Search Results (1,176)

Hybrid AC/DC microgrids have emerged as a promising solution for integrating diverse renewable energy sources, enhancing efficiency, and strengthening resilience in modern power systems. However, existing control schemes exhibit critical shortcomings that limit their practical effectiveness. Traditional linear controllers, designed around nominal operating points, often fail to maintain stability under large load and generation fluctuations. Optimization-based methods are highly sensitive to model inaccuracies and parameter uncertainties, reducing their reliability in dynamic environments. Intelligent approaches, such as fuzzy logic and ML-based controllers, provide adaptability but suffer from high computational demands, limited interpretability, and challenges in real-time deployment. These limitations highlight the need for robust control strategies that can guarantee reliable operation despite disturbances, uncertainties, and varying operating conditions. Numerical performance indices demonstrate that the reviewed robust control strategies outperform conventional linear, optimization-based, and intelligent controllers in terms of system stability, voltage and current regulation, and dynamic response. This paper provides a comprehensive review of recent robust control strategies for hybrid AC/DC microgrids, systematically categorizing classical model-based, intelligent, and adaptive approaches. Key research gaps are identified, including the lack of unified benchmarking, limited experimental validation, and challenges in integrating decentralized frameworks. Unlike prior surveys that broadly cover microgrid types, this work focuses exclusively on hybrid AC/DC systems, emphasizing hierarchical control architectures and outlining future directions for scalable and certifiable robust controllers. Also, comparative results demonstrate that state of the art robust controllers—including H∞-based, sliding mode, and hybrid intelligent controllers—can achieve performance improvements for metrics such as voltage overshoot, frequency settling time, and THD compared to conventional PID and droop controllers. By synthesizing recent advancements and identifying critical research gaps, this work lays the groundwork for developing robust control strategies capable of ensuring stability and adaptability in future hybrid AC/DC microgrids. Full article

This study systematically investigated the structural damage and electrochemical performance changes in 18650 cylindrical lithium-ion batteries under multiple impacts through a 10 kg drop-hammer impact test. The experimental results showed that as the state of charge (SOC) increased from 25% to 75%, the battery’s stiffness increased and its impact resistance improved, but the electrolyte leakage intensified, with a higher risk of leakage at high SOCs. An increase in the impact force led to enhanced voltage fluctuations and a continuous increase in deformation. After an impact of 500 mm, the voltage decreased about 0.02 V, while after an impact of 1000 mm, it dropped about 0.04 V. Axial impacts caused a sudden voltage drop to 1.96 V, resulting in permanent failure; compared with planar impacts, cylindrical surface impacts are more likely to cause compression in the middle and warping at both ends, significantly increasing the risk of internal short circuits. CT scans revealed that the battery porosity can reach up to 3.09% under high impact energy, and the deformation rate can reach 28.39%. The research results provide a quantitative experimental basis for the impact-resistant design and safety assessment of power batteries. Full article

With the rapid development of renewable energy and the continuous pursuit of efficient energy utilization, distributed photovoltaic power generation has been widely used in village-level microgrids. As a key platform connecting distributed photovoltaics with users, energy storage systems play an important role in alleviating the imbalance between supply and demand in VMG. However, current energy storage systems rely heavily on lithium batteries, and their frequent charging and discharging processes lead to rapid lifespan decay. To solve this problem, this study proposes a hybrid energy storage system combining supercapacitors and lithium batteries for VMG, and designs a hybrid energy storage scheduling strategy to coordinate the “source–load–storage” resources in the microgrid, effectively cope with power supply fluctuations and slow down the life degradation of lithium batteries. In order to give full play to the active support ability of supercapacitors in suppressing grid voltage and frequency fluctuations, the scheduling optimization goal is set to maximize the sum of the virtual inertia time constants of the supercapacitor. In addition, in order to efficiently solve the high-complexity model, the reason for choosing the snow goose algorithm is that compared with the traditional mathematical programming methods, which are difficult to deal with large-scale uncertain systems, particle swarm optimization, and other meta-heuristic algorithms have insufficient convergence stability in complex nonlinear problems, SGA can balance global exploration and local development capabilities by simulating the migration behavior of snow geese. By improving the convergence effect of SGA and constructing a multi-objective SGA, the effectiveness of the new algorithm, strategy and model is finally verified through three cases, and the loss is reduced by 58.09%, VMG carbon emissions are reduced by 45.56%, and the loss of lithium battery is reduced by 40.49% after active support optimization, and the virtual energy inertia obtained by VMG from supercapacitors during the scheduling cycle reaches a total of 0.1931 s. Full article

With the increasing penetration of renewable energy, traditional distribution network operation state assessment methods based on typical operating conditions are no longer applicable. It is urgent to conduct risk assessment research on the dynamic coupling characteristics of voltage, power flow, and distributed generation output after photovoltaic integration into active distribution networks. This paper first analyzes the spatiotemporal variation characteristics of power flow distribution and voltage fluctuations in active distribution networks, and proposes evaluation indicators for power flow and voltage over limit risks. Secondly, feature quantities related to the over limit risk assessment indicators are selected, and a distribution network over limit risk assessment method based on TCN-Transformer neural network architecture is proposed. Finally, based on the improved IEEE 33 node distribution network model, an active distribution network simulation model is built in Matlab(2023b), and a simulation dataset is constructed for multiple operating scenarios. On this basis, a comparative analysis of risk assessment examples for power flow and voltage exceeding limits is conducted, and the results verify the effectiveness and superiority of the proposed method. Full article

Feedthrough interference is inevitably introduced in MEMS gyroscopes due to non-ideal factors such as circuit layout design and fabrication processes, exerting non-negligible impacts on gyroscope performance. This study proposes a feedthrough suppression scheme for MEMS gyroscopes based on mixed-frequency excitation signals. Leveraging the quadratic relationship between excitation voltage and electrostatic force in capacitive resonators, the resonator is excited with a modulated signal at a non-resonant frequency while sensing vibration signals at the resonant frequency. This approach achieves linear excitation without requiring backend demodulation circuits, effectively separating desired signals from feedthrough interference in the frequency domain. A mixed-frequency excitation-based measurement and control system for MEMS gyroscopes is constructed. The influence of mismatch phenomena under non-ideal conditions on the control system is analyzed with corresponding solutions provided. Simulations and experiments validate the scheme’s effectiveness, demonstrating feedthrough suppression through both amplitude-frequency characteristics and scale factor perspectives. Test results confirm the scheme eliminates the zero introduced by feedthrough interference in the gyroscope’s amplitude-frequency response curve and reduces force-to-rebalanced detection scale factor fluctuations caused by frequency split variations by a factor of 21. Under this scheme, the gyroscope achieves zero-bias stability of 0.3118 °/h and angle random walk of 0.2443 °/h/√Hz. Full article

Ultrathin oxide semiconductors are promising channel materials for next-generation thin-film transistors (TFTs), but their performance is severely limited by bulk and interface defects as the channel thickness approaches a few nanometers. In this study, we show that high-pressure hydrogen annealing (HPHA) effectively mitigates these limitations in 3.6 nm thick ZnO TFTs. HPHA-treated devices exhibit a nearly four-fold increase in on-current, a steeper subthreshold swing, and a negative shift in threshold voltage compared to reference groups. X-ray photoelectron spectroscopy reveals a marked reduction in oxygen vacancies and hydroxyl groups, while capacitance–voltage measurements confirm more than a three-fold decrease in interface trap density. Low-frequency noise analysis further demonstrates noise suppression and a transition in the dominant noise mechanism from carrier number fluctuation to mobility fluctuation. These results establish HPHA as a robust strategy for defect passivation in ultrathin oxide semiconductor channels and provide critical insights for their integration into future low-power, high-density electronic systems. Full article

Three-dimensional bulk fin-type field-effect transistors (FinFETs) have been the dominant devices since the sub-22 nm technology node. Electrical characteristics of scaled devices suffer from different process variation effects. Owing to the trapping and de-trapping of charge carriers, random interface traps (RITs) degrade device characteristics, and, to study this effect, this work investigates the impact of RITs on the DC/AC/RF characteristic fluctuations of FinFETs. Under high gate bias, the device screening effect suppresses large fluctuations induced by RITs. In relation to different densities of interface traps (D_it), fluctuations of short-channel effects, including potential barriers and current densities, are analyzed. Bulk FinFETs exhibit entirely different variability, despite having the same number of RITs. Potential barriers are significantly altered when devices with RITs are located near the source end. An analysis and a discussion of RIT-fluctuated gate capacitances, transconductances, cut-off, and 3-dB frequencies are provided. Under high D_it conditions, we observe ~146% variation in off-state current, ~26% in threshold voltage, and large fluctuations of ~107% and ~131% in gain and cut-off frequency, respectively. The effects of the random position of RITs on both AC and RF characteristic fluctuations are also discussed and designed in three different scenarios. Across all densities of interface traps, the device with RITs near the drain end exhibits relatively minimal fluctuations in gate capacitance, voltage gain, cut-off, and 3-dB frequencies. Full article

As a reflective display technology, electrowetting displays (EWDs) have the advantages of a paper-like appearance, fast response speed, and full-color capability. However, the use of an overdriving voltage to improve the response speed of EWDs can cause fluctuations in display luminance, which manifest as glitches in the luminance change curve. In order to eliminate this luminance instability phenomenon, a new driving pulse is proposed, which consists of an overdriving phase, a switching phase, and a driving phase. Firstly, a simplified equivalent circuit model is proposed to apply a target voltage in the driving phase without break down of the hydrophobic insulating layer. Secondly, a COMSOL (Version 6.3) two-dimensional model is established to simulate the oil contraction process and conduct comparisons, so as to ensure the effectiveness of the overdriving pulse. Then, the overdriving phase is applied to improve oil response speed, and a linear function is used in the switching phase to alleviate glitch phenomena. Moreover, the influences of overdriving voltage, overdriving time, and linear switching time on the luminance curve are analyzed by charge trapping theory in order to obtain optimal performance. The experimental results show that the glitch phenomenon is eliminated effectively, and the luminance of the EWD is increased by 1.02% and 1.96% compared with the step switching pulse and PWM pulse, respectively, while the response time is shortened by 1.82% and 8.05% compared with the step switching pulse and PWM pulse, respectively. Full article

The high penetration of distributed generators (DGs) causes severe voltage fluctuations and voltage limit violations in distribution networks. Traditional control methods rely on precise line parameters, which are often unavailable or inaccurate, and therefore are limited in practical applications. This paper proposes a data-driven multi-mode adaptive control method with multi-region coordination to enhance the operational performance of distribution networks. First, the network is partitioned into multiple regions, each equipped with a local controller to formulate reactive power control strategies for DGs. Second, regions exchange voltage and current measurements to establish linear input–output relationships through dynamic linearization, thereby developing a multi-mode model for different control objectives. Finally, each region employs the gradient descent method to iteratively optimize its control strategy, enabling fast responses to changing operating conditions in distribution networks. Case studies on modified IEEE 33-node and 123-node test systems demonstrate that the proposed method reduces voltage deviation, load imbalance, and power loss by 31.25%, 19.17%, and 20.68%, respectively, and maintains strong scalability for application in large-scale distribution networks. Full article

This paper introduces a new quadruped spider robot platform specializing in environmental reconnaissance and mapping. The robot measures 180 mm × 180 mm × 95 mm and weighs 385 g, including the battery, providing a compact yet capable platform for reconnaissance missions. The robot consists of an ESP32 microcontroller and eight servos that are disposed in a biomimetic layout to achieve the biological gait of an arachnid. One of the major design revolutions is in the power distribution network (PDN) of the robot, in which two DC-DC buck converters (LM2596M) are used to isolate the power domains of the computation and the mechanical subsystems, thereby enhancing reliability and the lifespan of the robot. The theoretical analysis demonstrates that this dual-domain architecture reduces computational-domain voltage fluctuations by 85.9% compared to single-converter designs, with a measured voltage stability improving from 0.87 V to 0.12 V under servo load spikes. Its proprietary Bluetooth protocol allows for both the sending and receiving of controls and environmental data with fewer than 120 ms of latency at up to 12 m of distance. The robot’s mapping system employs a novel motion-compensated probabilistic algorithm that integrates ultrasonic sensor data with IMU-based motion estimation using recursive Bayesian updates. The occupancy grid uses 5 cm × 5 cm cells with confidence tracking, where each cell’s probability is updated using recursive Bayesian inference with confidence weighting to guide data fusion. Experimental verification in different environments indicates that the mapping accuracy (92.7% to ground-truth measurements) and stable pattern of the sensor reading remain, even when measuring the complex gait transition. Long-range field tests conducted over 100 m traversals in challenging outdoor environments with slopes of up to 15° and obstacle densities of 0.3 objects/m² demonstrate sustained performance, with 89.2% mapping accuracy. The energy saving of the robot was an 86.4% operating-time improvement over the single-regulator designs. This work contributes to the championing of low-cost, high-performance robotic platforms for reconnaissance tasks, especially in search and rescue, the exploration of hazardous environments, and educational robotics. Full article

With the rapid development of distributed energy and electric vehicles (EVs), the limited hosting capacity of distribution networks has severely impacted their economic dispatch and safe operation. To address these challenges, in this work, an optimal planning model considering the uncertainty of wind and solar power output is proposed, aiming to determine the location and capacity of electric vehicle charging stations (EVCSs). The model seeks to minimize the total costs, voltage fluctuations, and network losses, subject to constraints such as EV user satisfaction and grid company satisfaction. A multi-objective heat exchange optimization algorithm under Gaussian mutation (MOTEO-GM) is employed to validate the model on an extended IEEE-33 bus system and a real-world case in the University Town area of Chenggong District, Kunming City. Simulation results indicate that, in the test system, voltage fluctuations and system power losses are decreased by 43.05% and 37.47%, respectively, significantly enhancing the economic operation of the distribution grid. Full article

The wireless charging of electric vehicles (EVs) has drawn much attention as it can ease the charging process under different charging situations and environmental conditions. However, power transfer rate and efficiency are the critical parameters for the wide adaptation of wireless charging systems. Different investigations are presented in the literature that have aimed to improve power transfer efficiency and to maintain constant power at the load side. This paper introduces a Maximum Efficiency Point Tracking (MEPT) system designed specifically for a reconfigurable S-LCC compensated wireless charging system. The reconfigurable nature of the S-LCC system supports the constant current (CC) and constant voltage (CV) mode of operation by operating S-LCC and S-SP mode. The proposed system enhances power transfer efficiency under load fluctuations, coil misalignments, and a wide range of operating conditions. The developed S-LCC compensated system inherently maintains the power transfer rate constantly under a majority of load variations. Meanwhile, the inclusion of the MEPT method with the S-LCC system provides stable and maximum output under different coupling and load variations. The proposed MEPT approach uses a feedback mechanism to track and maintain the maximum efficiency point by iteratively adjusting the DC-DC converter duty ratio and by monitoring load power. The proposed approach was designed and tested in a 3.3 kW laboratory scale prototype module at an operating frequency of 85 kHz. The simulation and hardware results show that the developed system provides stable maximum power under a wider range of load and coupling variations. Full article

This paper proposes a flow battery-lithium-ion battery hybrid energy storage system (HESS) bi-level optimization planning method to address flexibility supply-demand balance challenges in regional power grids with high renewable penetration at 220 kV and above voltage levels. The method establishes a planning-operation coordination framework: Upper-level planning minimizes total lifecycle investment and operation-maintenance costs; Lower-level operation incorporates multiple constraints including flexibility gap penalties, voltage fluctuations, and line losses, overcoming single-timescale limitations. The approach enhances global search capability through the Improved Weighted Average Algorithm (IWAA) and optimizes power allocation accuracy using adaptive Variational Mode Decomposition (VMD). Validation using grid data from Southwest China demonstrates significant improvements across five comparative schemes. Results show substantial reductions in total investment costs, penalty costs, voltage fluctuations, and line losses compared to benchmark solutions, enhancing grid power supply stability and verifying the effectiveness of the model and algorithm. Full article

The integration of photovoltaic (PV) systems into power grids has surged due to the global shift towards renewable energy, but this rapid adoption presents challenges like voltage regulation and inverter degradation. High PV penetration can lead to overvoltage conditions and transient voltage fluctuations, which stress inverters and accelerate their degradation. To address these issues, advanced modeling techniques, particularly Bayesian modeling, are employed to predict and mitigate inverter failures by incorporating prior knowledge and real-world data. This approach enables probabilistic predictions of failure, improving maintenance scheduling and inverter design. By leveraging datasets from inverter operations with induction motors, this study aims to enhance the reliability of PV systems and optimize voltage regulation strategies for sustainable renewable energy growth. Full article

Push–pull switch-mode power supplies are widely employed due to their high efficiency and power density. However, traditional designs typically depend on multiple auxiliary circuits to achieve functions such as power-up control, voltage regulation, and system protection, resulting in structural complexity and difficulty in debugging. Additionally, dual-power high-voltage amplifier systems often suffer from voltage deviations caused by supply imbalances or load fluctuations, potentially leading to equipment failure and significant economic losses. To overcome these limitations, we propose a novel digital signal-controlled push–pull driver power supply topology in this paper. Specifically, this design utilizes digital pulse-width modulation (PWM) signals to control multi-stage metal-oxide-semiconductor field-effect transistors (MOSFETs), incorporating adjustable duty-cycle drives, multi-channel current sensing, and fault protection mechanisms. Experimental validation was performed on a ±220 V, 20 kHz, 180 W power supply prototype. The results demonstrate excellent performance, notably enhancing stability and reliability in dual-side synchronous power supply scenarios. Thus, this digital-control topology effectively addresses the drawbacks of conventional push–pull designs and offers potential applications in nondestructive testing and high-voltage driving systems. Full article