Search Results (806)

This study proposes a hierarchical two-layer control framework aimed at advancing the sustainability of renewable-integrated microgrids. The framework combines droop-based primary control, PI-based voltage and current regulation, and a supervisory Model Predictive Control (MPC) layer to enhance dynamic power sharing and system stability in renewable-integrated microgrids. The proposed method addresses the limitations of conventional control techniques by coordinating real and reactive power flow through an adaptive droop formulation and refining voltage/current regulation with inner-loop PI controllers. A discrete-time MPC algorithm is introduced to optimize power setpoints under future disturbance forecasts, accounting for state-of-charge limits, DC-link voltage constraints, and renewable generation variability. The effectiveness of the proposed strategy is demonstrated on a small hybrid microgrid system that serve a small community of buildings with a solar PV, wind generation, and a battery storage system under variable load and environmental profiles. Initial uncontrolled scenarios reveal significant imbalances in resource coordination and voltage deviation. Upon applying the proposed control, active and reactive power are equitably shared among DG units, while voltage and frequency remain tightly regulated, even during abrupt load transitions. The proposed control approach enhances renewable energy integration, leading to reduced reliance on fossil-fuel-based resources. This contributes to environmental sustainability by lowering greenhouse gas emissions and supporting the transition to a cleaner energy future. Simulation results confirm the superiority of the proposed control strategy in maintaining grid stability, minimizing overcharging/overdischarging of batteries, and ensuring waveform quality. Full article

This work presents a low-power photoplethysmography (PPG) readout integrated circuit (IC) that achieves a wide dynamic range (DR) through the direct integration of a voltage-controlled oscillator (VCO)-based quantizer into the photodiode driver. Conventional PPG readout circuits rely on either transimpedance amplifier (TIA) or light-to-digital converter (LDC) topologies, both of which require auxiliary DC suppression loops. These additional loops not only raise power consumption but also limit the achievable DR. The proposed design eliminates the need for such circuits by embedding a linear regulator with a mirroring scale calibrator and a time-domain quantizer. The quantizer provides first-order noise shaping, enabling accurate extraction of the AC PPG signal while the regulator directly handles the large DC current component. Post-layout simulations show that the proposed readout achieves a signal-to-noise-and-distortion ratio (SNDR) of 40.0 dB at 10 µA DC current while consuming only 0.80 µW from a 2.5 V supply. The circuit demonstrates excellent stability across process–voltage–temperature (PVT) corners and maintains high accuracy over a wide DC current range. These features, combined with a compact silicon area of 0.725 mm² using TSMC 250 nm bipolar–CMOS–DMOS (BCD) process, make the proposed IC an attractive candidate for next-generation wearable and biomedical sensing platforms. Full article

In regions with concentrated load centers in China, the AC transmission network is dense, leading to challenges such as difficulties in power flow control and excessive short-circuit currents. The scale effect of AC grids is approaching saturation, making it imperative to develop new AC/DC hybrid grid structures. To enhance the controllability, security, and stability of AC/DC hybrid power systems, a single-AC multi-DC hybrid grid structure is proposed in this paper. The operational characteristics of this grid are analyzed in terms of power flow control capability, N-1 overload, short-circuit current, frequency stability, voltage stability, and synchronous stability, and a method for constructing the single-AC multi-DC hybrid grid is presented. Finally, simulation analysis is conducted on a typical single-AC multi-DC case, and the results indicate that this hybrid grid structure can simultaneously satisfy the controllability, security, and stability requirements of AC/DC power systems, making it a highly promising grid configuration. Full article

In this paper, a nonlinear power transfer matrix model is presented for power control of Permanent Magnet Synchronous Generator (PMSG) wind turbines, incorporating the DC link dynamics to account for transient stability, thereby clarifying the technical aspect and purpose. The rising penetration of wind turbines (WTs) into the power grid necessitates that they remain connected during and after faults to ensure system reliability. During voltage dips, the stator and grid-side converter (GSC) of a permanent magnet synchronous generator (PMSG) system are directly impacted by the sudden voltage changes. These disturbances can induce large transient voltages and currents in the stator, which in turn may lead to uncontrolled current flow in the rotor circuit and stress the converter components. Moreover, Low Voltage Ride-Through (LVRT) is a critical requirement for grid connection to Wind Energy Conversion Systems (WECS). It ensures that WTs remain connected and operational during short periods of grid voltage dips (faults), instead of disconnecting immediately. This capability is essential for maintaining grid stability. However, in this paper, the authors propose an LVRT scheme for a grid-connected PMSG-based WECS. A sequence of attempts was performed to validate the effectiveness of the proposed control scheme under fault conditions and to improve its overall performance. Full article

Bus voltage regulation and accurate power sharing constitute two pivotal control objectives in DC microgrids. The conventional droop control method inherently suffers from steady-state voltage deviation. Centralized control introduces vulnerability to single-point failures, with significantly degraded stability under abnormal operating conditions. Distributed control strategies mitigate this vulnerability but require careful balancing between control effectiveness and communication costs. Therefore, this paper proposes a hybrid hierarchical control architecture integrating multiple control strategies to achieve near-zero steady-state deviation voltage regulation and precise power sharing in DC microgrids. Capitalizing on the complementary advantages of different control methods, an operation-condition-adaptive hierarchical control (OCAHC) strategy is proposed. The proposed method improves reliability over centralized control under communication failures, and achieves better performance than distributed control under normal conditions. With a fault-detection logic module, the OCAHC framework enables automatic switching to maintain high control performance across different operating scenarios. For the inherent trade-off between consensus algorithm performance and communication costs, a communication topology optimization model is established with communication cost as the objective, subject to constraints including communication intensity, algorithm convergence under both normal and N-1 conditions, and control performance requirements. An accelerated optimization approach employing node-degree computation and equivalent topology reduction is proposed to enhance computational efficiency. Finally, case studies on a DC microgrid with five DGs verify the effectiveness of the proposed model and methods. 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

Microgrid systems play a vital role in managing distributed energy resources like solar, wind, batteries, and supercapacitors. However, maintaining stable AC/DC bus voltages and minimizing grid reliance under dynamic conditions is challenging. Traditional control methods such as Sliding Mode Controllers (SMCs) suffer from issues like chattering and slow convergence, reducing practical effectiveness. This paper proposes a hybrid AC/DC microgrid that operates in both grid-connected and islanded modes while ensuring voltage stability and efficient energy use. A Conditional-Based Super-Twisting Sliding Mode Controller (CBSTSMC) is employed to address the limitations of conventional SMCs. The CBSTSMC enhances system performance by reducing chattering, improving convergence speed, and offering better tracking and disturbance rejection. To further refine controller performance, an Improved Grey Wolf Optimization (IGWO) algorithm is used for gain tuning, resulting in enhanced system robustness and precision. An Energy Management System (EMS) is integrated to intelligently regulate power flow based on renewable generation and storage availability. The proposed system is tested in real time using a Texas Instruments Delfino C2000 microcontroller through a Controller-in-the-Loop (CIL) setup. The simulation and hardware results confirm the system’s ability to maintain stability and reliability under diverse operating scenarios, proving its suitability for future smart grid applications. Full article

Partial shading in photovoltaic (PV) systems causes multiple local maximum power points (LMPPs), complicating tracking and reducing energy efficiency. Conventional maximum power point tracking (MPPT) methods, such as Perturb and Observe (P&O), often fail because of oscillations and entrapment at local maxima. To address these shortcomings, this study proposes a hybrid MPPT strategy combining artificial neural networks (ANNs) and the P&O algorithm to enhance tracking accuracy under partial shading while maintaining implementation simplicity. The research employs a detailed PV cell model in MATLAB/Simulink (2019b) that incorporates dynamic shading to simulate non-uniform irradiance. Within this framework, an ANN trained with the Levenberg–Marquardt algorithm predicts global maximum power points (GMPPs) from voltage and irradiance data, guiding and accelerating subsequent P&O operation. In the hybrid system, the ANN predicts the maximum power points (MPPs) to provide initial estimates, after which the P&O fine-tunes the duty cycle optimization in a DC-DC converter. The proposed hybrid ANN–P&O MPPT method achieved relative improvements of 15.6–49% in tracking efficiency, 16–20% in stability, and 14–54% in convergence speed compared with standalone P&O, depending on the irradiance scenario. This research highlights the potential of ANN-enhanced MPPT systems to maximize energy harvest in PV systems facing shading variability. Full article

Microgrids have emerged as a crucial solution for addressing environmental concerns, such as reducing greenhouse gas emissions and enhancing energy sustainability. By incorporating renewable energy sources like solar and wind, microgrids improve energy efficiency and offer a cleaner alternative to conventional power grids. Among various microgrid architectures, DC microgrids are gaining significant attention due to their higher efficiency, reduced reactive power losses, and direct compatibility with renewable energy sources and energy storage systems. However, DC microgrids face stability challenges, particularly due to the presence of constant power loads (CPLs), which exhibit negative incremental impedance characteristics. These loads can destabilize the system, leading to oscillations and performance degradation. This paper explores various control strategies designed to enhance the stability and dynamic response of DC microgrids, with a particular focus on interleaved boost converters (IBCs) interfaced with CPLs. Traditional control methods, including proportional–integral (PI) and sliding mode control (SMC), have shown limitations in handling dynamic variations and disturbances. To overcome these challenges, this paper proposes a novel RST-based control strategy for IBCs, offering improved stability, adaptability, and disturbance rejection. The efficacy of the RST controller is validated through extensive simulations tests, demonstrating competitive performance in maintaining DC bus voltage regulation and current distribution. Key performance indicators demonstrate competitive performance, including settling times below 40 ms for voltage transients, overshoot limited to ±2%, minimal voltage deviation from the reference, and precise current sharing between interleaved phases. The findings contribute to advancing the stability and efficiency of DC microgrids, facilitating their broader adoption in modern energy systems. Full article

Constant on-time (COT) buck converters offer fast transient responses and a simple architecture but face challenges like switching frequency variation, instability with low-equivalent series resistance (ESR) capacitors, and DC output voltage offset. This paper reviews advanced COT control techniques developed to overcome these limitations. We examine methods for frequency stabilization (e.g., adaptive on-time, phase-locked loop), stability with low-ESR capacitors (e.g., passive and active ripple injection, virtual inductor current), and improved DC regulation (e.g., offset cancellation). This review also covers techniques for optimizing transient response and multiphase architectures for high-current applications. Full article

As a critical component in high-voltage cable accessories, ethylene-propylene-diene monomer (EPDM) reinforced insulation faces severe issues of surface discharge and bulk breakdown at the insulation interface. To enhance the electrical resistance of EPDM bulk and insulation interfaces, the 4-allyloxy-2-hydroxybenzophenone was employed as a voltage stabilizer to modify EPDM. A systematic study was conducted on the influence of the voltage stabilizer on the DC breakdown strength of EPDM, the anti-migration properties of the voltage stabilizer, and its effect on the surface breakdown voltage of EPDM. Additionally, pressure and surface breakdown test setups were designed. The results indicate that the DC breakdown strength of EPDM decreases with increasing external pressure, and this decline is more pronounced in EPDM modified with the voltage stabilizer. Surface breakdown experiments demonstrate that the voltage stabilizer has a positive effect on improving the surface breakdown voltage of EPDM, with a more significant enhancement observed at the EPDM/XLPE bilayer dielectric interface. Surface potential tests reveal that the grafted voltage stabilizer introduces numerous shallow traps, inhibiting surface charge accumulation and thereby increasing the surface breakdown voltage. Full article

This study targets insulation challenges in high-frequency power transformers (HFPTs), which are an integral part of the high-voltage, high-capacity isolated DC/DC converter under development for offshore renewable energy systems. We propose a nano-silicon carbide (SiC)-doped polyimide (PI) winding insulation strategy to enhance discharge resistance and thermal stability under high-frequency electric stress. Experimental results show that 10 wt% SiC doping significantly improves insulation performance, extending failure time from 17 to 50 min and reducing maximum discharge amplitude by 76%, owing to enhanced charge trapping and interfacial polarization suppression. Surface and volume resistivity measurements further confirmed the improvement; at 120 °C, the 10 wt% SiC composite maintained high surface resistivity 3.30 × 10¹⁴ Ω and volume resistivity 1.41 × 10¹⁵ Ω·cm, significantly outperforming pure PI. In contrast, 20 wt% SiC, though still resistive, showed reduced stability due to agglomeration and interfacial defects, with a surface resistivity of 2.07 × 10¹⁴ Ω and degraded dielectric performance. Dielectric analysis revealed that 10 wt% SiC suppressed dielectric constant and loss across the frequency range, while 20 wt% SiC exhibited increased values at high frequency. These results highlight 10 wt% SiC as an optimal formulation for HFPT winding insulation. Full article

As electric scooters (e-scooters) continue to populate city streets and gain popularity as a key mode of micro-mobility, issues such as their energy consumption and demand from the power grid, as well as optimizing their electrical systems, become increasingly important. Improving performance requires a deep understanding of their electrical behavior and the design of smart control strategies. This paper presents a detailed analysis of the entire electrical system of commercial electric scooters, with a particular focus on the performance of key components such as the permanent magnet brushless direct current motor and the lithium-ion battery system. The study involves modeling and simulation of motor control, battery management, and DC-link voltage stabilization using MATLAB/Simulink. The simulations are complemented by laboratory measurements of the motor performance in an SXT Scooters MAX unit under various operating conditions. Additionally, a complete battery charging cycle is analyzed to evaluate charging characteristics and usable energy storage capacity. This paper presents a first step for researchers interested in studying the electrical systems of e-scooters. Additionally, it can serve as educational material for electrical engineers in the field of e-scooters. Full article

Bipolar DC microgrids gain significant attention for their flexible structure, high power supply reliability, and strong compatibility with distributed power sources. However, inter-pole voltage imbalance undermines system operational stability. An isolated bipolar bidirectional three-port converter with voltage self-balancing capability is proposed in this paper, which can serve as the interface between the energy storage system and bipolar bus while achieving automatic voltage balance between poles. Unlike traditional bidirectional grid-connected voltage balancers (VBs), the proposed converter requires no additional voltage monitoring or complex control systems. The operating modes, soft-switching boundary conditions, and inter-pole voltage self-balancing mechanism are elaborated. A 1 kW experimental prototype has been built to validate the theoretical analysis of the proposed converter. Full article

The rapid evolution of modern power systems, driven by the large-scale integration of renewable energy sources and the emergence of smart grids, presents new challenges in maintaining grid stability, power quality, and control reliability. As critical interfacing elements, three-phase pulse width modulation (PWM) converters must now ensure resilient and efficient operation under increasingly adverse and dynamic grid conditions. This paper proposes an adaptive neural network-based virtual flux (VF) estimator for sensorless predictive direct power control (PDPC) of PWM converters under nonideal grid voltage conditions. The proposed estimator is realized using an adaptive linear neuron (ADALINE) configured as a quadrature signal generator, offering robustness against grid voltage disturbances such as voltage unbalance, DC offset and harmonic distortion. In parallel, a PDPC scheme based on the extended pq theory is developed to reject active-power oscillations and to maintain near-sinusoidal grid currents under unbalanced conditions. The resulting VF-based PDPC (VF-PDPC) strategy is validated via real-time simulations on the OPAL-RT platform. Comparative analysis confirms that the ADALINE-based estimator surpasses conventional VF estimation techniques. Moreover, the VF-PDPC achieves superior performance over conventional PDPC and extended pq theory-based PDPC strategies, both of which rely on physical voltage sensors, confirming its robustness and effectiveness under non-ideal grid conditions. Full article