Search Results (152)

Electrochemical processes within a lithium-ion battery cause electrode expansion and gas generation, thus resulting in battery swelling and, in severe cases, reliability and safety issues. This paper presents the mechanisms responsible for swelling, including thermal expansion, lithium intercalation, electrode interphase layer growth, lithium plating, and gas generation, while highlighting their dependence on material properties, design considerations, C-rate, temperature, state of charge (SoC), and voltage. The paper then discusses how swelling correlates with capacity fade, impedance rise, and thermal runaway, and demonstrates the potential of using swelling as a diagnostic and prognostic metric for battery health. Swelling models that connect microscopic mechanisms to macroscopic deformation are then presented. Finally, the paper presents strategies to mitigate swelling, including materials engineering, surface coatings, electrolyte formulation, and mechanical design modifications. Full article

In the current energy landscape, power quality (PQ) emerges as a critical concern. Even when there is no fault on a line, PQ issues are common in all power networks since 90% of power systems’ loads are variable or inductive in nature. Variable loads cannot be avoided; hence, PQ concerns such as voltage swelling and sag will always arise. Voltage sag is one of the main issues within a distribution network, resulting in financial losses for the utility company and the customer. The Dynamic Voltage Restorer (DVR) effectively addresses voltage sags and minimizes total harmonic distortion (THD) in the distribution network. This paper proposed a novel control strategy to increase the PQ in a system. A Frilled Lizard Optimization-optimized fuzzy PI controller is proposed in this work to control the inverter. This proposed method improves the DVR’s ability to correct voltage sag and reduce total harmonic distortion as soon as possible. The PI control scheme is utilized initially to reduce the oscillations and remove the steady-state error. To increase the tendency rate of the error to zero, the PI method is applied to a fuzzy logic-based compensatory stage. The proposed approach is validated using pro-type models, as well as mathematical and Simulink modelling. In the Results Section, the performance of the proposed controllers with the DVR is tabulated and compared with other DVR controller schemes described in other research papers. Full article

Modern utility systems are being heavily strained by rising energy consumption and dynamic load variations, which have an impact on the quality and reliability of the supply. Harmonic injection and reactive power imbalance are caused by the widespread divergence. Power quality (PQ) issues are mostly caused by renewable energy powered by power electronic converters that are integrated into the utility grid, despite the fact that a range of industries require high-quality power to function properly at all times. Several solutions have been created, but continuing efforts and newly improved solutions are needed to solve these problems by operating according to various international standards. Distributed Static Compensator (DSTATCOM) was created in the proposed model to enhance PQ in a standard bus system. A standard bus system using the DSTATCOM model was initially developed. A real-time dataset was gathered while applying various PQ disturbance conditions. A deep learning controller was created using this generated dataset, which examined the bus voltages to generate the DSTATCOM pulse signal. Two case studies, the IEEE 13 bus and the IEEE 33 bus system, were used to analyze the proposed work. Performance of the proposed deep learning controller was verified in various situations, including interruption, swell, harmonics, and sag. The outcome of THD in the IEEE 13 bus is 0.09% at the sag period, 0.08% at the swell period, 0.01% at the interruption period, and in the IEEE 33 bus was 1.99% at the sag period, 0.44% at the swell period, and 0.01% at the interruption period. Also, the effectiveness of the proposed deep learning controller was examined and contrasted with current methods like K-Nearest Neighbor (KNN) and Feed Forward Neural Network (FFNN). The validated results show that the suggested method provides an efficient mitigation mechanism, making it suitable for all cases involving PQ issues. Full article

In low-voltage (LV) distribution networks, system operating conditions are always unbalanced due to the unpredictability of the load demand in each phase, coupled with a potentially asymmetrical network structure due to different phase conductors’ sizes and lengths. The widespread diffusion of distributed generators (DGs) among network users has significantly contributed to reducing the overall load of the electrical system, but at the cost of making voltages slightly more unbalanced. In this article, an LV distribution test network equipped with several single-phase DGs has been considered, and all During-Fault Voltages (DFVs) have been studied, according to each possible type of short circuit. To provide a measure of the asymmetry of unsymmetrical voltage dips, three different indices based on the symmetrical components of the voltages have been considered; moreover, the Monte Carlo simulation (MCS) method has allowed for studying faults and asymmetries in a probabilistic manner. Through the probability density functions (pdfs) of the DFVs, it has been possible to assess the impact of single-phase DGs on the asymmetry of bus voltages due to short-circuits. Full article

Aquaporins (AQPs) are membrane proteins that facilitate the transport of water and solutes. Among AQPs, plasma membrane intrinsic proteins (PIPs) play a critical role in maintaining water balance between the internal and external cell environments. This study focuses on the tomato due to its economic importance and cultivation under moderate salinity conditions in Japan. A swelling assay using X. laevis oocyte confirmed that all five examined tomato SlPIP2 isoforms showed water transport activity. Among them, two-electrode voltage clamp (TEVC) experiments showed that only SlPIP2;1, SlPIP2;4, and SlPIP2;8 transport Na⁺ and K⁺, with no transport activity for Cs⁺, Rb⁺, Li⁺, or Cl⁻. CaCl₂ (1.8 mM) reduced ionic currents by approximately 45% compared to 30 µM free-Ca²⁺. These isoforms function as very low-affinity Na⁺ and K⁺ transporters. Expression analysis showed that SlPIP2;4 and SlPIP2;8 had low, stable expression, while SlPIP2;1 was strongly upregulated in roots NaCl treatment (200 mM, 17days), suggesting distinct physiological roles for these ion-conducting AQPs (icAQPs). These data hypothesized that tomato icAQPs play a critical role in ion homeostasis, particularly under salinity stress. In conclusion, the first icAQPs have been identified in the dicotyledonous crop. These icAQPs are essential for plant resilience under salt stress. Full article

This paper proposes a Hybrid Adaptive Learning-Based Control (HALC) algorithm for voltage regulation in grid-forming inverters (GFIs), addressing the challenges posed by voltage sags and swells. The HALC algorithm integrates two key control strategies: Model Predictive Control (MPC) for short-term optimization, and reinforcement learning (RL) for long-term self-improvement for immediate response to grid disturbances. MPC is modeled to predict and adjust control actions based on short-term voltage fluctuations while RL continuously refines the inverter’s response by learning from historical grid conditions, enhancing overall system stability and resilience. The proposed multi-stage control framework is modeled based on a mathematical representation using a control feedback model with dynamic optimal control. To enhance voltage stability, Lyapunov is used to operate across different time scales: milliseconds for immediate response, seconds for short-term optimization, and minutes to hours for long-term learning. The HALC framework offers a scalable solution for dynamically improving voltage regulation, reducing power losses, and optimizing grid resilience over time. Simulation is conducted and the results are compared with other existing methods. Full article

In recent years, DC grids have gained traction, and several proposals regarding measuring strategies and several Power Quality (PQ) parameters have been defined to be used in such networks that differ from traditional AC power grids. As a complement to all this preliminary work, this study on the effect of modifying the sampling frequency on some of those parameters has been conducted. For time series evaluation of mean and RMS voltage values, the Dynamic Time Warping (DTW) algorithm has been used. Additionally, the consequence of varying the sampling rate in voltage event detection has also been analysed. As a result, relevant advice regarding sampling frequency is presented in this paper for an effective and optimum evaluation of RMS or mean voltage values and its implementation in detecting voltage events (dips or swells). At least for the parameters in the monitored DC microgrid, a clue for the minimum sampling rate that guarantees accurate measurements is found. Full article

This paper proposes a novel control strategy for a dual-stage grid-connected solar photovoltaic (PV) system designed to ensure reliable and efficient operation under unstable grid conditions. The strategy incorporates a Phase-Locked Loop (PLL)-based positive sequence estimator for accurate detection of grid voltage disturbances, including sags, swells, and fluctuations in solar irradiance. A dynamic DC-link voltage regulation mechanism is employed to minimize converter power losses and enhance the performance of the Voltage Source Converter (VSC) under weak grid scenarios. The control scheme maintains continuous maximum power point tracking (MPPT) and unity power factor (UPF) operation, thereby improving overall grid power quality. The proposed method is validated through comprehensive simulations and real-time hardware implementation using the OPAL-RT OP4510 platform. The results demonstrate compliance with IEEE Standard 519, confirming the effectiveness and robustness of the proposed strategy. Full article

This work proposes an effective control technique for enhancing the stability of Doubly Fed Induction Generator-Based Wind Turbines (DFIG-WTs) connected to the grid during voltage sag and swell events, ensuring the reliable and efficient operation of wind energy systems integrated with the grid. The proposed approach integrates a Dynamic Voltage Restorer (DVR) in series with a Wind Turbine Generator (WTG) output terminal to enhance the Fault Ride-Through (FRT) capability during grid disturbances. To develop a flexible control strategy for both unbalanced and balanced fault conditions, a combination of feedforward and feedback control based on a sliding mode control (SMC) for DVR converters is used. This hybrid strategy allows for precise voltage regulation, enabling the series compensator to inject the required voltage into the grid, thereby ensuring constant generator terminal voltages even during faults. The SMC enhances the system’s robustness by providing fast, reliable regulation of the injected voltage, effectively mitigating the impact of grid disturbances. To further enhance system performance, Model Predictive Control (MPC) is implemented for the Rotor-Side Converter (RSC) within the back-to-back converter (BTBC) configuration. The main advantages of the predictive control method include eliminating the need for linear controllers, coordinate transformations, or modulators for the converter. Additionally, it ensures the stable operation of the generator even under severe operating conditions, enhancing system robustness and dynamic response. To validate the proposed control strategy, a comprehensive simulation is conducted using a 2 MW DFIG-WT connected to a 120 kV grid. The simulation results demonstrate that the proposed control approach successfully limits overcurrent in the RSC, maintains electromagnetic torque and DC-link voltage within their rated values, and dynamically regulates reactive power to mitigate voltage sags and swells. This allows the WTG to continue operating at its nominal capacity, fully complying with the strict requirements of modern grid codes and ensuring reliable grid integration. Full article

Doubly Fed Induction Generator (DFIG)-based Wind Energy Systems (WESs) have become increasingly prominent in the global energy sector, owing to their superior efficiency and operational flexibility. Nevertheless, DFIGs are notably vulnerable to fluctuations in the grid, which can result in power quality issues—including voltage swells, sags, harmonic distortion, and flicker—while also posing difficulties in complying with Fault Ride-Through (FRT) standards established by grid regulations. To address the previously mentioned challenges, this paper develops an integrated approach utilizing a Dynamic Voltage Restorer (DVR) in conjunction with a Lithium-ion storage system. The DVR is coupled in series with the WES terminal, while the storage system is coupled in parallel with the DC link of the DFIG through a DC/DC converter, enabling rapid voltage compensation and bidirectional energy exchange. Simulation results for a 2 MW WES employing DFIG modeled in MATLAB/Simulink demonstrate the efficacy of the proposed system. The approach maintains terminal voltage stability, reduces Total Harmonic Distortion (THD) to below 0.73% during voltage sags and below 0.42% during swells, and limits DC-link voltage oscillations within permissible limits. The system also successfully mitigates voltage flicker (THD reduced to 0.41%) and harmonics (THD reduced to 0.4%), ensuring compliance with IEEE Standard 519. These results highlight the proposed system’s ability to enhance both PQ and FRT capabilities, ensuring uninterrupted wind power generation under various grid disturbances. Full article

Silicon oxide–graphite is a promising high-capacity anode material for next-generation lithium-ion batteries (LIBs). However, despite using a small fraction (≤5%) of Si, it suffers from a short cycle life owing to intrinsic swelling and particle pulverization during cycling, making practical application challenging. High-nickel (Ni ≥ 80%) oxide cathodes for high-energy-density LIBs and their operation beyond 4.2 V have been pursued, which requires the anodic stability of the electrolyte. Herein, we report a nonflammable multi-functional fluorinated ester–based liquid electrolyte that stabilizes the interfaces and suppresses the swelling of highly loaded 5 wt% SiO–graphite anode and LiNi_0.88Co_0.08Mn_0.04O₂ cathode simultaneously in a 3.5 mAh cm⁻² full cell, and improves cycle life and battery safety. Surface characterization results reveal that the interfacial stabilization of both the anode and cathode by a robust and uniform solid electrolyte interphase (SEI) layer, enriched with fluorinated ester-derived inorganics, enables 80% capacity retention of the full cell after 250 cycles, even under aggressive conditions of 4.35 V, 1 C and 45 °C. This new electrolyte formulation presents a new opportunity to advance SiO-based high-energy density LIBs for their long operation and safety. Full article

Dual Maximum Power Point Tracking (MPPT) inverters are essential in residential and small commercial solar power systems, optimizing power extraction from two independent solar panel arrays to enhance efficiency and energy harvesting. On the other hand, the Three-Level T-Type Voltage Source Inverter (3L T-Type VSI) is known for its reduced switching losses, improved harmonic distortion, and reduced part count in comparison to other three-level topologies. In this paper, a novel architecture is proposed to integrate the dual MPPT structure directly to each DC-side split capacitor of the 3L T-Type VSI, taking advantage of the intrinsic characteristics of the inverter’s topology. Further performance enhancement is achieved by integrating a classical MPPT strategy to the control framework to make it feasible for a real-case grid integration. The combination of these methods ensures faster and stable tracking under dynamic irradiance conditions. Considering that strategies dedicated to balancing the DC-link capacitor’s voltage slightly affect the AC-side current waveform, an enhanced sliding mode control (SMC) strategy tailored for dual MPPT and 3L T-Type VSI is deployed, combining the simplicity of conventional PI controllers used in the independent MPPT-based DC-DC converters with the superior robustness and dynamic performance of SMC. Real-time results obtained using the OPAL-RT Hardware-in-the-Loop platform validated the performance of the proposed control strategy under realistic test scenarios. The current THD was maintained below 4.8% even under highly distorted grid conditions, and the controller achieved a steady state within approximately 15 ms following perturbations in the DC-link voltage, sudden irradiance variations, and voltage sags and swells. Additionally, the power factor remained unitary, enhancing power transfer from the renewable source to the grid. The proposed system was able to achieve efficient power extraction while maintaining high power quality (PQ) standards for the output, positioning it as a practical and flexible solution for advanced solar PV systems. Full article

The creation of quick-reacting electrically conductive polymers for use as actuators driven by low electrical currents is now seen as an important issue. Enhancing the electrical conductivity of hydrogels through the incorporation of conductive fillers, like salts, can reduce the necessary actuating voltage. However, several important questions arise about how the type of salt chosen and its concentration will affect not only the activation efficiency of the actuators but also the structure of the hydrogels utilized. In this study, to enhance the electrical conductivity of the hydrogel and lower the necessary activation voltage of the hydrogel actuators, lithium chloride (LiCl) and sodium chloride (NaCl) were incorporated as conductive fillers into the polyvinyl alcohol (PVA) polymer matrix. To determine the deformation of actuators, as well as the activation and relaxation times and efficiencies during activation, linear actuators capable of being activated through extension/contraction (swelling/shrinking) cycles were developed and examined based on the LiCl/NaCl content, applied voltage, and frequency. The main finding is that the required actuating voltage was lowered by up to 20 V by adding an equal mass of salt in relation to the PVA mass content. With a load of around 20 kPa, it was observed that the extension deformation for PVA/NaCl-based actuators can achieve 75%, while in contraction deformation, can reach 17%. Additionally, for the PVA/LiCl-based actuators, the extension deformation can reach 87%, while during contraction deformation, it can reach 22%. The degree of swelling in the PVA/NaCl hydrogels was generally less than that in the PVA/LiCl hydrogels, which was associated with the finding that the actuators prepared from PVA/NaCl hydrogels delivered an output that was 10–15% lower than those made from PVA/LiCl hydrogels across different testing cycles. Furthermore, adding salt increases the degree of crosslinking, which can explain why increased crosslinking leads to reduced deformation when exposed to AC voltage. These actuators can find extensive use in soft robotics, artificial muscles, medical applications, and aerospace industries. Full article

This article proposes a multiscale classification framework for detecting voltage disturbances in electrical distribution systems using artificial neural networks (ANNs) combined with the Hilbert–Huang transform (HHT). The framework targets four core power quality (PQ) events defined in the IEEE 1159-2019 standard: normal operation and voltage sag, swell, and interruption. Unlike traditional methods that operate on a fixed disturbance duration, our approach incorporates multiple time scales (0.2 s, 0.4 s, and 0.8 s) to improve detection robustness across varied event lengths, a critical factor in real-world scenarios where disturbance durations are unpredictable. Features are extracted using empirical mode decomposition (EMD) and Hilbert spectral analysis, enabling accurate representation of the signals’ non-stationary and nonlinear characteristics. The ANN is trained using statistical descriptors derived from the first two intrinsic mode functions (IMFs), capturing both amplitude and frequency content. The method was validated in MATLAB on the IEEE 33-bus radial distribution test system using simulated disturbances. The proposed model achieved a classification accuracy of 94.09% and demonstrated consistent performance across all time windows, supporting its suitability for real-time monitoring in smart distribution networks. This study contributes a scalable and adaptable solution for automated PQ event classification under variable conditions. Full article

This paper proposes a supercapacitor-battery hybrid energy storage scheme based on a series-parallel hybrid compensation structure and model predictive control to address the increasingly severe power quality issues in oilfield microgrids. By adopting the series-parallel hybrid structure, the voltage compensation depth can be properly improved. The model predictive control with a current inner loop is employed for current tracking, which enhances the response speed and control performance. Applying the proposed hybrid energy storage system in an oilfield DC microgrid, the fault-ride-through ability of renewable energy generators and the reliable power supply ability for oil pumping unit loads can be improved, the dynamic response characteristics of the system can be enhanced, and the service life of energy storage devices can be extended. This paper elaborates on the series-parallel compensation topology, operational principles, and control methodology of the supercapacitor-battery hybrid energy storage. A MATLAB/Simulink model of the oilfield DC microgrid employing the proposed scheme was established for verification. The results demonstrate that the proposed scheme can effectively isolate voltage sags/swells caused by upstream grid faults, maintaining DC bus voltage fluctuations within ±5%. It achieves peak shaving of oil pumping unit load demand, recovery of reverse power generation, stabilization of photovoltaic output, and reduction of power backflow. This study presents an advanced technical solution for enhancing power supply quality in high-penetration renewable energy microgrids with numerous sensitive and critical loads. Full article