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The electric power equipment industry is rapidly advancing toward “informationization,” with the swift progression of intelligent sensing technology serving as a key driving force behind this transformation, thereby triggering significant changes in global electric power equipment. In this process, intelligent sensing has created an urgent demand for high-performance integrated power systems that feature compact size, lightweight design, long operational life, high reliability, high energy density, and low cost. However, the performance metrics of traditional power supplies have increasingly failed to meet the requirements of modern intelligent sensing, thereby significantly hindering the advancement of intelligent power equipment. Energy harvesting technology, characterized by its long operational lifespan, compact size, environmental sustainability, and self-sufficient operation, is capable of capturing renewable energy from ambient power sources and converting it into electrical energy to supply power to sensors. Due to these advantages, it has garnered significant attention in the field of power sensing. This paper presents a comprehensive review of the current state of development of energy harvesting technologies within the power environment. It outlines recent advancements in magnetic field energy harvesting, electric field energy harvesting, vibration energy harvesting, wind energy harvesting, and solar energy harvesting. Furthermore, it explores the integration of multiple physical mechanisms and hybrid energy sources aimed at enhancing self-powered applications in this domain. A comparative analysis of the advantages and limitations associated with each technology is also provided. Additionally, the paper discusses potential future directions for the development of energy harvesting technologies in the power environment. Full article

In response to the instability fluctuations and erosion characteristic changes in pantograph-catenary system (PCS) arcs induced by humidity variations in an open environment, a single-variable controlled experimental approach based on multi-source data fusion is proposed. This study innovatively establishes a humidity-controlled reciprocating current-carrying arc initiation test platform, integrating digital image processing with the dynamic analysis of multi-physics sensor signals (current, voltage, temperature). The study quantitatively evaluates the arc motion characteristics and the erosion effects on the frictional contact pair under different relative humidity levels (30%, 50%, 70%, and 90%) with a DC power supply (120 V/25 A). The experimental data and analysis reveal that increasing humidity results in higher contact resistance and accumulated arc energy, with arc stability first improving and then decreasing. At low humidity, arc behavior is more intense, and the erosion rate is faster. As humidity increases, the electrode wear transitions from adhesive wear to electrochemical wear, accompanied by copper transfer. The results suggest that the arc stability is optimal at moderate humidity (50% RH), with a peak current-carrying efficiency of 66% and a minimum loss rate of 14.5%. This threshold offers a vital theoretical framework for the optimization and risk assessments of PCS design. Full article

Utilizing pipeline Savonius hydro turbines driven by the pressure difference in water flow in the irrigation pipelines to generate electricity can achieve stable and reliable charging of the sensor battery, thereby addressing autonomous energy supply concerns. However, due to the low energy capture efficiency of the Savonius turbine with a small pressure difference, it is necessary to optimally design the internal flow channel structure to improve its efficiency and achieve a more miniaturized overall equipment, which has extremely high engineering application value. This study investigates the Savonius turbine, installed within the irrigation pipeline operating under specific conditions (diameter: 60 mm; flow rate: 15 m³/h; inlet pressure: 0.2 MPa; outlet pressure ≤ 0.05 MPa). A validated Computational Fluid Dynamics numerical model was developed to generate 200 datasets for a subsequent structural optimization process utilizing a Bayesian-optimized broad learning technique. The optimal structural parameters for maximum efficiency are a deflector angle of 10°, an aspect ratio of 0.775, and three blades, resulting in a maximum efficiency of 21.73% at a rotational speed of 1098 r/min. For the maximum power coefficient, the optimal combination is a deflector angle of 10°, a height-to-diameter ratio of 0.9, and three blades, yielding a peak power coefficient of 0.1859 at a rotational speed of 600 r/min. Full article

Wireless power transfer (WPT) technology offers a convenient, efficient, and environmentally robust power supply solution for rack-and-pinion modules. For WPT systems in such modules where the transmitter coil is a long rail, increasing the transmitter coil turns to enhance mutual inductance leads to issues like high cost, low efficiency, and installation difficulties. This paper introduces a relay resonator to strengthen system coupling and proposes a three-coil design scheme employing a single-turn long rail as the transmitter coil. The proposed all-detuned LCC-S-S topology exhibits constant output voltage (CV) and zero phase angle (ZPA) input characteristics while accounting for all cross-mutual inductances and coil resistances. The frequency detuning level of the relay resonator critically governs the system’s power transfer efficiency and directly determines the operational mode of the rectifier—either continuous conduction mode (CCM) or discontinuous conduction mode (DCM). To maximize system efficiency, the optimal detuning frequency of the relay coil is selected under CCM operation. Through optimized design of the three-coil parameters, the final prototype achieves an output power of 106.743 W and an efficiency of 90.865% when integrated with a 1200 mm single-turn long-rail transmitter coil. Full article

In loop-powered 4–20 mA transmitter systems, sensors like temperature, pressure, flow, and gas sensors are chosen based on specific application requirements. These systems are widely adopted in high-precision measurement scenarios, including industrial automation, process control, and environmental monitoring. The transmitter requires a high-performance analog front end (AFE) for precise amplification and signal conditioning. This paper presents a low-noise instrumentation amplifier (IA) for high-precision transmitter front ends, featuring a Successive Approximation Register (SAR)-assisted offset calibration architecture. The proposed structure integrates a chopper current-feedback instrumentation amplifier (CFIA) with an automatic offset calibration loop (AOCL), significantly suppressing internal offset errors and enabling high-accuracy signal acquisition under stringent power and environmental temperature constraints. The designed amplifier provides four selectable gain settings, covering a range from ×32 to ×256. Fabricated in a 0.18 μm CMOS process, the CFIA operates at a 1.8 V supply voltage, consumes a static current of 182 μA, and achieves an input-referred noise as low as 20.28 nV/√Hz at 1 kHz, with a common-mode rejection ratio (CMRR) up to 122 dB and a power-supply rejection ratio (PSRR) up to 117 dB. Experimental results demonstrate that the proposed amplifier exhibits excellent performance in terms of input-referred noise, offset voltage, PSRR, and CMRR, making it well-suited for front-end detection in field instruments that require direct interfacing with measured media. Full article

A wearable closed-loop transcutaneous electrical nerve stimulation (TENS) platform has been developed to address the limitations of conventional open-loop neuromodulation systems. Unlike existing systems such as CLoSES—which targets intracranial stimulation—and electromyography-triggered functional electrical stimulation (EMG-FES) platforms primarily used for motor rehabilitation, the proposed device uniquely integrates low-latency surface electromyography (sEMG)-driven control with six-channel current stimulation in a fully wearable, non-invasive format aimed at ambulatory pain modulation. The system combines real-time sEMG acquisition, adaptive signal processing, a programmable multi-channel stimulation engine, and a high-voltage, boost-regulated power supply within a compact, battery-powered architecture. Bench-top evaluations demonstrate rapid response to EMG events and stable biphasic output (±22 mA) across all channels with high electrical isolation. A human-subject protocol using the Cold Pressor Test (CPT), heart rate variability (HRV), and galvanic skin response (GSR) has been designed to evaluate analgesic efficacy. While institutional review board (IRB) approval is pending, the system establishes a robust foundation for future personalized, mobile neuromodulation therapies. Full article

Power electronics has significantly contributed to advances in developing single-stage integrated converter topologies, enabling DC/AC conversion with voltage step-up capability in a compact and efficient structure. This work proposes a novel Integrated Zeta–Ćuk Inverter (IZCI), derived from combining the Zeta and Ćuk DC/DC converter structures. In addition, the proposed topology achieves high efficiency and full utilization of the input voltage. A potential application for the IZCI topology involves DC microgrids, in which the proposed topology can supply AC local loads, achieving high power quality, such as a low total harmonic distortion (THD). The IZCI operates in discontinuous conduction mode (DCM), exhibiting three distinct operating stages for each switching period. The DCM operation guarantees a linear relationship between output and duty cycle, simplifying the control strategy and requiring fewer sensors, thereby reducing the cost and processing requirements. The feasibility and performance of the IZCI topology are evaluated and validated through experimental results in a standalone application. The results demonstrate high energy conversion efficiency and reliability, providing an AC output voltage with low harmonic distortion. Full article

The instability of the energy supply, growing demand and the need to reduce carbon emissions are priority challenges in developing countries such as Ecuador, where power outages affect productivity and generate economic losses. Therefore, solar energy is positioned as a sustainable alternative. The objective of this study is to evaluate a pilot photovoltaic (PV) system for residential housing in coastal areas in the Santa Elena province, Ecuador. The methodology included the following: (i) criteria for the selection of three representative residential housings; (ii) design of a distributed generation system using PVsyst software; and (iii) proposal of strategic guidelines for the design of PV systems. This proposed system proved to be environmentally friendly, achieving reductions of between 16.4 and 32 tonnes of CO₂ in the first 10 years. A return on investment (ROI) of 16 years was achieved for the low-demand (L) scenario, with 4 years for the medium-demand (M) scenario and 2 years for the high-demand (H) scenario. The sensitivity analysis showed that the Levelized Cost of Energy (LCOE) is more variable in the L scenario, requiring more efficient designs. It is proposed to diversify the Ecuadorian energy matrix through self-supply PV systems, which would reduce electricity costs by 6% of consumption (L scenario), 30% (M scenario), and 100% (H scenario). Although generation is concentrated during the day, the net metering scheme enables compensation for nighttime consumption without the need for batteries, thereby improving the system’s profitability. The high solar potential and high tariffs make the adoption of sustainable energy solutions a justifiable choice. Full article

As global energy systems shift to low-carbon models, microgrid systems play an increasingly vital role in decentralized energy management. This study proposes a collaborative scheduling strategy, incorporating both power and carbon contribution for multi-microgrid systems. Through the utilization of a cooperative Stackelberg game and a Nash bargaining model, a bi-level game framework is established between grid operators and microgrid alliances, enabling efficient resource sharing and equitable benefit distribution. To accurately assess each microgrid’s impacts, a VCG (Vickrey–Clarke–Groves)-based mechanism is introduced to quantify its marginal contribution to both power supply and carbon mitigation. The contribution factors are then embedded into the bargaining process, guiding incentive-compatible allocation. Furthermore, to improve computational efficiency and enable distributed problem-solving, an enhanced analytical target cascading (ATC) algorithm is applied. Experimental results reveal that this approach improves both economic and environmental performance, effectively reducing carbon emissions and dependence on the main grid. Full article

Parallel-type slew-rate enhancers (PSREs) improve the driving capability of operational transconductance amplifiers (OTAs) for large capacitive loads. While capacitive-boosting (CB) techniques enhance PSRE efficiency in fully-differential designs, their application to single-ended configurations—common in off-chip load driving—remains unexplored. This work identifies a critical limitation of standard CB in single-ended unity-gain buffers: severe slew-rate degradation due to large common-mode input swings. To overcome this, we propose a novel split CB (SCB) technique for single-ended PSREs that strategically divides the boosting capacitance. Simulated in a 0.18-µm CMOS process, the proposed method achieves a ×5.53 reduction in settling time compared to standard CB when driving a 1-nF load. With only 4 µA quiescent current under a 3.3-V supply, it attains a 1% settling time of 2.56 µs for 2.64-V steps, demonstrating robust performance across process-voltage-temperature variations. This technique enables low-power, high-speed interfaces for drivers of off-chip devices. Full article

The widespread deployment of electric vehicles (EVs) has introduced substantial challenges to electricity pricing, grid stability, and renewable energy integration. This paper proposes a real-time pricing optimization framework for large-scale EV charging networks incorporating renewable intermittency, demand elasticity, and infrastructure constraints within a high-dimensional optimization model. The core objective is to dynamically determine spatiotemporal electricity prices that simultaneously reduce system peak load, improve renewable energy utilization, and minimize user charging costs. A rigorous mathematical formulation is developed integrating over 40 system-level constraints, including power balance, transmission capacity, renewable curtailment, carbon targets, voltage regulation, demand-side flexibility, social participation, and cyber resilience. Real-time electricity prices are treated as dynamic decision variables influenced by charging station utilization, elasticity response curves, and the marginal cost of renewable and grid-supplied electricity. The problem is solved over 96 time intervals using a hybrid solution approach, with benchmark comparisons against mixed-integer programming (MILP) and deep reinforcement learning (DRL)-based baselines. A comprehensive case study is conducted on a 500-station EV charging network serving 10,000 vehicles integrated with a modified IEEE 118-bus grid model and 800 MW of variable renewable energy. Historical charging data with ±12% stochastic demand variation and real-world solar and wind profiles are used to simulate realistic operational conditions. Results demonstrate that the proposed framework achieves a 23.4% average peak load reduction per station, a 17.9% improvement in renewable energy utilization, and user cost savings of up to 30% compared to baseline flat-rate pricing. Utilization imbalances across the network are reduced, with congestion mitigation observed at over 90% of high-traffic stations. The real-time pricing model successfully aligns low-price windows with high-renewable periods and off-peak hours, achieving time-synchronized load shifting and system-wide flexibility. Visual analytics including high-resolution 3D surface plots and disaggregated bar charts reveal structured patterns in demand–price interactions, confirming the model’s ability to generate smooth, non-disruptive pricing trajectories. The results underscore the viability of advanced optimization-based pricing strategies for scalable, clean, and responsive EV charging infrastructure management in renewable-rich grid environments. Full article

The traditional arc suppression device suffers from high costs and low utilization. These problems can be effectively avoided by using a hybrid multi-function arc suppression device (HMF-ASD). However, an HMF-ASD will consume active power during arc suppression. Based on this, a P-Q arc suppression method based on DC-link voltage stability is proposed. The energy flow during a single line-to-ground (SLG) fault is analyzed to optimize operation of the HMF-ASD. The topology and principle of the HMF-ASD are introduced. Secondly, the influence mechanism of the traditional arc suppression method on the output active power and energy flow direction of the HMF-ASD is analyzed. The internal reason for the change in the DC-link voltage is clarified. Additionally, non-fault phases of the HMF-ASD are regulated to produce no active output, delivering only the reactive current required for arc suppression. This method effectively mitigates SLG faults while maintaining DC-link voltage stability. Non-fault phases exclusively supply reactive power, with the active power needed for arc suppression drawn directly from the grid. The validity of the proposed method is confirmed through both simulation and experiment. Full article

As a novel energy storage technology, seawater batteries exhibit significant application potential across various domains, including marine exploration, underwater communication, and island power supply. However, the deep-sea low-temperature environment adversely affects the performance of seawater battery systems. This paper proposes a seawater metal–air battery system equipped with a preheater (SMAB-P). This innovative system establishes stable natural circulation and utilizes the high-temperature seawater within the system to preheat the incoming low-temperature seawater, thereby effectively enhancing battery performance. It was found that, compared with the SMAB system without a preheater, when achieving a heat recovery rate of 100% the average temperature of seawater in the electrode plate area of the SMAB-P system can be increased by 54%. Consequently, the electrical conductivity of seawater within the system can be increased by approximately 20%, leading to a significant reduction in ohmic losses and an enhancement in the load voltage of the battery. Furthermore, increasing either the height or width of the electrode plate can enhance self-driven force and circulation flow rate, as well as both average and maximum temperatures of seawater in the electrode plate area to some extent. Reducing the annular space of the preheater can significantly increase the seawater temperature within the system, but excessive reduction may hinder the effective replacement of fresh seawater in the system. It is also noted that seawater velocity in the electrode plate channels remains relatively low and evenly distributed while exhibiting very small temperature variation. Full article

With the rapid development of energy transformation, the proportion of new energy is increasing, and the efficient trading mechanism of multi-microgrids can realize energy sharing to improve the consumption rate of new energy. A distributed multi-microgrid cooperative energy sharing strategy is proposed based on Nash bargaining. Firstly, by comprehensively considering the adjustable heat-to-electrical ratio, ladder-type positive and negative carbon trading, peak–valley electricity price and demand response, a multi-microgrid system with wind–solar-storage-load and combined heat and power is constructed. Then, a multi-microgrid cooperative game optimization framework is established based on Nash bargaining, and the complex nonlinear problem is decomposed into two stages to be solved. In the first stage, the cost minimization problem of multi-microgrids is solved based on the alternating direction multiplier method to maximize consumption rate and protect privacy. In the second stage, through the established contribution quantification model, Nash bargaining theory is used to fairly distribute the benefits of cooperation. The simulation results of three typical microgrids verify that the proposed strategy has good convergence properties and computational efficiency. Compared with the independent operation, the proposed strategy reduces the cost by 41% and the carbon emission by 18,490 kg, thus realizing low-carbon operation and optimal economic dispatch. Meanwhile, the power supply pressure of the main grid is reduced through energy interaction, thus improving the utilization rate of renewable energy. Full article

Endotoxins, lipopolysaccharides released from the outer membrane of Gram-negative bacteria, pose a significant risk in healthcare environments, particularly in Central Sterile Supply Departments (CSSDs), where the delivery of sterile pyrogen-free medical devices is critical for patient safety. Traditional methods for controlling endotoxins in water systems, such as ultraviolet (UV) disinfection, have proven ineffective at reducing endotoxin concentrations to comply with regulatory standards (<0.25 EU/mL). This limitation presents a significant challenge, especially in the context of reverse osmosis (RO) permeate used in CSSDs, where water typically has very low conductivity. Despite the established importance of endotoxin removal, a gap in the literature exists regarding effective chemical-free methods that can meet the stringent endotoxin limits in such low-conductivity environments. This study addresses this gap by evaluating the effectiveness of the eBooster™ electrochemical technology—featuring proprietary electrode materials and a reactor design optimized for potable water—for endotoxin removal from water, specifically under the low-conductivity conditions typical of RO permeate. Laboratory experiments using the B250 reactor achieved >90% endotoxin reduction (from 1.2 EU/mL to <0.1 EU/mL) at flow rates ≤5 L/min and current densities of 0.45–2.7 mA/cm². Additional real-world testing at three hospitals showed that the eBooster™ unit, when installed in the RO tank recirculation loop, consistently reduced endotoxin levels from 0.76 EU/mL (with UV) to <0.05 EU/mL over 24 months of operation, while heterotrophic plate counts dropped from 190 to <1 CFU/100 mL. Statistical analysis confirmed the reproducibility and flow-rate dependence of the removal efficiency. Limitations observed included reduced efficacy at higher flow rates, the need for sufficient residence time, and a temporary performance decline after two years due to a power fault, which was promptly corrected. Compared to earlier approaches, eBooster™ demonstrated superior performance in low-conductivity environments without added chemicals or significant maintenance. These findings highlight the strength and novelty of eBooster™ as a reliable, chemical-free, and maintenance-friendly alternative to traditional UV disinfection systems, offering a promising solution for critical water treatment applications in healthcare environments. Full article