Activating anion redox reactions in P2-type layered oxides is an effective strategy to achieve higher specific capacities for sodium-ion batteries. A common approach to realizing anion redox reactions involves substituting transition metals with elements such as lithium or magnesium. However, this strategy faces challenges due to the inherent irreversibility of the anion redox reaction and kinetic hysteresis. In addition, high-voltage conditions can lead to irreversible oxygen loss and excessive electrolyte decomposition, resulting in rapid capacity decay and a sustained decrease in discharge potential. In this study, W-doped P2-type layered oxide Na_0.6Li_0.27Mn_0.73-x W _x O₂ (NLMWO) was synthesized using a high-temperature solid-state method. The effects of varying W doping levels on the electrochemical performance of the materials were investigated through multiple characterization techniques. The results demonstrate that W doping effectively reduces Na⁺/vacancy ordering, suppresses the P2-OP4-O2 phase transition, and enhances Na⁺ diffusion rates. The capacity retention of Na_0.6Li_0.27Mn_0.72W_0.01O₂ (NLMWO-1) with 1.0% W doping increased by 63.6% after 100 cycles at a rate of 0.5 C in the voltage range of 2.0—4.6 V, compared to Na_0.6Li_0.27Mn_0.73O₂ (NLMO). At 5.0 C, NLMWO-1 delivers an average discharge specific capacity of 92.6 mAh/g, 1.5 times that of NLMO, demonstrating excellent rate capability. These findings suggest that inactive metal doping can effectively mitigate the irreversible anion redox of transition metal layer oxides, providing valuable insights for the design of high-capacity and high-stability cathode materials for sodium-ion batteries.

The emergence of new high specific energy fluorinated carbon (CF _x ) materials has continuously improved the specific energy/specific power characteristics of Li/CF _x primary batteries, especially the power type Li/CF _x batteries have begun to be used in small commercial power systems and may become the power type lithium primary batteries with the highest specific energy. However, there is a lack of comparative study on the self-discharge of Li/CF _x lithium primary batteries prepared from different types of CF _x materials. This article selects four typical novel CF _x materials that are divided into energy type and power type materials according to their applications, among which two energy type CF _x materials have F/C ratios close to 1 and more stable and saturated C－F chemical bonds, while two power type CF _x materials have lower F/C ratios and more ionic C－F bonds, resulting in better conductivity and rate performance. After being stored at a high temperature of 55 ℃, the self-discharge rate of the industrially prepared BR18650 Li/CF _x battery, regardless of whether it has been discharged or not, is almost zero, making it suitable for long-life shelf storage. However, for power batteries stored at 55 ℃, the higher the depth of discharge (DOD), the greater the internal resistance and self-discharge rate of the battery. The pre-discharge treatment that is commonly used in lithium primary battery industry can lead to an increase in the self-discharge rate of power type batteries, which means that power type batteries should be put into use immediately after pre-discharge activation. Intermittent use of power type batteries can lead to an increase in their self-discharge rate and internal resistance, which may be due to the damage of the loose LiF protective film causing the fresh CF _x interface to be exposed to the electrolyte and continuous reaction, but the energy type CF _x material has less impact due to its more stable saturated C－F covalent bonds.

SnSe thermoelectric materials are promising due to their low thermal conductivity, low cost, and environmental friendliness, making them a focus in thermoelectric research. This study explores the effects of heat treatment temperature on the thermoelectric properties of polycrystalline SnSe blocks prepared via hydrothermal synthesis and cold sintering. X-ray diffraction (XRD) analysis confirmed that the primary diffraction peaks of all samples corresponded with SnSe, while scanning electron microscopy (SEM) revealed a transformation from bulk to lamellar structures with reduced internal voids as annealing temperature increased. Positron annihilation spectroscopy indicated the presence of vacancy-type defects, such as V_Se, V_Sn, V_SnSe, and large vacancy clusters, which serve as phonon scattering centers, thereby reducing lattice thermal conductivity. As the annealing temperature rose, a decrease in voids and partial restoration of these defects lowered the potential barrier at grain boundaries, enhancing electrical conductivity. The electrical conductivity, power factor, and dimensionless thermoelectric figure of merit (ZT) increased consistently with higher annealing temperatures. At a test temperature of 773 K, the sample annealed at 500 ℃ exhibited an electrical conductivity (σ) of 4.1 × 10³ S/m and a power factor of 3.71 μW/(cm·K²). Although thermal conductivity slightly increased with higher annealing temperatures due to reduced phonon scattering centers, the overall ZT value reached 0.7 for the 500 ℃ annealed sample, a 35.7% improvement compared to the unannealed sample. These findings demonstrate that the combination of cold sintering and heat treatment is highly effective for enhancing the thermoelectric performance of SnSe, providing a theoretical basis for the development of high-performance thermoelectric materials.

To address the issues of low thermal conductivity and leakage in paraffin (PW) phase change materials, porous aluminum metal foams were fabricated as a supporting framework using the ice template method. PW was then infiltrated into these metal foams via vacuum impregnation, resulting in chemically stable phase change composites (PCCs). The morphology, leakage resistance, thermal cycling stability, thermal response performance, and thermal conductivity of the PCCs were evaluated. Results showed that increasing the aluminum framework ratio significantly reduced leakage, enhancing the leakage resistance of the PCCs. The thermal physical properties were further analyzed, revealing that the inclusion of metal foams did not alter the phase transition temperature of PW, with stable melting and solidification peaks at 61 ℃ and 51 ℃, respectively. However, as the aluminum framework ratio increased, the enthalpy of phase transformation of the PCCs decreased. After 50 phase change cycles, the melting and solidification enthalpy values of the PCCs remained largely stable, with PW@30Al samples retaining enthalpy values of 116 J/g and 118 J/g, respectively, demonstrating excellent thermal cycling stability and phase transition reversibility. Additionally, the thermal conductivity of the PCCs improved progressively with a higher aluminum framework ratio, resulting in a faster thermal response. The thermal conductivity of PW@30Al samples increased from 0.2 W/(m·K) for pure PW to 3.1 W/(m·K), representing approximately a 15-fold increase. These findings suggest that the prepared PCCs have significant potential for applications in phase change heat storage and thermal management.

The pressure difference between adjacent channels in a proton exchange membrane fuel cell (PEMFC) induces cross-flow within the gas diffusion layer (GDL), which enhances mass transport, improves liquid water removal, and supports reactant supply. To investigate the effect of cross-flow on reactant distribution and transmembrane water transport, this study developed a three-dimensional two-phase model that incorporates cross-flow dynamics with water transport processes. The model was validated through single-cell testing using a purpose-built experimental setup. The analysis focused on cross-flow pathways and their impact on water transmembrane transport. Results indicate that cross-flow drives gas entry into the GDL from the high-pressure channel corners, directs it toward adjacent low-pressure channels, and exits at the subsequent channel corners. Cross-flow velocity increases with the pressure difference between neighboring channels, with the cathode exhibiting higher cross-flow velocities due to greater pressure drops compared to the anode. The highest cathode cross-flow velocity (0.13 m/s) was recorded near the channel outlet, whereas the anode's peak velocity (0.05 m/s) occurred near the channel inlet. Cross-flow enhances the electro-osmotic drag water flux at channel corners and aids in removing water accumulated beneath the ribs, thereby affecting the concentration-driven transmembrane water flux. Airflow at the inlet reduces membrane water content, while elevated concentration gradients at the outlet increase membrane water content in that region.

With the increasing global demand for energy, the development and utilization of new energy sources have become pressing challenges. To address energy concerns, lithium-ion batteries have seen rapid advancements over the past few decades and are now widely used in electronic devices and vehicle power supplies. The high-nickel ternary cathode material LiNi_0.8Co_0.1Mn_0.1O₂ (NCM811) is considered one of the most promising cathode materials for next-generation lithium-ion batteries due to its high energy density and cost-effectiveness. Increasing the operating voltage can significantly enhance the energy density of this electrode material. However, under high voltage, the structural stability of NCM811 is compromised due to issues such as cation mixing, crack formation and propagation, lattice oxygen release, side reactions, and lattice distortion caused by electrolyte contact. These factors lead to irreversible phase transitions, severe capacity degradation, and a sharp decline in cycling performance, hindering the large-scale application of high-voltage NCM811. This paper reviews the latest research on modification strategies for NCM811 under high voltage. It begins with an overview of the failure mechanisms of NCM811 at high voltage, followed by a discussion on how element doping, surface coating, and composite modification strategies impact its electrochemical performance and the mechanisms by which these modifications improve stability. Finally, the paper explores future directions for NCM811 improvement strategies, proposing feasible, application-oriented solutions for various modification approaches.

Power lithium-ion batteries possess a specific service life, typically around 5-8 years, after which they must be decommissioned. Spent batteries contain a wealth of valuable energy metals and strategic elements. Notably, the graphite from the negative electrode is classified as a strategic mineral element, constituting 12% to 21% of the battery's composition. Without proper handling, it will lead to resource waste and environmental governance pressure. This article summarizes an overview of the recent research progress on the reuse of spent graphite negative electrode powder from three aspects: failure mechanism, impurity removal methods, and repair regeneration. Firstly, the article conducts a systematic anylysis of the failure mechanism of spent graphite, examining four aspects: solid electrolyte interphase thickening failure, surface dendrites, active particle rupture, and collector corrosion; Secondly, the efficient removal methods of impurity ions from spent graphite are emphatically introduced, including acid-base treatment, deep eutectic solvent leaching, electrolysis, etc; Lastly, the article emphasizes strategies for the repair and reuse of spent graphite, including carbon material coating repair, metal oxide coating repair, and the construction of artificial surface interface. The article also discusses the development direction and application prospects of spent graphite, suggesting that future regeneration efforts will focus on high value, low energy consumption, and sustainable practices. It is anticipated that this article will serve as a theoretical foundation and guide for the resourceful utilization of graphite negative electrodes from retired power batteries.

Silicon-based materials, including elemental silicon and its oxides, are promising candidates for next-generation anode materials in lithium-ion batteries due to their high specific capacity and low operating voltage. However, significant volume changes during the lithiation and delithiation processes lead to the pulverization and fracturing of silicon, compromising battery cycling performance. Current modification strategies for silicon anodes include nanosizing, carbon coating, alloying, and polymer/Si(SiO _x ) composite approaches. Nanosizing and alloying aim to mitigate internal volume expansion within silicon particles, while carbon coating and polymer/Si(SiO _x ) composites externally suppress volume changes and enhance conductivity. This paper discusses the mechanisms and primary challenges associated with silicon anode lithiation and delithiation. It emphasizes the role of polymer binders in stabilizing silicon anodes, reviewing recent progress in polymer binder composites, including three-dimensional structural binders that limit silicon expansion, self-healing binders that accommodate elastic volume changes, and conductive binders that enhance overall conductivity. The paper concludes with future research directions and trends in the development of polymer binders for silicon anodes.

Solid-state electrolytes are essential components of solid-state batteries, garnering significant attention for their potential to pair effectively with high-capacity cathode and anode materials, enhance energy density, and address the safety issues inherent in liquid lithium-ion batteries. Among these, NASICON-type oxide solid electrolytes, such as Li_1+x Al _x Ti_2-x (PO₄)₃ (LATP, 0 ≤ x ≤ 0.5) and Li_1+x Al _x Ge_2-x (PO₄)₃ (LAGP, 0 ≤ x ≤ 0.5), stand out due to their excellent air stability, high ionic conductivity, low-cost raw materials, and favorable synthesis conditions, making them strong candidates for commercial applications. However, traditional methods for optimizing synthesis and modification are often costly, time-consuming, and inefficient. Current research focuses on elucidating ion transport mechanisms, exploring novel synthesis techniques, and enhancing the efficiency of material development for LATP and LAGP. This paper reviews the advancements in LATP and LAGP research, including their crystal structures, ion conduction mechanisms, synthesis methods, performance enhancement strategies, and the integration of machine learning in material synthesis. By evaluating synthesis costs and product performance, the study identifies optimal synthesis pathways with potential for industrial application. Specific examples illustrate the promising role of machine learning in advancing the field of solid-state electrolytes. The paper concludes with an analysis of existing research gaps and outlines future directions for basic research, engineering applications, and commercial promotion of LATP and LAGP solid-state electrolytes.

Anion exchange membrane water electrolysis (AEMWE), which integrates the advantages of alkaline water electrolysis and proton exchange membrane water electrolysis, features high electrolysis efficiency, rapid response, and low cost. It is currently regarded as one of the most promising technologies for renewable and sustainable hydrogen production. The anion exchange membrane (AEM) is a critical component responsible for OH^– conduction and gas crossover prevention, directly influencing the performance and longevity of AEMWE systems. However, existing AEMs face challenges such as low ionic conductivity and poor stability. This review first introduces the role of AEMs in electrolysis cells, outlines the requirements and evaluation parameters for high-performance AEMs, and emphasizes the OH^- transport mechanism and influencing factors in AEMs. The structural composition of AEMs, including common types of cationic groups and polymer backbones, is then detailed. The degradation mechanisms of various cationic groups and the characteristics of different polymer backbones are also discussed. We primarily focus on the design strategies for enhancing the stability of cationic functional groups, modification and preparation methods for polymer backbones, and the overall performance of AEMs. Finally, we address the challenges faced by AEM membranes and explore potential future research directions. This review suggests that high-performance AEMs suitable for practical applications should be developed through strategies such as crosslinking, block copolymerization, side-chain grafting, and composite membrane technology, based on the design of alkali-stable AEMs. These approaches provide valuable references and guidance for the advancement of AEMs in hydrogen production technologies.

The energy storage technology of flow redox cells is not only the key to the efficient use of new energy resources, but also the core technology to implement the "dual carbon" goals. Through the analysis of the working principle of flow redox cells, it is found that the energy density of flow redox cells is related to the solubility of the active substances in the electrolyte and the electrochemical activity. The optimization of flow redox cell performance can be achieved by constructing a multi-electron transfer system, improving the solubility of active substances, and increasing the voltage. At the same time, the performance and research progress of different types of flow redox cells are analyzed, and the applications of flow redox cells in different scenarios are summarized, so as to prospect the future development direction of flow redox cells.

The multi-energy complementary system integrating wind, solar, and energy storage technologies optimizes the use of renewable energy resources, enhancing both economic and environmental benefits. This study proposes a multi-energy complementary system model that incorporates wind, solar, and energy storage. The objective is to minimize the system's overall cost and carbon emissions, addressing both economic and environmental concerns. An improved non-dominated genetic algorithm is developed to obtain the Pareto optimal solution set for the multi-objective optimization problem. The optimal capacity configuration and operation scheme are determined using the technique for order preference by similarity to ideal solution. The system's operation scheduling is optimized using the CPLEX solver, a linear programming software, to validate the effectiveness and accuracy of the proposed system framework and scheduling model. Results demonstrate that the proposed optimization method significantly enhances renewable energy utilization, minimizes economic costs and carbon emissions, and improves the system's economic and environmental performance. This research offers valuable insights for the sustainable, stable, and reliable energy supply of renewable energy systems and supports the low-carbon transition of industrial parks.

To address the complex thermal challenges in lithium-ion battery thermal management systems during charging and discharging, a physical model of a multi-channel battery pack thermal management system with a spoiler structure was developed and validated using measured parameters of a single battery. Numerical simulations based on the finite volume method were performed for both non-spoiler and various spoiler configurations. The Nusselt number and Fanning friction coefficient were used to characterize the heat transfer and flow characteristics of the battery pack system. The impact of different spoiler parameters, including angle, length, and arrangement, on the heat transfer and flow characteristics of the battery pack were analyzed through numerical simulations. The results indicate that the spoiler structure enhances turbulence intensity, improves convective heat transfer efficiency on the battery cell surface, and increases the system's pressure difference. As the spoiler angle increases, the maximum temperature and temperature difference of the battery pack initially increase and then decrease. Conversely, increasing the spoiler length causes the maximum temperature and temperature difference to first decrease and then increase. Optimal thermal performance is achieved with a spoiler angle of 45° and a length of 15 mm. When the spoiler length and angle are fixed, the arrangement of the spoiler structures has a minor effect on the thermal characteristics but still performs better than the non-spoiler configuration. These findings provide valuable insights and a robust foundation for designing and optimizing thermal management systems for multi-channel battery packs in lithium-ion battery charging and discharging equipment.

Due to the high risks and costs associated with fire and explosion tests, simulated investigations of fire characteristics and suppression performance in energy storage systems are crucial. This study establishes a full-scale simulation model for a 20-foot energy storage container using Fire Dynamics Simulator software. The research analyzes the fire propagation process within the battery system and examines the diffusion patterns of typical gases, including CO₂, H₂, and CO. Results indicate that the concentrations of H₂, and CO at the center of the fire source can exceed 1000 ppm(1 ppm=10^-4%), whereas concentrations at the container's corners range from 24 to 183 ppm. Additionally, the temperature and distribution of characteristic gases stabilize within 10 seconds, exhibiting a distinct stratification phenomenon. The water spray system demonstrates a significant cooling effect, rapidly reducing temperatures from 791 ℃ to below 330 ℃. However, the use of water spray can lead to incomplete combustion of the ignited battery box, resulting in an increased concentration of combustible gases in localized areas of the energy storage system. This study aims to provide a simulation-based approach for the safety design and fire prevention strategies of lithium-ion battery energy storage systems.

Carnot batteries, known for their efficiency, environmental benefits, flexibility, and reliability, hold substantial potential for energy storage applications. This study focuses on a packed bed thermal energy storage (TES) system, designed and integrated into a 20 kW/5 h Carnot battery experimental setup. Stratified thermal storage was achieved through the use of three layers of different materials, facilitating cascading heat storage and release.Two-dimensional axisymmetric simulations, validated experimentally, were used to investigate the effects of phase change intervals and porosity on the cascaded packed bed thermal energy storage (CPB-TES) system. To enhance energy efficiency and ensure stable operation of compressors and expanders within the Carnot battery, a heat exchanger was implemented at the backend of the system to recover excess heat from the CPB-TES. Results indicated that while increasing the inlet temperature and flow rate accelerated phase change processes and charge-discharge rates, it also led to energy losses. Smaller phase change intervals resulted in more pronounced plateaus within the phase change material, thereby shortening the phase change duration. A porosity of 0.4 in the packed bed exhibited higher energy storage density and more efficient heat exchange between the fluid and phase change material compared to a porosity of 0.6. Under experimental conditions with a minimum inlet flow rate of 120 m³/h and a maximum inlet temperature of 331 ℃, the round-trip efficiency of the system up to 70.31% through to heat recovery. This research offers a comprehensive analysis of critical components in Carnot batteries, driving overall system optimization and supporting the efficient and scalable application of Carnot batteries.

The rapid advancement of next-generation information technology has led to a significant increase in data center construction, which demands continuous power supply and uninterrupted cooling. Concurrently, with the growing adoption of global renewable energy, many countries have introduced peak-valley electricity pricing policies. The current cooling systems in data centers often exhibit suboptimal cooling performance and high energy consumption, making it challenging for these centers to adapt to existing electricity pricing policies. To address this issue, this study proposes a novel combined cooling and power system for data centers by integrating two-phase immersion liquid cooling technology with Carnot battery energy storage technology. To assess the feasibility of this system across different regions, Harbin, Nanjing, and Guangzhou were selected as case study locations. The study compares and analyzes the energy efficiency and economic performance of the proposed system against the immersion cooling system utilizing natural cooling mode throughout the year. Results indicate that the new system reduces the annual electricity cost per kilowatt of data center IT equipment by 235.52 CNY, 245.24 CNY and 281.28 CNY in Harbin, Nanjing, and Guangzhou, respectively. The proposed scheme significantly enhances the power flexibility of data centers while substantially reducing their operational and maintenance costs.

To enhance the utilization of low-temperature waste heat in the steel industry, this study integrates low-temperature flue gas waste heat from the outlet of a sinter annular cooler into a pumped thermal energy storage (PTES) system. The PTES system comprises a heat pump (HP) cycle, a heat storage system, and an organic Rankine cycle (ORC). A thermodynamic calculation model of the PTES cycle process was developed, examining the effects of HP condensation temperature, ORC evaporation temperature, and ORC superheat degree on the system's performance with different working fluids. Results indicate that lowering the HP condensation temperature and raising the ORC evaporation temperature can improve the heating coefficient (COP_new) and power efficiency (η_ptp) of the PTES system. When isobutane is used as the ORC working fluid, COP_new and η_ptp decrease by 0.16 and 0.88%, respectively, as the HP condensation temperature increases by 2 ℃. Conversely, COP_new, ORC thermal efficiency (η_ORC), and η_ptp increase by 0.034, 0.26%, and 0.68%, respectively, with a 2 ℃ increase in ORC evaporation temperature. Compared to the ORC evaporator, temperature matching between the circulating working fluid and the heat storage medium in the HP condenser has a more significant impact on system performance, and the HP condensation temperature does not affect η_ORC. With constant HP condensation and ORC evaporation temperatures, reducing the ORC superheat degree improves the PTES system's thermodynamic performance. Considering COP_new, η_ORC, and η_ptp, R245fa is identified as the optimal working fluid for the ORC, followed by isobutane and R236ea. For PTES systems driven by low-temperature sinter flue gas waste heat, R245fa is recommended as the preferred ORC working fluid.

Phase conversion thermal energy storage technology serves as a primary technical approach to regulate energy supply and demand while enhancing energy utilization due to its high heat storage density and stable temperature. This study presents a physical model of a combined phase change thermal storage unit, consisting of plate-capsule arrangements with three different diameters of phase change capsules equidistantly spaced, using paraffin as the phase change material and urea-formaldehyde resin as the capsule wall material. To account for the variation in physical parameters of the phase change material during the phase change process, the apparent heat capacity method is modified using a functional approximation. The simulation calculates the phase change thermal storage system considering the effects of internal natural convection and heat transfer fluid flow. The analysis focuses on the impact of capsule diameter on the heat storage process, examining variables such as the liquid phase rate within the capsules, average temperature, and heat flux variation over time. The findings indicate that the diameter of the phase change capsules significantly influences the thermal storage performance of the system. The enhancement of natural convection within the capsules increases with larger diameters, leading to extended phase change and heat storage durations. Capsules with larger diameters exhibit higher effective thermal conductivity during the melting phase, which gradually stabilizes to a constant value. In addition, the PCM (phase change material) heat flux initially fluctuates with time before settling to a constant value.

The electrolytic water hydrogen production system, integrated with hydrogen storage, serves as an ideal adjustable resource by regulating power and facilitating large-scale renewable energy consumption. This study introduces virtual synchronous motor (VSM) control technology into electrolytic hydrogen production to address issues of insufficient inertia and poor frequency stability arising from the large-scale integration of renewable and clean energy into power grids. Using the proton exchange membrane (PEM) electrolysis hydrogen production system as a case study, a VSM control strategy is proposed. First, the independent adjustment of the electrolytic cell's power is achieved by implementing a DC current control mechanism, effectively reducing grid frequency fluctuations during load variations. Next, the impact of current regulation rate limits within the electrolytic cell on the frequency adjustment transition process is analyzed. A microgrid simulation system is then developed using MATLAB/Simulink. Experimental results indicate that, compared to traditional double closed-loop control, the PEM electrolysis hydrogen production system based on VSM control independently adjusts the hydrogen production power during grid load changes, reducing grid frequency variation by 64.71%.

Frequent natural disasters in recent years have posed significant threats to the safe operation of distribution power systems. The energy storage batteries in electric vehicle exchange stations, known for their easy transportability, show great promise for emergency power supply scenarios. In order to enhance the resilience of distribution networks, this paper proposes an operational scheduling method that utilizes electric vehicles to transport energy storage batteries from exchange stations. The study begins by developing an optimization model for the distribution network that integrates the EV transportation traffic network, aiming to minimize system operating costs during emergencies. This model considers factors such as load loss cost, generation cost, and transportation cost. Then, the nonlinear parts of the optimization problem are analyzed, and the problem is then reformulated into a mixed-integer optimization problem, making it easier to solve. The proposed strategy is verified through case studies demonstrating its effectiveness under certain boundary conditions. This method enables the intelligent dispatch of swappable electric vehicles, effectively transferring energy storage batteries from areas with sufficient energy to those experiencing shortages. This approach not only reduces the operating costs of the power system during emergencies but also significantly enhances the overall resilience of the power system's operations.

With the advancement of carbon peaking and carbon neutrality goals and the evolution of new power systems, the carbon market and energy storage systems have become essential components in enhancing the economic and low-carbon performance of distribution networks. This study establishes an optimized operation model for distribution networks integrated with energy storage, considering the dynamics of the carbon trading market. The model employs carbon emission flow theory to analyze node carbon potential within the power topology network, constructing a framework for calculating the internal carbon flow and carbon potential of storage systems, taking into account charging and discharging efficiencies. The Shapley value method, which evaluates individual marginal benefits, is utilized to allocate carbon emission responsibilities on the user side. Simulation results from an IEEE-33 node distribution network reveal that user-side carbon emission responsibilities are significantly influenced by load scale and location. The Shapley value method proves effective and equitable in managing carbon responsibility allocation. Under conditions ensuring reliable grid operation, a distribution network system equipped with energy storage and a tiered carbon pricing mechanism can achieve a 10.7% reduction in overall regional carbon emissions, an 8.2% increase in profits for distribution network operators, and a 5.7% reduction in user carbon costs. This research highlights the pivotal role of energy storage systems in optimizing operations and reducing emissions in high-renewable energy distribution networks, offering both theoretical and practical support for the future low-carbon and economically efficient operation of power grids.

Combined Cooling, Heating, and Power (CCHP) systems are critical for industrial parks and building users to achieve dual carbon reduction goals in their energy utilization. This study addresses the challenges of energy imbalance, equipment coupling, grid connection, and online access modes within CCHP systems by integrating a battery energy storage system and a water tank thermal storage system. A multi-objective optimization function for the CCHP system's energy management strategy is developed, targeting operating costs and fuel consumption. The study considers the impact of constraints and congestion operators on the search performance of the non-dominated sorting genetic algorithm (NSGA-II) and applies an improved NSGA-II algorithm to optimize the CCHP system's energy management strategy. The results demonstrate that, in grid-connected and online modes, the CCHP system with composite energy storage achieves reductions in daily operating costs and fuel consumption by 0.89% and 2.11%, respectively, on typical summer days compared to a system without energy storage. On typical winter days, the savings increase to 27.70% and 7.30%, respectively, with annual reductions of 11.11% in operating costs and 6.06% in total energy consumption. These findings indicate that the energy management strategy derived from the improved NSGA-II algorithm provides effective energy regulation for the CCHP system with composite energy storage.

During the independent operation of DC microgrids, the integration of numerous power electronic conversion devices, coupled with the power fluctuations of renewable energy sources and variable loads, results in reduced inertia, lower damping, and compromised stability. These conditions often cause significant bus voltage fluctuations, potentially threatening the stable operation of the DC microgrid. To address these challenges, this paper investigates an enhanced virtual DC motor (VDCM) control strategy based on parameter adaptation to improve the transient stability of the bus voltage. The control principle of the virtual DC motor is introduced, and a small-signal model of the energy storage control system is established. An in-depth analysis is conducted on the influence of virtual inertia, damping coefficient, and voltage regulator proportional and integral parameters on system stability, highlighting the parameter requirements during each stage of bus voltage fluctuations. Based on this analysis, functional relationships between virtual inertia, proportional coefficient, integral coefficient, and bus voltage deviation are derived. By dynamically adjusting VDCM and voltage regulator parameters in response to voltage deviations, the proposed strategy effectively reduces recovery time under disturbances and minimizes voltage fluctuations. The correctness and feasibility of the proposed control strategy are validated through a hardware-in-loop experimental system utilizing a real-time digital simulator and rapid control prototyping.

The rapid advancement of energy storage technologies has enabled the use of their fast regulation capabilities to alleviate power supply pressures on conventional sources during automatic generation control (AGC), enhancing system frequency stability. However, issues such as overcharging, over-discharging, and suboptimal power allocation in energy storage systems during AGC control have led to poor performance evaluations under the control performance standard (CPS). This paper proposes an AGC control strategy that integrates CPS indicators and the real-time state of energy storage. Initially, a dynamic model for frequency regulation is developed based on the AGC control process, and a simplified transfer function is derived according to the response characteristics of each component. To improve the rationality of power allocation, initial distribution between battery energy storage system (BESS) clusters and non-BESS clusters is determined based on the state of charge (SOC), followed by a secondary allocation among individual BESS units considering adjustable power variability. Additionally, controller parameters are fine-tuned using feedback from CPS results to ensure frequency regulation commands align with frequency regulation requirements. Finally, simulations based on actual CPS evaluations, frequency deviations, and the state of energy storage, conducted using data from a northern region's installed capacity, demonstrate that the proposed strategy enhances CPS quality and optimizes the frequency regulation capabilities of energy storage.

The intermittency and instability of renewable energy generation pose significant challenges to the stable operation of power grids, and the application of energy storage technology is key to addressing these issues. Therefore, a multi-objective optimization method for the capacity configuration of renewable energy and energy storage stations based on confidence theory is developed in this paper, aiming to enhance grid stability and reliability. First, the uncertainties brought by the high proportion of renewable energy integration into the grid are analyzed and a multi-objective robust optimization model is established. Then, based on confidence theory, a normalized regularization constraint method is developed to generate a diverse Pareto solution set, ensuring the validity and diversity of solutions under different uncertainties. Finally, the long-term performance of each Pareto solution is simulated through posterior sample analysis to evaluate its practical effect. Case studies on the IEEE transmission network show that at lower confidence interval values, the total system cost is lower but the adjustment capability is limited; while at higher confidence interval values, the system's adjustment capability significantly improves, but the total cost also increases. Additionally, when facing a 5% load fluctuation, the system's operating cost is reduced by 15%, and power supply reliability is increased by 10%.

To enhance the utilization of substantial regenerative braking energy generated by electric locomotives and address voltage unbalance issues caused by single-phase traction power supply systems in the grid, this paper proposes a YNd-multiport based railway hybrid energy storage system (YNd-MC-RHESS). The operational principles and modes of the YNd-MC-RHESS are first analyzed. A power optimization control strategy for the multiport converter is then developed with the primary goal of maximizing regenerative braking energy utilization. This strategy integrates nonlinear current control to enhance the converter's response time and improve the energy allocation efficiency within the hybrid storage system. Finally, the proposed control strategy is validated using Hardware-in-the-Loop (HIL) dynamic simulations under typical operational scenarios, demonstrating its capability to dynamically manage power transfers between different ports and ensure equitable energy allocation and release across various storage media. Experimental results reveal that, following the deployment of the hybrid storage system, the utilization rate of regenerative braking energy reaches 93.67%, thereby achieving efficient use of this valuable energy resource.

To regulate voltage fluctuations in urban rail transit traction systems caused by the frequent acceleration and deceleration of trains, this study proposes a passivity-based collaborative control method utilizing ensemble empirical mode decomposition for a hybrid energy storage system (HESS) composed of supercapacitors and batteries. This method enables the recovery of regenerative braking energy and reduces the overall energy consumption of urban rail transit systems. The ensemble empirical mode decomposition technique is employed to extract multiple intrinsic mode functions of the HESS, allowing precise reconstruction of high-frequency and low-frequency components through the instantaneous frequency curve of each intrinsic mode function processed by the Hilbert transform, thereby enhancing the power trajectory accuracy for both supercapacitors and batteries. To address the multi-variable, strongly coupled, and nonlinear nature of the HESS, a bilinear model is developed in dq coordinates, facilitating synchronous linear transformation of state and control variables. A globally asymptotically stable passivity-based controller is then proposed to ensure synchronized and rapid tracking of desired power trajectories, achieving collaborative control even under external uncertainties. Simulation results using MATLAB demonstrate that the proposed method ensures long-term cooperative operation of supercapacitors and batteries, effectively meeting the demands for regenerative braking energy recovery and utilization in urban rail transit. The proposed approach offers advantages such as rapid response and robust stability.

In recent years, the scale of urban rail transit has grown very rapidly, and the overall energy consumption of rail transit transportation systems has increased accordingly. Aiming at the problem of high energy consumption in rail transit transportation, this paper studies and analyzes the capacity configuration and energy optimization of rail energy storage systems. First, the research and application progress of energy storage systems in rail transit transportation is summarized, and then the capacity configuration and energy optimization problems of energy storage systems are analyzed and modeled, and a full life cycle cost model of energy storage systems is constructed. Finally, a hybrid optimization algorithm based on genetic algorithm and particle swarm algorithm is proposed to obtain the minimum total cost and the corresponding capacity and energy configuration, which will help achieve the goals of energy-saving, low-carbon and green rail transit transportation.

Artificial intelligence technology plays an important role in modern battery automation production. This article summarizes the application of artificial intelligence technology in battery automation production. The article first analyzes the current research progress of artificial intelligence technology, including model algorithms and computing power directions. Then, from the perspectives of automated production control, intelligent production testing, predictive maintenance, and environmentally friendly production, the improvement of artificial intelligence technology on battery automation production was emphasized. At the same time, the development trend of the combination of energy storage industry and artificial intelligence technology was analyzed and summarized.

With the continuous innovation of renewable energy and distributed power generation technology, the power system has ushered in a new round of upgrading and transformation. Virtual energy storage technology, as a new type of energy management technology, provides a new solution for energy balance and stable operation of power plants. This article reviews the application of virtual energy storage technology in the daily work of modern power plants, including the theoretical research and technological development process of virtual energy storage technology, as well as the optimization effect of virtual technology on various types of work in power plants. It has been proven that by introducing virtual energy storage technology, energy utilization efficiency and power quality can be effectively improved. In the future, related industry technologies are bound to be more widely applied and researched.

Photovoltaic energy storage coupling regulation is the basis for the stable and efficient operation of distribution network. With the vigorous development of renewable energy, photovoltaic power generation is more and more widely used in distribution network. How to solve the volatility of photovoltaic power generation has become the key to parallel operation. The introduction of the energy storage system into the field of photovoltaic power generation lays a foundation for realizing the dynamic balance between photovoltaic power supply and load-side consumption, and also provides an optimal scheme for the optimal operation of distribution network. This paper analyzes the function of photovoltaic energy storage in the operation of distribution network, and puts forward the strategy to improve the operation stability of distribution network based on photovoltaic energy storage from multiple perspectives such as output power, energy utilization ratio, digital management, uncertainty optimization and voltage regulation.

Lithium-ion batteries, known for their lack of memory effect, lightweight nature, and environmental friendliness, are widely used as energy sources in electric vehicles, electronic devices, and various scales of energy storage. In a lithium-ion battery management system, the state of charge (SOC) is a critical indicator, and its accurate estimation is essential for efficient energy management and optimal control of the battery system. This paper proposes an SOC estimation method based on the dynamic noise-adaptive unscented Kalman filter (DN-AUKF). The open circuit voltage (OCV) of the battery at different SOCs is first obtained through intermittent discharge experiments and fitted to derive the OCV-SOC curves. The lithium-ion battery is then modeled using a second-order RC equivalent circuit model, with parameter identification conducted via the hybrid pulse power characterization (HPPC) test. Recognizing that the SOC estimation in lithium-ion batteries is a nonlinear process and highly susceptible to operational noise, this study utilizes a traceless transform based on the Kalman filter (KF) to address system nonlinearity, integrates an adaptive factor for noise characteristic estimation, and dynamically adjusts the process noise covariance to enhance algorithm robustness and estimation accuracy. The proposed algorithm is validated under dynamic stress test (DST) and federal urban driving schedule (FUDS) conditions, demonstrating that the DN-AUKF algorithm significantly improves average estimation error, maximum error, and root mean square error compared to the adaptive unscented Kalman filter (AUKF) and unscented Kalman filter (UKF) algorithms under various conditions. The DN-AUKF's average absolute estimation error is less than 0.51%, indicating its superior performance in accurately estimating the SOC of lithium-ion batteries, even under extreme conditions such as low power and high-rate charge and discharge scenarios.

The state of charge (SOC) is a crucial metric for assessing the remaining power of lithium batteries, playing a significant role in optimizing battery usage and ensuring safety. To address the challenge of SOC estimation using the H infinity frilter (HIF), which offers high robustness but limited accuracy, this study proposes an adaptive unscented H infinity filter (AU_HIF) to enhance estimation precision. The dual polarization equivalent circuit model, known for its balanced accuracy and complexity, is selected to develop the new estimation algorithm. The unscented Kalman filter (UKF), which is more suitable for nonlinear state estimation compared to the traditional extended Kalman filter, is combined with a novel fading factor designed based on the prior error covariance matrix. This design minimizes the impact of outdated measurements on estimation results, improving the tracking capability and accuracy of the filtering algorithm. The effectiveness of the proposed AU_HIF is validated through simulations using data collected from a custom-built experimental platform. Results demonstrate that the adaptive unscented HIF outperforms traditional H infinity filtering, the standard UKF, and other modified H infinity filtering algorithms in terms of estimation accuracy and robustness. This research significantly enhances SOC estimation for battery systems used in new energy vehicles and energy storage power stations.

Accurate estimation of the state of charge (SOC) and state of peak power (SOP) is crucial for ensuring the safe and stable operation of vanadium redox batteries (VRBs). To address the high errors and poor robustness associated with traditional estimation algorithms, this paper proposes a joint estimation method for SOC and SOP of VRBs based on adaptive unscented Kalman filtering (AUKF) and economic model predictive control (EMPC). First, considering the coupling characteristics of the electrochemical and fluid dynamics fields of VRBs, a comprehensive equivalent circuit model is developed to accurately represent the VRB operation. The artificial bee colony (ABC) algorithm is employed for offline identification of model parameters. Subsequently, given the limitations of the traditional unscented Kalman filter (UKF) algorithm, such as sensitivity to system noise, poor convergence, and neglect of dynamic battery parameters, an online parameter identification and SOC estimation algorithm based on AUKF is proposed. This approach enhances the model's accuracy by adaptively adjusting UKF parameters. Building on the SOC estimation results, the EMPC algorithm is utilized to estimate SOP, considering constraints including voltage, current, SOC, and electrolyte flow rate. The proposed SOC/SOP joint estimation algorithm's accuracy is validated under multiple experimental conditions. The findings of this research provide a reliable basis for predicting the peak power of VRBs under various operating conditions and for the precise scheduling of energy storage stations.

Internal short-circuit (ISC) faults in lithium-ion battery (LIB) systems are major contributors to thermal runaway and fire incidents. Diagnosing ISC faults is crucial for early warning of potential accidents and ensuring the safe operation of LIB systems. The isolated forest algorithm, an unsupervised anomaly detection method, is widely utilized in identifying anomalous data. Leveraging the characteristic voltage deviation of ISC-affected LIBs within a series-connected LIB pack, this study proposes an ISC fault diagnosis method based on the isolated forest algorithm. To validate the proposed method, a series-connected LIB module was constructed to perform ISC experiments under various short-circuit resistance conditions. ISC experiments were also conducted in an echelon-utilized LIB energy storage system (ESS) under real-world operating conditions. The isolated forest algorithm was then applied to analyze the experimental data. Results indicate that, under cyclic charging and discharging conditions, the algorithm achieved an accuracy rate of over 74%, a recall rate exceeding 76%, and a precision rate above 91% for a 1000 Ω ISC fault. For dynamic driving conditions of electric vehicles, the algorithm demonstrated an accuracy rate above 86% and a recall rate over 95% for a 300 Ω ISC fault. In the ESS's actual operating conditions, the recall rate for detecting a 25 Ω ISC fault exceeded 98%. The experimental outcomes confirm that the isolated forest algorithm effectively detects micro-ISC faults in LIBs across various operational scenarios, with detected ISC resistance reaching the magnitude of thousands of ohms.

Lithium-ion batteries, as electrochemical energy storage devices, involve complex multi-physical field coupling, making non-destructive monitoring of their internal state crucial for enhancing battery management capabilities. Due to the low thermal conductivity of cells and insufficient heat exchange between the battery and the external environment, temperature distribution within the cell is uneven during operation, resulting in significant temperature differences between the internal and external regions. This study employs the integrated functional electrode (IFE) concept, utilizing an in situ S-shaped fiber optic sensor to monitor the internal temperature distribution of the NCM523 pouch cell, capturing temperature evolution patterns before and after battery aging and identifying hotspot locations. Results confirm that embedding the fiber optic sensor does not impair the electrochemical performance of the cell during extended cycling, establishing the reliability of in situ temperature monitoring. Post-mortem analysis of the IFE after battery aging reveals its ability to decouple fiber optic signals, monitor temperature without adverse effects on electrochemical performance, resist corrosion, and enable distributed in situ temperature measurement. By analyzing temperature data, this study proposes using the rate of temperature rise during the constant-current discharge stage as a critical parameter for battery management. It highlights that the temperature evolution in the central region of the battery and around the positive electrode tab is crucial for effective battery monitoring and management.

The ongoing advancements in sodium-ion battery technology necessitate an in-depth understanding of capacity fading mechanisms during high-temperature storage to enhance the calendar life of these battery systems. This study systematically investigates the high-temperature storage performance of Na₄Fe₃(PO₄)₂P₂O₇-based sodium-ion batteries. A comprehensive analysis was conducted using multiple techniques, including transmission electron microscopy (TEM), inductively coupled plasma emission spectroscopy(ICP), Raman spectroscopy, Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy(XPS) , to assess changes in specific capacity, structural integrity, morphology, and interfacial components of both cathode and anode active materials during storage. Results reveal a slight decrease in electrode specific capacity after storage, without significant structural damage to the cathode or anode. Iron dissolution from the cathode was minimal, showing negligible crosstalk. However, the solid electrolyte interphase (SEI) on the anode thickened significantly, with the SEI layer dissolving and regenerating continuously, primarily composed of organic components. These findings indicate that side reactions at the anode interface are the primary contributors to capacity loss during high-temperature storage. This work deepens the understanding of the calendar aging process in sodium-ion batteries and provides critical scientific insights for enhancing sodium-ion battery performance.

With the increasing demand for longer ranges in electric vehicles, the cathode materials of Li(Ni _x Co _y Mn_1-x-y )O₂ (NCM) cells are shifting from low-nickel (NCM111) to high-nickel (NCM811) compositions. This study investigates the thermal runaway propagation behavior, deformation characteristics, and residue analysis of 51 Ah NCM811 lithium-ion batteries in confined spaces. Results show that during thermal runaway in confined spaces, all cells in the NCM811 battery module expelled a significant amount of red high-temperature particles, although only the triggered cell exhibited a pronounced jet fire. While confined spaces can suppress flame formation during thermal runaway, they cannot prevent the propagation of thermal runaway within the battery module. The front and back surface temperatures of NCM811 cells at 100% state of charge during thermal runaway ranged between 820 ℃ and 979 ℃, with propagation times ranging from 52 to 106 seconds. The mass loss ranged between 390—462 g, corresponding to a mass loss percentage of 45.58%—52.73%. Post-thermal runaway analysis revealed significant agglomeration of cathode material particles, with numerous holes observed on the particle surfaces. The oxygen content in the cathode material decreased from 39.96% to 32.15% after thermal runaway, confirming oxygen release during the event. This study provides a theoretical basis for the safe and optimal design of high-nickel NCM lithium-ion battery modules, the suppression of thermal runaway propagation, and insights into thermal runaway accident investigations of high-nickel batteries.

This study aims to investigate the toxic products generated during the thermal runaway of ternary lithium-ion batteries and examine the impact of structural changes on battery performance and safety. With the rapid growth of the electric vehicle market, ternary batteries have gained popularity due to their high energy density and extended service life. However, thermal runaway poses a significant safety risk for electric vehicles, making it a critical area of concern for the industry. In this research, we initiated the thermal runaway of ternary batteries using flame ignition and subsequently collected and analyzed the gases produced. Experimental results indicated that the severity of thermal runaway intensifies with an increase in the state of charge (SOC). Once thermal runaway occurs, it can easily trigger a chain reaction in nearby batteries. During this process, toxic gases including carbon monoxide (CO), hydrogen fluoride (HF), acrolein, acrylonitrile, and aromatic chemicals are emitted. Notably, carbon monoxide and several other toxic compounds pose severe health risks. Building upon the analysis of toxic emissions, this study further examined the structural changes occurring within the battery during thermal runaway. Advanced characterization techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS), were employed to observe and analyze battery materials before and after thermal runaway. The findings revealed that the cathode and anode materials undergo significant pyrolysis and oxidation, resulting in the generation of substantial quantities of gas and macromolecular compounds. These byproducts further accelerate the thermal runaway process and contribute to the structural degradation of the battery. This study not only elucidates the toxic emissions generated during the thermal runaway of ternary batteries and their associated hazards but also provides an in-depth analysis of the structural transformations within the battery. The findings offer crucial data for the safety evaluation of electric vehicles and serve as a valuable reference for the improvement and optimization of ternary lithium-ion batteries.

The thermal runaway of lithium-ion batteries releases a significant amount of gas, drawing considerable attention from researchers. Detecting and analyzing these gas products is a crucial aspect of studying thermal runaway in lithium-ion batteries. This review first introduces the reactions occurring at various stages of thermal runaway and identifies the sources of the main gas products. It then focuses on the current primary detection and analysis technologies for thermal runaway gas products from lithium-ion batteries, including gas sensors, Fourier transform infrared spectroscopy (FTIR), gas chromatography (GC), gas chromatography-mass spectrometry (GC-MS), Raman spectroscopy, ion chromatography (IC), composite gas analyzers, and combinations of these technologies. The review summarizes the practical applications of each technology, evaluates their limitations, suggests problem-solving methods, and discusses the advantages, disadvantages, development, and application of these technologies. Furthermore, the current research status on the detection results of thermal runaway gas products is elaborated and analyzed from five aspects: gas generation mechanism, gas composition and production, combustion and explosion hazards, toxicity, and monitoring and warning, providing valuable insights for the safe use and development of lithium-ion batteries. Finally, based on an analysis of the advantages of detection technologies and research on gas products, gas sensors, and GC-MS combined with gas sensors are recommended as the most suitable gas analysis technologies, offering guidance for selecting appropriate detection methods. The future optimization, development directions, and prospects of gas product detection and analysis technologies are discussed, providing a reference for the advancement of related technologies.

Thermal runaway in lithium batteries is characterized by rapid temperature increases, easy propagation, and complex chemical reactions, making it difficult for conventional fire protection measures to quickly extinguish and cool affected batteries. This study proposes a low-pressure dual-fluid atomization spray fire protection system utilizing CO₂ and water, specifically designed for the fire protection and cooling of thermally runaway lithium batteries within liquid-cooled battery packs. The system monitors temperature changes both within the battery pack and individual batteries. An orthogonal experiment was conducted to investigate the influence of dual-fluid spray parameters on the cooling effect of thermally runaway lithium batteries, analyzing the impact of these factors on the results. Experimental findings demonstrate that the dual-fluid spray exhibits excellent diffusion characteristics within the battery pack, effectively cooling the thermally runaway battery located directly beneath the atomizing nozzle. Increased gas pressure, higher water flow rates, and a greater number of nozzle holes enhance droplet diffusion and significantly reduce battery cooling time. Among these factors, the atomizing gas pressure exerts the most significant influence on the experimental outcomes. Under optimal conditions, the dual-fluid spray system rapidly cools thermally runaway batteries to safe temperatures and effectively suppresses further heat propagation. This study's findings indicate that the proposed system surpasses traditional fire protection methods in terms of cost, environmental impact, and cooling effectiveness, presenting a novel solution for designing fire protection systems in energy storage stations and cabinets.

Lithium-ion batteries play a crucial role in promoting the widespread use of renewable energy and ensuring the stable operation of power grids. However, thermal runaway-induced thermal spread in these batteries can result in significant losses. Therefore, thermal runaway warning technology for lithium-ion batteries is essential for preventing safety issues. This study develops a lithium-ion battery thermal runaway test platform, collecting data on surface temperature, output voltage, and battery expansion pressure during normal cycles and overcharge-induced thermal runaway events. A total of 66895 samples were obtained, including 245 samples exhibiting overcharge thermal runaway. The dataset captures the continuous transition from normal operation to overcharge and subsequent thermal runaway in a time series. The internal volume changes of the battery are effectively represented by measuring the expansion pressure signals. A regression prediction algorithm based on SE-Res-LSTM is developed to predict battery expansion pressure, utilizing the prediction error to detect overcharge-induced thermal runaway in real-time. In terms of timeliness, early detection of overcharge thermal runaway is achieved 12 s after the onset of overcharging, which is 233 s earlier than the conventional temperature-based method that triggers a warning when the battery surface reaches 60 ℃. This significantly enhances the accuracy and responsiveness of early warning systems.

With the rapid development of the new energy vehicle industry, as an important link to ensure vehicle safety and performance, the stability and efficiency of the energy supply system of the testing station have become crucial. The composite energy storage system, as the core energy support of the new energy vehicle testing station, combines the advantages of various energy storage technologies to provide stable and efficient energy supply for the testing station. This article aims to explore the use and maintenance strategies of composite energy storage systems for new energy vehicle testing stations, analyze their working principles, application scenarios, and maintenance methods, and propose optimization suggestions, in order to provide reference for energy management of new energy vehicle testing stations.

Flywheel energy storage power metering technology is an innovative power management technology that combines flywheel energy storage with power metering technology. Flywheel energy storage has shown great potential for application in power systems due to its high power density, long lifespan, fast response, environmental friendliness, and pollution-free characteristics. Electricity metering technology is an important component of the power system, used for accurate measurement and monitoring of the use of electricity. Combining the two, flywheel energy storage power metering technology aims to improve the operational efficiency of the power system, optimize resource allocation, and promote the sustainable development of the power industry. This article analyzes the application research of flywheel energy storage power metering technology from the perspective of energy conservation and consumption reduction, and elaborates on the future application research directions of flywheel energy storage power metering technology from multiple perspectives, in order to achieve efficient and green management of the power system.

Compressed air energy storage, as an emerging energy storage technology, has received widespread attention due to its advantages of large-scale, high efficiency, and environmental protection. However, energy storage systems have extremely high requirements for power stability, so designing and introducing high-efficiency digital LDO low-voltage differential linear regulators play an important role in improving the stability and safety of compressed air energy storage systems. This article provides an overview of the LDO circuit design process in compressed air energy storage, including the principles and research progress of LDO technology, the requirements and steps for LDO circuit design in compressed air energy storage, and finally analyzes and elaborates on the practical improvement of LDO circuit design in compressed air energy storage.

This bimonthly review paper highlights 100 recent published papers on lithium batteries. We searched the Web of Science and found 6213 papers online from Aug. 1, 2024 to Sep. 30, 2024. 100 of them were selected to be highlighted. The selected papers of cathode materials focus on high-nickel ternary layered oxides and LiCO₂, and the effects of doping, interface modifications and their structural evolution with prolonged cycling are investigated. For anode materials, silicon-based composite materials are improved by optimized electrode structure and using new binders to mitigate the effects of volume changes. Efforts have also been devoted to designing composite metal lithium anode and controlling the inhomogeneous plating of lithium. The relation of structure design and performances of chloride-based and polymer-based solid-state electrolytes has been extensively studied. Different combinations of solvents, lithium salts, and functional additives are used for liquid electrolytes to meet the requirements for battery applications. For solid-state batteries, the modification and surface coating of the cathode, the design of composite cathode, the anode/electrolyte interface and 3D anode have been widely investigated. Studies on lithium-sulfur batteries are mainly focused on the structural design of the cathode and the development of functional coating and electrolytes, and solid state lithium-sulfur battery has also drawn large attentions. Dry coating technology for electrodes is developed for Li-ion batteries. Also the safety and recycling of Li-ion batteries are concerned. There are a few papers for the characterization techniques of the structural transition of cathode materials and the interfacial evolution of lithium deposition, while theoretical simulations are devoted to the study of ion transport in solid state electrolytes.

Compressed air energy storage (CAES) is recognized as a viable solution to address variability and uncertainty in wind power generation. The performance of energy storage systems is significantly influenced by market conditions and regulatory frameworks, which directly affect the system's quality, reliability, efficiency, and environmental impact. CAES systems can operate independently to maximize profit or in synergy with wind power generation to fully utilize renewable energy resources, thereby achieving mutual benefits in the market. This study investigates the application and potential advantages of CAES in wind power systems with transmission constraints. A comprehensive model is developed to optimize operational strategies for wind energy and CAES, assessing the contributions of CAES to system reliability, efficiency, and environmental goals. The results highlight the benefits of integrating CAES in balancing wind power, enhancing system performance across various metrics. The proposed methods and findings offer valuable guidance for utilities and policymakers in formulating effective regulatory frameworks, promoting large-scale energy storage integration, supporting the expansion of renewable energy, and ensuring a reliable power supply for consumers.

Energy serves as a critical foundation and guarantee for economic and social development. China's energy structure has long been dominated by coal, positioning the country as the world's largest carbon emitter. The urgent need for clean and low-carbon energy transformation highlights hydrogen as a key secondary energy source for achieving low-carbon objectives. This article first introduces the current state of the hydrogen energy industry in China. To foster industry development, the government has implemented a series of supportive policies. Despite rapid progress under these policies, a significant gap remains compared to developed countries, particularly in advancing key hydrogen technologies. This underscores the urgent need for cultivating "high-precision and cutting-edge" talents in the hydrogen energy sector to support its growth. Subsequently, the article details the development of hydrogen energy disciplines in China. In terms of academic programs, hydrogen science and engineering is an emerging field, currently offered by only six universities. On the research front, major universities have established dedicated teams and platforms to conduct scientific research in hydrogen energy. In addition, the article highlights academic advancements, including the publication of hydrogen energy literature, the launch of specialized journals, and the formation of hydrogen energy societies. The study further explores the construction of a hydrogen energy discipline system by integrating the interdisciplinary nature of hydrogen energy, focusing on four key areas of the hydrogen energy industry chain: hydrogen production, storage and transportation, application, and safety. To cultivate "comprehensive, applied, innovative, and internationalized" talents, the article proposes a talent training model that emphasizes interdisciplinary approaches, integration of industry and education, collaboration between scientific research and education, and international exchange. Finally, the article provides recommendations for the further development of hydrogen energy disciplines and strategies for talent cultivation in this critical field.