provide the load position for the closed‐loop motion control, the feedback continuity cannot be satisfied especially for the multi‐object scenarios, where the vision capture device and the computation ability cannot provide an ideal image processing. The issue of spatial‐temporal discontinuity is discussed and the solution on basis of fusing the electrical and kinetic models is proposed. With this idea, the only feedback of the full‐closed‐loop servo drive is the computer vision, the motor side and load side encoders are both cancelled, and the reliable control performance with respect to the heavy load and high precision positioning is maintained. The scheme is validated on a heavy‐load full‐closed‐loop servo bench driven by a sensorless PMSM with only feedback captured from a regular camera.
Julian Oelhaf, Georg Kordowich, Mehran Pashaei
et al.
The integration of renewable and distributed energy resources reshapes modern power systems, challenging conventional protection schemes. This scoping review synthesizes recent literature on machine learning (ML) applications in power system protection and disturbance management, following the PRISMA for Scoping Reviews framework. Based on over 100 publications, three key objectives are addressed: (i) assessing the scope of ML research in protection tasks; (ii) evaluating ML performance across diverse operational scenarios; and (iii) identifying methods suitable for evolving grid conditions. ML models often demonstrate high accuracy on simulated datasets; however, their performance under real-world conditions remains insufficiently validated. The existing literature is fragmented, with inconsistencies in methodological rigor, dataset quality, and evaluation metrics. This lack of standardization hampers the comparability of results and limits the generalizability of findings. To address these challenges, this review introduces a ML-oriented taxonomy for protection tasks, resolves key terminological inconsistencies, and advocates for standardized reporting practices. It further provides guidelines for comprehensive dataset documentation, methodological transparency, and consistent evaluation protocols, aiming to improve reproducibility and enhance the practical relevance of research outcomes. Critical gaps remain, including the scarcity of real-world validation, insufficient robustness testing, and limited consideration of deployment feasibility. Future research should prioritize public benchmark datasets, realistic validation methods, and advanced ML architectures. These steps are essential to move ML-based protection from theoretical promise to practical deployment in increasingly dynamic and decentralized power systems.
The paper presents a comprehensive overview of recent advancements in power electronics and electric machine design, focusing on novel topologies, semiconductor technologies, and integrated design techniques for electric drives. New drive topologies are gradually moving from the research phase to practical application, aiming to increase the rated power, efficiency, and reliability of electric drives. Specifically, these topologies can be categorized into series, which focus on increasing the operating voltage; parallel, which aim at enhancing the operating current and adding redundancy; and multiphase, known for offering significant benefits such as improved fault tolerance, higher torque generation, the possibility of synthetic loading, and diverse winding layout options. Emerging wide bandgap semiconductors, such as silicon carbide and gallium nitride, allow for operation at higher frequencies and lower power losses, enabling further drive integration. In terms of design practices, higher computational power, supported by advanced software, enables simulation and analysis in multiple domains (thermal, mechanical, electromagnetic) using multiphysics co-simulation, as well as multi-objective optimization concepts to achieve rapid prototyping of optimized drive systems. All the approaches described are important steps towards further improving electric drives for numerous applications in industry, consumer electronics, and transportation.