Search Results (314)

This paper presents a comprehensive review of state-of-the-art developments in electric vehicle (EV) charging technologies, charging stations, and charging protocols, with particular emphasis on their integration with renewable energy sources (RESs). EV chargers are generally classified into on-board and off-board configurations. This study examines recent designs and advanced control strategies for both AC/DC and DC/DC power conversion stages, highlighting key technical aspects, recent innovations, and existing challenges. Furthermore, it provides an in-depth discussion of emerging multiport EV charger architectures that integrate photovoltaic (PV) systems, energy storage units, EVs, and the power grid within a unified framework. A comparative analysis is also presented to evaluate various converter topologies and energy management strategies used in the AC/DC and DC/DC stages of EV charging systems. Critical performance indicators such as power rating, output voltage level, efficiency, economic feasibility, and system complexity are also discussed. A comprehensive comparison is conducted among 13 review papers between 2015 and 2026, identifying key trends, methodological differences, and common findings. Full article

Direct renewable-to-load systems have emerged as a promising pathway for improving local renewable energy utilization for large electricity consumers under constrained grid interaction and device operating limits. This paper investigates a park-level direct renewable-to-load system integrating battery energy storage and power-to-hydrogen facilities and formulates its operation problem as a sequential continuous-control task. A Deep Deterministic Policy Gradient (DDPG)-based scheduling framework is developed to explicitly model renewable generation, load demand, battery dynamics, hydrogen conversion and inventory evolution, renewable curtailment, storage-related operating cost, and the no-power-export operating boundary. Case studies based on measured wind/PV and load time-series data demonstrate that coordinated heterogeneous storage can effectively enhance system flexibility. Compared with single-type storage configurations, the coordinated battery–hydrogen scheme achieved the best overall storage performance, reducing the daily operating cost to CNY $25.28\times {10}^4$/day while increasing renewable energy utilization to 54.79%. Further benchmarking against MILP, GA, and a without-storage baseline shows that, although MILP remains the best offline benchmark, the proposed DDPG method provides a favorable trade-off between solution quality and online efficiency. Specifically, DDPG achieved an operating cost of CNY $20.93\times {10}^4$/day and a renewable energy utilization of 514.38 MWh, while requiring only 0.25 s/step for online inference. Typical-day analysis further reveals a clear functional complementarity between the two storage types; battery storage mainly provides fast short-term regulation, whereas the hydrogen subsystem mainly supports longer-duration energy shifting. These results indicate that the proposed framework offers a practical and efficient solution for the operation optimization of direct renewable-to-load systems under no-power-export constraints. Full article

The rapid expansion of photovoltaic (PV) generation has increased the need for educational and experimental platforms that allow students and researchers to study the dynamics, control strategies, and power conversion stages of grid-connected PV systems under realistic operating conditions. Although Hardware-in-the-Loop (HIL) simulation is widely used to validate power electronic converters and control algorithms, many existing platforms rely on specialized real-time simulators that limit their accessibility in academic environments. This paper presents the design and implementation of a cost-effective HIL simulation platform for grid-connected PV systems intended for research and training applications. The proposed system integrates real hardware under test within a real-time environment that emulates PV array behavior and grid conditions, combining Controller Hardware-in-the-Loop (CHIL) and Power Hardware-in-the-Loop (PHIL) techniques. A Texas Instruments C2000 microcontroller is used as the real-time digital simulator, providing an accessible alternative to conventional real-time simulation platforms. The platform architecture, the real-time PV emulator, and the experimental implementation are described and validated through simulation and experimental results. Finally, guided laboratory practices are presented to support hands-on training in PV systems and power electronics. Full article

The increasing penetration of inverter-based renewable energy sources has significantly reduced system inertia, leading to faster frequency deviations in low-inertia power systems. This paper proposes an asynchronous distributed model predictive control (AD-MPC) strategy to coordinate flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) for enhanced frequency stability in low-inertia power grids. A modified IEEE 39-bus system integrating a 3 MW wind energy conversion system (WECS), a 2 MW PV solar unit, and an electric vehicle (EV) load emulator unit was simulated to evaluate the system performance of the controller under a 30% increase in load disturbance. The results show that the coordinated FESS–BESS operation using the proposed AD-MPC controller achieves faster frequency recovery and reduces frequency deviation by 4% compared to single storage configurations. The proposed approach demonstrates that the high-speed FESS can provide a rapid inertial response, while the BESS delivers primary frequency support, offering a promising solution for maintaining dynamic stability in future renewable-dominated power systems. Full article

Thin-film solar cells (TFSCs) remain a cornerstone of the global transition toward renewable energy, characterized by consistent reductions in manufacturing costs and steady gains in power conversion efficiency. In addition to electricity generation, TFSCs play an important role in advanced solar thermal cooling, heating, and energy storage systems, where their tunable optical absorption, low thermal mass, and flexibility enable integration with photovoltaic–thermal (PV/T) collectors, thermally driven cooling cycles, and hybrid thermal–electrical storage architectures. This paper provides a comprehensive review of prominent TFSC technologies, including copper indium gallium selenide (CIGS), cadmium telluride (CdTe/CdS), amorphous silicon (a-Si), copper zinc tin sulfide (CZTS), organic photovoltaics (OPVs), and metal halide perovskite solar cells (PSCs), with a focus on their material structures, performance specifications, and current efficiency benchmarks. Compared to state-of-the-art reviews, this article distinguishes itself by addressing next-generation innovations, cross-domain solar thermal–photovoltaic applications, and economic analysis. Specifically, the integration of machine learning and simulation-based material dynamics is examined to accelerate material discovery, process optimization, and the characterization of novel TFPV components relevant to coupled thermal–electrical energy systems. Furthermore, the study explores how additive manufacturing is transforming the industry through the development of high-efficiency electrodes, electrohydrodynamic atomization for thin-film deposition, and the fabrication of flexible solar arrays suitable for thermally integrated and building-scale energy systems, including space applications. By integrating advancements in module efficiency, scalable manufacturing approaches, and techno-economic analysis, this paper positions TFSCs as sustainable, resource-abundant technologies essential for next-generation solar thermal cooling, heating, and energy storage infrastructures. 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

Grid-connected photovoltaic (PV) systems can serve not only as sources of active power but also as active power conditioners for improving power quality. This paper proposes an integrated control strategy for a single-phase grid-connected reduced-switch-count T-type inverter that simultaneously performs maximum power point tracking (MPPT) without a DC-DC conversion stage, compensates for nonlinear load harmonics, and minimises switching losses through a tailored multi-carrier pulse-width modulation (PWM) algorithm. A novel reference current derivation method based on a single-phase dq transformation framework unifies MPPT and active power filtering within a single control loop. The proposed system was validated through MATLAB/Simulink 2025b simulations for a 3500 W PV array supplying a nonlinear RL load with a full-bridge diode rectifier exhibiting a load current total harmonic distortion (THD) of approximately 46%. Simulation results demonstrate an MPPT efficiency of 99.8% at full irradiance (1000 W/m²), an overall system efficiency above 97%, and a grid current THD below 4% across the full irradiance operating range (0–1000 W/m²). Dynamic performance under step irradiance changes was also evaluated: the DC bus voltage deviation remains within 5 V for P&O step sizes between 0.00005 V and 0.0002 V, and the grid current THD recovers to below 5% within 2–6 grid cycles following each irradiance transition. Full article

Current-source DC links and their associated power converters require continuous conduction mode (CCM), necessitating specialized switching device configurations. These topologies have gained significant attention due to the increasing adoption of current-mode power distribution systems. The operation of a current-source DC-DC converter relies on temporary magnetic energy storage, typically regulated using established switch-mode power conversion techniques. For a stable current step up or step down the use of the tapped inductor concept can provide an ultimate stable solution for current adjustment and the proposed concept is now developed on a step-down current source DC-DC power converter for the first time to reveal in the power electronics field. The use of tapping concept is similar to a coupled inductor and this allows flexible current modification. In this article, this concept is extended to a family of Tapped inductor current-based DC-DC together with soft-switching to reduce the loss of the switching devices. The key advantage is that it can offer a wide range of current conversions with high efficiency. The theoretical and experimental analysis of the proposed converter family is presented. An experimental prototype of the converter was built and tested, operating with a switching frequency of 100 kHz and accommodating input currents ranging from 1 A to 10 A. The converter achieved current conversion ratios of 0.8, 0.67 and 0.57 times the input current, with an output power range of 1 W to 314 W. The maximum efficiency of 88% was achieved at an output power of 314 W. The high efficiency and wide current conversion range of this current-based converter make it suitable for a variety of applications such as current driving LED systems, photovoltaic (PV) system current source control, and constant current fast charging systems for electric vehicles (EVs). Full article

Integrating renewable energy harvesting with wireless power transfer (WPT) introduces complex multi-physics coupling challenges, primarily regarding thermal detuning and conversion inefficiencies within compact enclosures. This study proposes an optimized architecture and analytical framework for a Solar-Driven Portable Energy Storage System (SPESS) that bridges the gap between solar harvesting and autonomous wireless delivery. The system integrates a high-efficiency 5 V monocrystalline photovoltaic (PV) array with a 10,000 mAh lithium-ion core, regulated by an adaptive Maximum Power Point Tracking (MPPT) algorithm. We formalize the synergistic coupling between thermal and electrical subsystems, demonstrating how iterative thermal–electric co-design—utilizing CFD-modeled ventilation and anisotropic graphite spreaders—effectively suppresses capacitive drift in the resonant network. Unlike fixed-frequency chargers, this design employs Phase-Locked Loop (PLL) frequency stabilization to maintain a “High-Q” state, achieving wireless transmission efficiencies exceeding 85% and a measured 12.3% restorative gain in the WPT stage compared to a thermally detuned baseline. Robustness analysis confirms spatial resilience up to 10 mm of lateral misalignment and thermal stabilization at 48 °C under continuous 15 W load, contributing to a calculated 18% extension in battery cycle life via suppressed chemical degradation. Experimental validation across varying irradiance levels (100–1200 W/m²) demonstrates a full recovery cycle of 23.6 cumulative solar hours at Standard Test Conditions (STC). This research provides a scalable, theoretically grounded framework for resilient, self-sustaining energy modules for disaster relief, remote education, and mobile health applications. Full article

In this paper, the dynamic modeling and integrated simulation of a ship microgrid system designed to enhance power quality and energy efficiency in electric propulsion vessels are proposed. The proposed system consists of a photovoltaic (PV) array, a battery energy storage system (BESS), a diesel generator, and a propulsion system, all of which are organically integrated through power conversion devices. To compensate for the intermittent nature of solar power, a control strategy featuring Maximum Power Point Tracking (MPPT) for the PV system and bidirectional DC/DC converter control for the battery was implemented. Specifically, a control logic to stabilize the system output in response to the fluctuating loads of the electric propulsion system was developed using PSCAD (v50) software. The simulation results demonstrate that the proposed control strategy maintains DC-link voltage deviation within ±1.8% and achieves a settling time of less than 0.8 s while optimizing propulsion efficiency (peak-shaving ratio 25–30%) under both constant and variable speed operating conditions. Battery SOC variation is limited to 18–88%, preventing overcharge or discharge. This research provides a foundational framework for the design of energy management systems (EMSs) and grid stability assessments for future eco-friendly electric propulsion ships. Full article

The European Union aims to cut greenhouse gas emissions by 55% by 2030 and reach climate neutrality by 2050, targets that depend on expanding renewable generation in the European energy system. While photovoltaic (PV) capacity has grown quickly in several member states, others remain far behind. This paper frames that divergence as a systems planning problem: installed MW expands through diffusion-like dynamics, but the conversion of investment into energizable capacity is filtered by grid-integration constraints and institutional throughput. The study develops a macro-level framework for systems-level assessment and decision support to guide PV capacity planning and budget allocation using official 2012–2022 data for 22 EU countries. We combine (i) unsupervised clustering of standardized national deployment trajectories, (ii) bounded logistic fits interpreted as an operational diffusion-with-saturation representation that yield comparable growth parameters and maturity years (80–90% of the estimated ceiling), and (iii) a proportional reallocation scenario for countries below 5 GW in 2022. Three clusters emerge—steady growth, early plateau, and atypical paths—and an analytically tractable maturity indicator integrates capacity, rate, and timing in a single measure. In a 10 GW reallocation scenario, average progress toward the 5 GW benchmark rises from 9.8% to 23.1%, closing about 14.8% of the aggregate shortfall. The allocation experiment reveals a clear asymmetry: systems with an existing installed base convert additional MW into benchmark progress more efficiently than very low-baseline systems, where binding constraints are more likely to sit in permitting, interconnection queues, and hosting capacity rather than in finance alone. Turning these allocations into usable capacity depends on timely interconnection and power-electronics integration and on grid-enablement constraints such as interconnection readiness, inverter compliance, and local hosting capacity in high-penetration areas. The contribution is a transparent, updateable decision-support pipeline that links observed trajectory regimes to a maturity “clock” and an auditable allocation baseline, making the trade-off between closing capacity gaps and respecting feasibility filters explicit in an EU system with heterogeneous national subsystems. The proposed approach links macro-level maturity clusters to operational feasibility signals in the grid integration layer, showing that modeling-based allocation can improve system progress but cannot substitute grid-enablement measures, highlighting the importance of regional coordination in the EU energy system under heterogeneous national trajectories. Full article

This paper presents the analysis, design, and experimental validation of a Partial Power Processing (PPP) Single-Ended Primary Inductor Converter (SEPIC) for photovoltaic (PV) applications. The proposed topology limits the fraction of processed power through the active switching stage, thereby reducing MOSFET RMS current and associated conduction losses and improving overall conversion efficiency. A complete analytical framework is developed, including steady-state modeling, state-space formulation, and small-signal analysis. The theoretical results are validated through MATLAB/Simulink simulations and laboratory-scale experimental tests under multiple loading conditions. Comparative analysis against a conventional Full Power Processing (FPP) SEPIC converter demonstrates that the proposed PPP configuration achieves efficiencies up to 95% in simulation and up to 93% experimentally, compared to 87% for the FPP counterpart under identical nominal conditions ($V_{\mathrm{in}}=18$ V, $f_{\mathrm{s}}=70$ kHz). Additionally, the PPP approach reduces the MOSFET RMS current by more than 50%, which directly translates into lower conduction losses and reduced device power dissipation. The results confirm that the proposed PPP-SEPIC converter constitutes a technically viable and energy-efficient solution for photovoltaic DC–DC power conversion systems. Full article

Given the rising global demand for environmentally sustainable energy sources, solar photovoltaic (PV) power generation has emerged as a pivotal component of the energy transition. In PV systems, power conversion efficiency is degraded and operational lifespan reduced due to the presence of defective modules. Consequently, achieving accurate and efficient defect detection during PV module manufacturing is critical to ensuring product quality and reliability. To address this challenge, we propose MambaVSS-YOLOv11n, an electroluminescence (EL) image-based multi-defect detection method for PV modules. Our study utilizes a dataset containing six types of defects—Broken Gate, Cold Solder Joint, Black Spot, Scratch, Microcrack, and Suction Mark—to construct 692 labeled EL images of defective PV modules. The model integrates the Vision State Space (VSS) module from Mamba and optimizes the C3k2 Bottleneck structure to enhance fine-grained feature extraction, while employing Space-to-Depth Convolutional (SPD-Conv) Layer for downsampling to improve computational efficiency. Additionally, to address YOLOv11n’s limited generalization capability for small objects and complex backgrounds, we adopt the Inner Mask Distance Penalized Intersection over the Union (Inner-MDPIoU) loss function, which enhances detection accuracy and mitigates the impact of low-quality samples. Experimental results demonstrate that compared to YOLOv11n, MambaVSS-YOLOv11n reduces the number of parameters by 18.1%, while improving mAP@0.5 to 0.869 and mAP@0.5:0.95 to 0.637. This achieves model lightweighting while enhancing detection performance. These findings indicate that the model is well-suited for real-time defect detection in PV module production lines, providing PV manufacturers with a lightweight yet accurate and reliable solution for PV module defect inspection. Full article

The integration of renewable energy sources, including photovoltaic (PV) and fuel cell (FC) systems, into AC grids has attracted immense research interest in recent times. Furthermore, incorporating these renewable sources of energy into medium-voltage grids is garnering increased attention because of the obvious benefits of medium-voltage integration at elevated power levels. Photovoltaic applications entail the arrangement of solar panels capable of outputting voltages up to 1.5 kV; nonetheless, fuel cells display restricted output voltage, with a maximum market range of 400 to 700 V. Hence, the efficient integration of renewable energy sources into low-voltage or medium-voltage grids demands the utilization of a step-up direct current (DC–DC) inverter and a converter for connection to the alternating current (AC) grid, in which an efficient step-up converter is critical for the medium-voltage grid. Therefore, this study presents a three-phase buck-boost split-source inverter (BSSI) that resolves the constrained output voltage of the fuel cells. This study focuses on modifying the configuration of a conventional three-phase split-source inverter (SSI) circuit by adding a few components while maintaining the inverter’s modulation. This novel circuit design enables the reduction in voltage strains on the inverter switch components and improves DC-link use in relation to a traditional SSI configuration. For an 800 bus, maximal voltage stress on the primary inverter switches is lowered when compared with the standard SSI that delivers entire DC-bus voltage to switches. A rectifier-based model is employed to simulate the behavior of a renewable energy source. Combining these advantages with the conventional modulation of the inverter offers a more effective design. The buck-boost split-source inverter (BSSI) was analyzed using three distinct modulation techniques: the sinusoidal pulse-width modulation scheme (SPWM), the third-harmonic injected pulse-width modulation (THPWM) scheme, and space vector modulation (SVM). The proposed analysis was validated through MATLAB-SIMULINK and practical outcomes on a 5.0 kW model. The practical and SIMULINK data were found to be closely aligned with the analysis. The circuit developed in this study also ensures efficient DC-to-AC conversion, specifically with regard to low-voltage sources, like fuel cells or photovoltaic (PV) systems. Full article

This paper presents a PSCAD-based analysis of short-circuit faults and protection characteristics in a real distribution-level microgrid that integrates a 1 MWh battery energy storage system (BESS) with a 500 kW power conversion system (PCS) and a 500 kW photovoltaic (PV) plant connected to a 22.9 kV feeder. While previous studies often rely on simplified inverter models, this paper addresses the critical gap by integrating actual manufacturer-defined control parameters and cable impedances. This allows for a precise analysis of sub-millisecond transient behaviors, which is essential for developing robust protection schemes in inverter-dominated microgrids. The PSCAD model is first verified under grid-connected steady-state operation by examining PV output, BESS power, and grid voltage at the point of common coupling. Based on the validated model, DC pole-to-pole faults at the PV and ESS DC links and a three-phase short-circuit fault at the low-voltage bus are simulated to characterize the fault current behavior of the grid, BESS and PV converters. The DC fault studies confirm that current peaks are dominated by DC-link capacitor discharge and are strongly limited by converter controls, while the AC three-phase fault is mainly supplied by the upstream grid. As an initial application of the model, an instantaneous current change rate (ICCR) algorithm is implemented as a dedicated DC-side protection function. For a pole-to-pole fault, the ICCR index exceeds the 100 A/ms threshold and issues a trip command within 0.342 ms, demonstrating the feasibility of sub-millisecond DC fault detection in converter-dominated systems. Beyond this example, the validated PSCAD model and associated data set provide a practical platform for future research on advanced DC/AC protection techniques and protection coordination schemes in real BESS–PV microgrids. Full article