Search Results (1,529)

Early identification of thermal and electrical anomalies in grid-connected photovoltaic (PV) systems is becoming increasingly important to reduce energy losses, limit power quality (PQ) degradation, and avoid excessive operating stress on power electronic converters. Conventional electrical monitoring methods can provide overall performance information, but they are generally unable to detect and localize early-stage defects occurring at module or cell level. In this context, the present study proposes an integrated diagnostic framework that combines non-destructive infrared thermography (IRT) with advanced electrical signal processing techniques for PV condition monitoring. The proposed approach correlates thermographic information, capable of revealing defects such as hotspots, cell cracks, and bypass diode failures, with high-frequency electrical signal analysis based on frequency-domain and time–frequency methods, together with deep learning-driven thermographic segmentation. By associating thermal acquisitions with electrical PQ indicators, the framework enables the early detection of physical defects linked to inefficient Maximum Power Point Tracking (MPPT) operation and progressive degradation of PV system performance. The methodology was experimentally validated on a grid-connected photovoltaic installation under different fault conditions, including hotspots, bypass diode anomalies, and localized overheating effects, demonstrating the potential of the proposed approach for predictive maintenance and intelligent PV monitoring applications. The obtained results indicate that the proposed framework improves the reliability of photovoltaic fault detection by combining thermographic inspection with advanced electrical signal analysis and AI-based defect interpretation, thus supporting predictive maintenance strategies in smart PV infrastructures. The proposed approach demonstrates image segmentation capabilities, as evidenced by a precision (PA) of 96.88%, a mean IoU (mIoU) of 77.83% and a macro F1-score of 87.47%. The proposed framework maintained reduced computational requirements compatible with real-time monitoring applications. Full article

This paper proposes a mathematical co-design framework for synchronous Boost DC-DC converters and their PI voltage controllers. In contrast to the conventional sequential design approach, where the power stage is sized first and the controller is tuned afterward, the proposed method treats the converter and the controller as a single coupled design problem. A nonlinear averaged model of the synchronous boost converter operating in continuous conduction mode is considered, explicitly incorporating the inductor series resistance, the capacitor equivalent series resistance, and the on-state resistances of the active switches. In addition, a simplified but physically interpretable loss model is included in order to capture inductor copper loss, capacitor ESR loss, semiconductor conduction loss, and switching loss. Based on this formulation, the joint design of the power stage and the PI controller is cast as a constrained multi-objective optimization problem whose decision variables include the inductance, capacitance, switching frequency, and controller gains. The optimization criteria account for output-voltage ripple, settling time, total losses, and current stress, while practical constraints related to duty cycle, current limits, ripple bounds, and closed-loop feasibility are enforced. The proposed framework makes it possible to compute Pareto-efficient designs and to reveal trade-offs that remain hidden under classical decoupled design procedures. Numerical case studies are structured to compare the proposed co-design strategy with a conventional sequential-design baseline. An optional technology-aware extension is also considered, allowing the influence of different semiconductor classes, such as Si, SiC, and GaN, to be assessed through technology-dependent loss and switching-frequency assumptions. The results indicate that the proposed framework provides a mathematically grounded and practically useful basis for integrated converter–controller synthesis in nonideal power electronic systems. Full article

High-nickel NCA/Si–C 21700 cells exhibit strongly condition-dependent degradation, but the coupled influence of temperature and rate on electrochemical, thermal, and structural evolution remains insufficiently resolved. Here, Samsung INR21700-50E cells were aged under a 3 × 3 matrix of ambient temperatures (0, 23, and 40 °C) and C-rates (0.5C, 1C, and 2C). Periodic reference performance tests were used to track capacity, 10 s direct-current internal resistance, electrochemical impedance, pseudo-open-circuit voltage, differential voltage/incremental capacity behavior, heat generation, and post-mortem morphology. Guided by the hypothesis that temperature and rate history change not only the speed but also the dominant pathway of aging, the results show that both ambient temperature and the charge/discharge rate program govern the aging trajectory. Low-temperature cycling accelerates capacity loss and resistance growth through severe polarization and lithium plating, indicating dominant loss of lithium inventory. High-temperature operation promotes interfacial side reactions, impedance rise, and cathode structural degradation, leading to stronger loss of active material at later stages. An increasing C-rate amplifies these effects by raising overpotential and thermal load. Heat generation power increases markedly with aging and depends strongly on temperature–rate history. Scanning electron microscopy confirms cathode cracking, anode surface film thickening, and separator degradation under severe conditions. These experimental indicators are integrated into a mechanism-aware diagnostic framework that maps capacity retention, DCIR/EIS parameters, ICA/DVA indices, and heat generation metrics to dominant aging modes, supporting BMS state-of-health estimation, lifetime prediction, thermal management, and second-life screening of high-nickel NCA cells. The condition-averaged trajectories are further converted into a semi-empirical aging law that links capacity loss, resistance growth, and heat generation increase for BMS-oriented lifetime prediction. Full article

This paper introduces a new combination of hybrid energy storage in a split-shaft wind energy conversion system based on a hydraulic transmission system. In the hybrid energy storage, a flywheel, supercapacitor, and battery are integrated into the wind energy conversion system with minimal additional supporting hardware. The split-shaft configuration allows the direct connection of the flywheel to the doubly fed induction generator (DFIG) shaft without a power electronic converter. The principal operation and minimization of this hybrid storage, as well as the energy management strategy, are explained. The goal is to smooth out output power fluctuations using the response surface method. A 1.5 MW hydraulic wind turbine is simulated in Matlab 23, and the hybrid storage is configured and optimized. The direct connection of the flywheel facilitates reaching a suitable level of smoothness at a reasonable cost. The proposed configuration is compared with conventional storage, and the results demonstrate that the integrated hybrid energy storage reduces the annualized storage cost by 71%. Full article

The increasing penetration of power electronic devices and distributed generation is significantly altering power quality conditions in low-voltage systems. While power quality assessment is commonly based on RMS currents, voltage quality indicators, and overall distortion metrics, these parameters may not fully reveal phase-selective harmonic behaviour in modern converter-dominated installations. This paper presents a measurement-based power quality assessment of a secondary school building equipped with a grid-connected photovoltaic (PV) system. A one-week monitoring campaign was conducted at the point of common coupling (PCC), capturing voltage, current, harmonic distortion, and power flow characteristics under real operating conditions. The results reveal pronounced phase-selective current harmonic distortion, with substantially elevated total harmonic distortion (THD_I) and total demand distortion (TDD) in one phase despite relatively balanced RMS current levels and acceptable voltage quality. The harmonic spectrum is dominated by low-order odd harmonics, whereas voltage distortion remains comparatively low and well balanced across phases. The study demonstrates that significant harmonic asymmetry may remain hidden in apparently balanced three-phase systems when assessment relies primarily on conventional RMS-based indicators. The findings highlight the importance of detailed current harmonic analysis and show that acceptable voltage quality does not necessarily imply acceptable current quality. The presented results provide measurement-based evidence of hidden harmonic asymmetry in modern low-voltage buildings and contribute to a better understanding of power quality challenges associated with nonlinear loads and distributed energy resources. Full article

Transformerless inverters are increasingly becoming essential in renewable energy generation, particularly for grid-connected photovoltaic (PV) and other sustainable and alternative energy resources. The transformerless designs offer higher efficiency, compact size, and reduced cost compared to traditional inverters with bulky transformers. These inverters minimize energy losses and enable direct connection to the grid by removing the low-frequency transformer. This paper investigates a highly reliable single-phase common-ground inverter for solar panels and other alternative energy generation. The proposed PV inverter has the benefits of existing non-isolated common-ground PV inverters, including direct connection of an input source’s negative terminal to the AC neutral terminal, eliminating leakage ground currents. The inverter is an enhancement of the dual-buck inverter, incorporating one additional diode and a flying capacitor. The dual-buck structure with the inductor inserted between the inverter phase leg prevents short-circuiting. This increases the reliability of the entire power electronics system. Moreover, using external diodes to freewheel the current, the configuration has no reverse recovery issues, allowing power MOSFETs to be employed with safe commutation at higher DC-link voltage and achieve higher efficiency. Summarily, this design prevents short-circuit issues, enhancing reliability and efficiency, and relaxing pulse-width-modulation dead times. The derivation of the PV inverter is carefully analyzed. A 700 W prototype of power converter hardware has been built. The comparative study validates the operational performance, and the grid-connected experiment confirms its theoretical analysis. Experimental results of the hardware prototype are discussed to prove the feasibility and effectiveness of the proposed PV inverter. Full article

Power electronic DC–DC conversion stages play a pivotal role in photovoltaic (PV) energy conversion. Here, maximum power point tracking (MPPT) is necessary to regulate the operating point of the converter with high bandwidth and robustness in the presence of irradiance and temperature disturbances. This paper proposes an MPPT scheme based on an Intelligent Wave Algorithm (IWA) for a PV source connected to a flyback DC–DC converter. The proposed IWA is formulated as a population-based metaheuristic that updates the converter’s duty cycle to maximize PV power while reducing the oscillations commonly observed in classical methods. A unified MATLAB/Simulink test bench has been developed in which multiple MPPT algorithms—Perturb and Observe (P&O), Incremental Conductance (InC), Particle Swarm Optimization (PSO), Harris Hawks Optimization (HHO) and the proposed IWA—are implemented in parallel flyback subsystems that share the same PV module and converter parameters. The simulation results show that the IWA method achieved consistent convergence to the maximum power point more rapidly than both classical and advanced meta-heuristic methods, obtaining 12.5% better response time and 8.9% better steady-state output power than the method closest to it. Overall, the findings suggest that combining a flyback converter with IWA-based maximum power point tracking (MPPT) improves the efficiency and stability of energy harvesting, making this approach suitable for low- to medium-power photovoltaic (PV) applications within modern power electronics conversion systems. Full article

This paper addresses the “dual-high” challenges posed by high proportions of renewable energy and power electronic equipment in new power systems, and investigates the active support characteristics of grid-forming energy storage stations in terms of voltage and frequency. Regarding voltage support, the paper analyzes the transient process of a three-phase short-circuit fault in the power grid and proposes a low-voltage ride-through control strategy based on the flexible adjustment of active power and voltage commands. By suppressing short-circuit currents and power-angle instability during the fault, this strategy effectively enhances the system’s transient stability. The effectiveness of this strategy when the grid voltage drops to zero was verified through PSCAD/EMTDC simulations. Regarding frequency support, a small-signal model for frequency regulation of grid-forming converters was established, revealing the influence of controller parameters on the system’s virtual inertia. Simulation results indicate that grid-forming control possesses adjustable inertial support capabilities, effectively enhancing the system’s frequency stability. This research provides a theoretical basis and control strategy support for the application of grid-forming energy storage stations in power grids with a high proportion of renewable energy. Full article

This paper presents a complete analysis and simulation of the operation of a zero-emission marine vessel with electric propulsion. A hypothetical passenger ferry operating in the Aegean Sea, Greece, is considered, which is powered by a hydrogen fuel cell, a battery energy storage system (BESS) and photovoltaic (PV) energy. Wind-assisted ship propulsion (WASP) is employed to reduce the energy consumption of the ship. A complete analysis is performed, which includes optimal energy management, dynamic analysis and emerging stability concerns due to the high integration of power electronic converters in the shipboard microgrid. The energy management system (EMS) applies multi-objective optimization based on the corona virus optimization (CVO) algorithm and the teaching–learning-based optimization algorithm (TLBO). The dynamic behavior of the microgrid is tested using real-time digital simulations. Converter-driven stability issues are investigated, which may arise due to interactions among the various converter controllers and passive components of the microgrid. Full article

The exhaustion of fossil fuels, environmental concerns, and difficulties in deploying smart grids have expedited the development of renewable energy distributed generators (REDGs) and electric vehicles (EVs). In recent decades, there has been a notable rise in the production and marketing of EVs. Previous research has proposed reactive power control solutions, including the use of power electronic converters associated with distributed generators (DGs) to alleviate voltage fluctuations. This research presents a strategy for the best integration of electric vehicles through bidirectional charging and renewable energy distributed generators inside power systems, with the objective of efficiently managing voltage, active power, and reactive power flows at interconnection points. Furthermore, it entails determining appropriate locations and dimensions for electric car charging stations through a comparative examination of computing time and iterations between the Hybrid Genetic Algorithm Improved Particle Swarm Optimization (HGAIPSO) and several other optimization methods, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Improved Particle Swarm Optimization (IPSO). This analysis was performed on the IEEE-118 bus system, incorporating Vehicle-to-Grid (V2G), Grid-to-Vehicle (G2V), and REDG allocations. The simulation results indicated that the suggested HGAIPSO approach is more rapid and effective regarding calculation time for complex networks, attaining optimal solutions with greater efficiency. Full article

The increasing penetration of converter-interfaced renewable energy resources is accelerating the transition of conventional distribution networks toward hybrid AC/DC architectures, where photovoltaic generation, battery energy storage, electric mobility, and mixed AC/DC loads are coupled through multiple power electronic interfaces. While these architectures offer important advantages in flexibility and integration efficiency, they also introduce tighter interactions between AC-side and DC-side operating behavior, making coordinated assessment increasingly important under variable operating conditions. Despite growing interest in hybrid AC/DC systems, comparative studies that jointly examine system-level stability and voltage-quality-related behavior across renewable penetration levels and stressed operating scenarios remain limited. This paper proposes a reduced-order comparative screening framework for renewable-rich hybrid AC/DC distribution systems, using stability- and voltage-quality-related indicators based on a representative reduced-order benchmark model. The adopted framework combines scenario-based simulation with unified AC-side, DC-side, transient, and composite performance indicators to evaluate how different converter coordination strategies influence operating robustness under renewable intermittency, abrupt load changes, converter operating-point variations, and different renewable penetration levels. The considered indicators include voltage deviation, overshoot, violation duration, transient fluctuation, converter utilization, and composite operating-robustness measures; they are intended as system-level voltage-dynamics proxies rather than as a complete harmonic or standards-based power-quality assessment. The results indicate that adaptive coordinated control provides the strongest DC-side robustness under stressed conditions, whereas droop-based coordination often offers a favorable practical compromise between AC-side and DC-side performance. The analysis also reveals a clear trade-off between DC-side regulation and AC-side voltage-quality-related behavior, highlighting the need for joint multi-domain evaluation. In particular, the improved DC-side robustness obtained with adaptive coordination is accompanied by slightly higher AC-side voltage-quality-related deviations in several scenarios. Within the scope of the adopted reduced-order benchmark, the proposed framework provides a practical and reproducible basis for identifying critical operating regions and for supporting higher-fidelity future studies on robust renewable integration in hybrid AC/DC distribution networks. Full article

This paper presents an Internet of Things-oriented intelligent supervisory system and high-level control for a small wind turbine powering a residential building. The proposed approach integrates wind generation, battery storage, grid interaction, technical condition analysis, and initial operating mode selection within a single cyber–physical framework. A nonlinear discrete–time hybrid mathematical model was developed for the study, describing the interdependent operating processes of the turbine, storage, and power converter, along with a control algorithm that accounts for constraint flows. A series of experiments are presented for steady-state and dynamic operating scenarios, including wind-speed variations, evening energy shortages, stochastic disturbances, and a developing converter unit fault. As a result, the proposed Internet of Things-oriented supervisory algorithm ensures more efficient utilization of the available wind resource, reduced grid-import dependency, improved battery reserve preservation, and lower thermal loading of the power electronics. Under developing fault conditions and stochastic operating disturbances, the proposed framework maintains more stable residential energy-management behavior and improved operational robustness. The obtained results confirm the potential of the proposed control design for autonomous and semi-autonomous low-power wind energy systems for residential and distributed use. Full article

This paper proposes an experimental methodology for the systematic determination of the equivalent circuit parameters of three winding high frequency transformers (3W-HFTs) for modeling the electrical behavior and the power losses of triple active bridge (TAB) power converters intended for onboard electric vehicle charging applications. For modeling the 3W-HFTs, a comprehensive lumped element equivalent circuit is adopted, and its electrical and electromagnetic parameters are determined through a structured sequence of open-circuit and short-circuit measurements performed over a wide frequency range from 20 Hz to 13 MHz using a precision impedance analyzer to thoroughly investigate impedance resonance behavior, while wide-bandgap power electronic devices are employed. The comparison between the lumped element impedance model and the measured impedance responses demonstrates strong agreement in terms of both magnitude and phase across the frequency range under study. Furthermore, the comparison of simulation results and experimental measurements performed on a TAB prototype under both open-circuit and load operating conditions validates the 3W-HFT electrical characteristics and the estimation of TAB’s power losses distribution. The close consistency between experimental results and simulation outcomes confirms the effectiveness of the proposed characterization approach. Full article

Ultra-fast electric vehicle (EV) charging systems are among the most demanding converter-dominated applications due to their high power levels, wide battery-voltage range, strict thermal constraints, and the need for adaptive charging control. Conventional design and tuning approaches often rely on fixed control policies and computationally expensive iterative optimization, which limits their ability to address nonlinear multi-objective trade-offs across the full charging envelope. This paper proposes a hybrid AI–quantum co-design framework for a SiC-based dual active bridge (DAB) converter intended for ultra-fast EV charging applications. The proposed approach combines a physical converter model, an AI surrogate-learning layer for rapid prediction of converter performance, and a quantum-assisted optimization layer for multi-objective exploration of design and control variables. To demonstrate the framework, a representative modular 350 kW ultra-fast charging case study is considered, implemented by four parallel 87.5 kW SiC-based DAB modules and including converter-level optimization and adaptive charging-policy refinement. The revised manuscript introduces a complete system schematic, an explicit DAB converter topology, a clarified methodological workflow, and a simulation-based proof-of-concept evaluation. Representative results indicate improved design-space exploration and more balanced trade-offs between efficiency, thermal stress, ripple, and dynamic response compared with a conventional baseline tuning approach. Although the study does not claim hardware-level quantum advantage, it provides a structured and practically interpretable computational framework for intelligent co-design of high-power charging converters. Full article

Driven by demanding global emission regulations and the urgent requirements for sustainable mobility, Electric Vehicles (EVs) have emerged as the primary alternative to Internal Combustion Engine (ICE) vehicles. Central to this transition is the electric propulsion system (EPS), a multidisciplinary integration of power electronics, advanced motor drives, and electrochemical energy storage. This paper provides a comprehensive overview of the current landscape of power electronic drives, focusing on the evolution of high-efficiency traction motors and next-generation energy storage systems (ESSs), and advancements in ultra-fast chargers. The analysis explores the vital impact of power converters, evaluating recent breakthroughs in wide-bandgap (WBG) semiconductors and advanced control topologies that enhance energy density and thermal management. Furthermore, the study identifies critical challenges in the design, modulation, and operational reliability of converters under dynamic automotive environments. By synthesizing current research trends and technical bottlenecks, this paper offers insights into the future trajectory of power electronics in achieving high-performance, cost-effective, and carbon-neutral transportation. Full article