This bimonthly review paper highlights 100 recent published papers on lithium batteries. We searched the Web of Science and found 6847 papers online from Feb. 1, 2025 to March 31, 2025. 100 of them were selected to be highlighted. The selected papers of cathode materials focus on high-nickel ternary layered oxides, and the effects of doping, interface modifications and structural evolution with prolonged cycling are investigated. For anode materials, silicon-based composite materials are improved by optimized electrode structure and new binders to mitigate the effects of volume changes. Efforts have also been devoted to design composite metal lithium anode and control the inhomogeneous plating of lithium. The relation of structure design and performances of sulfide-based, chloride-based and polymer-based solid-state electrolytes has been extensively studied. Different combination of solvents, lithium salts, and functional additives are used for preparing 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 interface to 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 optimization of electrolytes, and solid state lithium-sulfur battery has also drawn large attentions. Thick electrode preparation technology is applied to Li-ion batteries. There are also a few papers for the characterization techniques of structural phase transition of the cathode materials and the interfacial evolution of lithium deposition, while theoretical papers are mainly focused on the ion transport behaviors in solid state electrolytes.

Sodium-ion batteries are regarded as one of the most promising next-generation electrochemical energy storage technologies owing to the abundant raw material availability and low cost. The presodiation technique offers a practical solution to replenish sodium ions irreversibly consumed during the first-cycle charging, a process caused by the formation of interfaces. By introducing an additional sodium source, this technique effectively improves the cycle life and energy density of the batteries, making it highly valuable for the large-scale production and application of sodium-ion batteries.Presoiation techniques are mainly divided into anode presodiation and cathode presodiation. Among these, the self-sacrificial sodium supplement agent pre-mixing method, part of the cathode presodiation technique, stands out owing to its simple operation and lack of need for additional equipment, making it favorable for large-scale implementation. This article first briefly introduces the classification of sodium supplement agents. It then examines the challenges associated with the practical use and production of the self-sacrificial sodium supplement agent pre-mixing method. Key challenges include safety and stability issues during production and storage, concerns related to the alkalinity and particle size of sodium supplement agents during electrode manufacturing, as well as issues such as excessive decomposition potential during battery cycling. The decomposition products and their impacts on electrode sheets after decomposition also pose significant problems. Subsequently, this article summarizes corresponding solutions proposed in recent years through presodiation-related research and patents. It further explores the application of this method in anode-free sodium-metal batteries. Finally, it presents design principles for developing improved sodium supplement agents, offering guidance for the future application of the cathode presodiation technique.

The energy density of lithium-ion batteries with graphite anodes is nearing its theoretical limit but still falls short of the demand for higher-energy-density batteries. Lithium-ion batteries with silicon-based anodes, lithium-sulfur batteries, and lithium-metal batteries, which offer higher specific capacities, can achieve a leap in energy density. However, these batteries face critical challenges in cycle stability and safety that must be urgently addressed. The use of electrode materials with high specific capacities inevitably leads to greater volume changes, posing significant challenges to battery preparation and stable operation. Scaffold materials offer excellent tunability, mechanical strength, and porosity, making them a promising solution for mitigating volume effects in high-specific-capacity electrode materials. This review classifies scaffold materials, analyzes the challenges faced by different components in high-specific-capacity batteries, and examines their applications in the cathode, separator, electrolyte, and anode of lithium-ion batteries. It discusses the working principles, advantages, and disadvantages of scaffold materials for different battery components. It also identifies key issues and severe challenges to advancing scaffold materials in the field of lithium batteries. Ultimately, it highlights potential future research directions for scaffold materials. This review aims to provide valuable insights and reference outputs for promoting the continuous advancement of battery technology through scaffold materials.

To effectively enhance the temperature uniformity of cylindrical lithium-ion batteries, this study proposes an innovative honeycomb-branching channel cold plate. A numerical simulation method was used to develop a cooling model for cylindrical lithium-ion battery packs, incorporating this unique cold plate design. The study focused on two critical factors affecting cooling performance: coolant temperature and channel branch angle. Performance comparisons were also made with two other designs, the honeycomb-serpentine channel cold plate and the planar serpentine channel cold plate, for a comprehensive evaluation. Results demonstrated that the honeycomb-branching channel cold plate effectively minimized the maximum temperature difference within the battery pack, especially under high coolant temperature conditions. The branch angle of the channels was found to weakly affect the peak temperature of the battery pack, offering flexibility in design options. Furthermore, compared to the honeycomb-serpentine and planar serpentine channel cold plates, the honeycomb-branching channel cold plate significantly lowered both the peak temperature and the maximum temperature difference of the battery pack, all while reducing energy consumption. This design proved especially effective in cooling high heat generation regions within the battery electrodes, making it a promising solution for thermal management systems seeking improved cooling performance and energy performance.

Overcharging has been identified as a primary contributor to thermal runaway (TR) in lithium-ion batteries (LIBs), where TR modeling plays a pivotal role in understanding coupled heat-gas generation mechanisms for safety enhancement. This study develops an integrated gas-thermal TR model incorporating side reaction-driven gas generation and internal pressure dynamics to characterize overcharge-induced failure. Systematic analysis reveals that charging rate (C-rate) and electrolyte decomposition potential critically govern TR progression, with parametric studies demonstrating that reducing C-rate from 2 C to 1 C combined with elevating electrolyte decomposition potential from 4.3 V to 4.7 V delays TR initiation by 22% in state-of-charge (SOC) while postponing safety valve activation by 15% SOC. The C-rate predominantly regulates temperature evolution during early overcharging (SOC<110%), whereas electrolyte decomposition potential dominates reaction kinetics in later stages (SOC>130%). Notably, increased C-rate substantially weakens the TR-suppressing effect of elevated decomposition potential (22% SOC reduction in suppression efficacy at 3 C vs 1 C), while safety valve activation exhibits stronger dependence on electrolyte stability with merely 3% SOC variation across 1—3 C rates. These findings establish quantitative correlations between material properties and failure thresholds, providing actionable insights for optimizing LIB thermal safety through coordinated charging protocol design and electrolyte stabilization strategies.

Lithium iron phosphate batteries have gained widespread application in energy storage owing to their long cycle life, high safety, and low cost, making them one of the mainstream electrochemical energy storage devices. However, research on the performance degradation and safety of LFP batteries during stationary storage remains limited and is not sufficiently comprehensive. This study focuses on commercial cylindrical LFP batteries, investigating the evolution of electrochemical performance and failure mechanisms under varying temperature gradients (from room temperature to 72 ℃ and different states of charge (SOCs ranging from 0 to 100%). A series of composite storage simulation experiments were conducted, employing various nondestructive analysis techniques and adiabatic acceleration calorimeters (ARCs). The experimental results have shown that the state of health (SOH) and thermal runaway characteristics of LFP batteries during storage are significantly affected by temperature and SOC. The capacity attenuation rate of LFP battery with 100% SOC at 72 ℃ is 22.1 times that at room temperature and 5.6 times that with 0 SOC. Higher temperatures and higher SOC levels accelerate capacity fading, mainly owing to the loss of active lithium ions and active materials within the battery. Conversely, the thermal safety of LFP batteries during storage has been improved, which may be attributed to the reduced energy within the battery system caused by the depletion of active materials. Finally, a semi-empirical prediction model of LFP battery capacity decay is constructed based on the characteristic peak strength using the incremental capacity (IC) method. This study provides valuable technical guidance for the operation, maintenance, and safety measures required for LFP batteries in future large-scale energy storage applications.

The traditional air-cooled thermal management system for battery packs is known for its simple design and low cost. However, it struggles with poor cooling uniformity and local overheating, particularly in high-power-density applications. To address this, two air duct structures and a novel air-cooled guide plate were designed using principles of fluid dynamics and heat transfer. Through simulations in Fluent, combined with Bernardi's heat generation theory and the Realizable k-ε turbulence model, the thermal performance of double "Z" and "U"-shaped ducts was analyzed. The double "Z" duct was selected to further investigate the effects of guide plate configuration, hole size, and inlet air velocity on the temperature and flow fields.Resultsshow that guide plates optimize flow distribution and improve internal temperature uniformity. Smaller holes in the guide plate significantly lower the maximum temperature, while higher inlet air velocities enhance overall cooling and minimize temperature variation. This study demonstrates that the proposed micro-perforated air-cooled unit effectively dissipates heat during high-rate operations, improving the lifespan and safety of energy storage battery packs.

A type of electrolyte-supported tubular solid oxide fuel cell (SOFC) with a NiO-YSZ|YSZ|LSCF-GDC structure has been successfully developed using cold isostatic pressing and dip-coating methods. The fabricated SOFC features an electrolyte thickness of approximately 200 μm. An ammonia decomposition catalyst was also prepared using an impregnation method, with nanoscale Ru catalyst anchored on the inner surface of microchannels in a honeycomb ceramic to create an ammonia decomposition reactor. The decomposition rate of ammonia increased with temperature, reaching 98.9% at 500 ℃ and 99.6% at 600 ℃ .The microchannel ceramic cracking reactor was then inserted and fixed upstream of the ammonia fuel input in the microtubular SOFC (μT-SOFC). Field emission scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) were employed to conduct microstructural characterization and elemental distribution analysis of both the μT-SOFC and the embedded cracking reactor. The μT-SOFC exhibited an open-circuit voltage of 1.19 V and, when fueled with ammonia, achieved maximum power densities of 8 mW/cm², 19 mW/cm², 41 mW/cm², 53 mW/cm², and 57 mW/cm² at temperatures of 600 ℃, 700 ℃, 750 ℃, 800 ℃, and 850 ℃, respectively. These power densities reached 62%, 61%, 98%, 98%, and 92% of the performance observed when using 75%H₂+25%N₂ was as fuel.This study employed an anode internal circular current collection mode, where each ring uniformly collected current. Simulation results indicated that the total current is roughly proportional to the number of rings. Currently, there is limited research on μT-SOFC electrolyte support systems, and this study provides guidance on the model of μT-SOFC with an electrolyte support system.

The potential of lithium metal batteries (LMBs) in high-energy-density applications such as electric vehicles, portable electronic devices, and other fields has become widely recognized. However, the cycling performance and safety of LMBs are degraded by uncontrolled growth of lithium dendrites and the formation of dead lithium during the charging and discharging processes. This paper establishes a multi-physics simulation model based on the phase-field method, which simulates the growth and dissolution of lithium dendrites. The effects of charging and discharging voltage, cycle number, and temperature on the dendrite morphology and dead lithium formation were systematically investigated. It was found that lithium dendrites begin growing during charging and dissolve during discharging. Dissolution begins at the trunk and root of the dendrite, leading to necking in narrow regions and eventual detachment from the electrode, forming dead lithium. The lithium deposition (dissolution) rates increase (decrease) with charging (discharging) time. Overall, the dissolution rate exceeds the deposition rate. Increasing the charging voltage increases the dendrite deposition rate and the morphological complexity, whereas increasing the discharging voltage increases the dendrite dissolution rate and the dead lithium formation. Increasing the number of cycles slows the dendrite growth but enhances the accumulation of dead lithium. Elevated temperatures suppress dendrite growth, promote lithium dissolution, and reduce dead lithium formation. This research provides valuable insights for enhancing the cycling performance and safety of LMBs.

Lithium fluoride carbon (Li/CF _x ) batteries are known for their exceptionally high specific energy among lithium primary batteries. However, they face challenges such as low voltage plateau, low actual specific energy, and poor rate performance during discharge. This article uses commercial Keqin black as a carbon source and uses a solid-phase direct fluorination method to prepare fluorinated Keqin black (FKB). To enhance material properties, the FKB/RGO composite is prepared via a solution thermal reduction method. This approach improves material conductivity, increases the active contact area between the electrode material and the electrolyte, and shortens the lithium-ion diffusion pathway. The resulting FKB/RGO material achieves a discharge specific capacity of 858.4 mAh/g at 0.1 C and a discharge capacity of 550.6 mAh/g at 10 C, demonstrating excellent energy density and rate performance. This work contributes to promoting the engineering application of FKB/RGO materials in high-performance battery systems.

Polytetrafluoroethylene fibrosability was utilized to create a dry, self-supporting film by prefibrosing the raw material into a uniform mixture, followed by hot roller pressing. The resulting dry diaphragm achieved a thickness of 120—200 μm and a surface weight capacity of 36—60 mg/cm², 2—4 times higher than current commercial wet electrode surface loads. Scanning electron microscopy (SEM) analysis of the membrane's surface and cross-section showed that the original granular polytetrafluoroethylene binder was fully fibrosed during mixing and hot pressing. The nanofibrous binder, formed during the preparation process, was evenly distributed across the electrode film, with polytetrafluoroethylene fibers and the conductive agent surrounding active particles, creating an abundant "3D" network structure. The diaphragm displayed excellent lyophilic properties, with measured optical contact angles ranging from 97° and 112°. The membrane electrode exhibited strong mechanical properties, with a maximum tensile force of 2.64 MPa, and an elongation is of 34.64%, ensuring the film's integrity during the winding process. The electronic resistivity of the diaphragm is as low as 13.58 mΩ·cm. For the 200 μm super-thick electrode, the first charge-discharge efficiency reached 87.51%, with a specific discharge capacity of 209.60 mAh/g, and a maximum discharge gram capacity of 160mAh/g at 1C ratio. This study demonstrates the feasibility of polytetrafluoroethylene fibrosis for advancing low-cost, large-scale electrode preparation technology, and provides a reliable solution for the efficient use of energy.

Electrolytes not only affect ion transfer processes but also participate in the formation of electrode-electrolyte interphases, which play an important role in the stability of battery cycling. Electrolyte additives play a crucial role in constructing electrode-electrolyte interphases; however, compared with lithium-ion batteries, numerous challenges remain in the research of sodium-ion battery electrolytes and their additives. In this study, fluoroethylene carbonate (FEC) and 1,3-propylene sultone (PS) were investigated as electrolyte additives for sodium-ion batteries. The effects of electrolytes with different additives on battery performance were analyzed. The results demonstrated that using an optimized FEC+PS dual-additive electrolyte formulation, the pouch cell maintained 85.1% capacity retention after 600 cycles at 1 C, and its cycle performance was significantly better than that of batteries without any additive or with FEC additive alone. This formulation significantly enhanced the lifespan of NaNi_1/3Fe_1/3Mn_1/3O₂ (NFM) || Hard carbon (HC) cells. Transmission electron microscopy and X-ray photoelectron spectroscopy analyses revealed that CEI/SEI containing sodium alkyl sulfonate (ROSO₂Na) and sodium fluoride (NaF) derived from FEC-PS dual-additive exhibited high mechanical stability and flexibility. These properties significantly enhance the interface stability of the electrode-electrolyte, efficiently suppressing the dissolution of NFM-positive transition metals and HC-negative Na dendrites during the cycle and alleviating the gas production of the pouch cell. Based on the pouch cell, the components of the electrode-electrolyte interphase were optimized by adjusting the additive composition. This approach enhanced both the stability of the battery interphase and its cycling performance, thereby providing theoretical and technical support for the advancement of high-performance sodium-ion battery electrolytes.

To address the challenges of temperature rise and excessive temperature differences during the operation of a 5 kWh household storage battery plug-in box, a submerged inner tank model was designed. The model allows the batteries to be directly immersed in a cooling medium, while maintaining electrical connectivity to an external battery pack. The study investigated how battery spacing, immersion height ratio, and discharge rate impact cooling performance during static immersion in the inner tank. In addition, the thermal safety performance of the model was experimentally analyzed. Results revealed that a battery spacing of 2.5 mm significantly improves temperature uniformity within the battery module. Optimal cooling performance was achieved when the batteries were 100% submerged. Discharging the fully immersed battery module at 0.5 C, 1.0 C, and 1.5 C notably reduced the maximum temperature compared to non-immersed conditions, while also greatly improving temperature uniformity. Subsequently, the accuracy of the conventional liquid cooling model was verified through experiments, with the simulation results closely aligning with experimental data, showing a maximum deviation of only 1.29 ℃. Finally, overcharge thermal runaway diffusion experiments demonstrated that this cooling method effectively suppresses the spread of thermal runaway.

Li₅FeO₄ (LFO) is a promising prelithium cathode additive owing to its high theoretical specific capacity, low cost, and non-toxic nature. However, practical applications of LFO are hindered by its high residual alkali content and low electrical conductivity, which significantly reduce its delithiation capacity. To address these challenges, this study employed a high-temperature solid-phase method to prepare pure LFO material and used plasma-enhanced chemical vapor deposition (PECVD) to produce LFO@C material. The physicochemical and electrochemical properties of LFO@C were investigated under varying carbon-coating times and temperatures. Characterizations using scanning electron microscopy (SEM), transmission electron microscopy (TEM), and energy-dissipative spectroscopy (EDS) showed that different PECVD carbon-coating parameters deposited different carbon layer structures on the LFO@C surface. A uniform and dense carbon layer was achieved when the material was carbon-coated at 500 ℃ for 2 h. X-ray diffraction (XRD) analysis confirmed that no irreversible phase transition occurred in LFO@C under these conditions, provided the carbon-coating temperature did not exceed 500 ℃ and the duration was limited to 2 h.The carbon content and electrical conductivity of LFO@C initially increased and then declined with extended carbon-coating time, while both properties increased steadily as the coating temperature rose. Residual alkali analysis demonstrated a significant reduction in the residual alkali content after PECVD carbon-coating. The surface of the carbon layer played a key role in the residual alkali value of LFO@C material. The electrochemical properties of the carbon-coated LFO@C materials have been greatly improved. Among the carbon-coated materials, the LFO-5002 material exhibited the highest initial charge specific capacity of 756.4 mAh/g at 2.0—4.2 V, and an irreversible capacity of 623.51 mAh/g, exceeding the uncoated LFO material by over 200 mAh/g. The results showed that PECVD could be used to coat the surface of LFO particles with a uniform and dense carbon layer. This process significantly reduced the residual alkali of the carbon-coated materials, while greatly enhancing electrical conductivity and capacity, and the prelithiation performance. In this work, the irreversible capacity of cathode prelithiation material LFO was significantly improved by carbon-coating modification, which provided technical guidance for the design of high capacity cathode prelithiation materials.

Sodium-ion batteries are emerging as one of the most promising energy storage systems beyond lithium-ion batteries, holding great potential for widespread adoption. However, their development is hindered by a low initial Coulombic efficiency (ICE). Sodium supplementation is recognized as an effective strategy to address this issue, playing a critical role in advancing the commercialization of sodium-ion batteries. This article reviews the research progress of presodium technologies worldwide It examines advancements from three key perspectives, namely cathodes, electrolytes, and anodes. For the cathodes, sodium supplementation methods include direct impregnation, sacrificing additives, and electrochemical treatment. The optimization of electrolytes primarily focuses on improving sodium salts and solvents, balancing their proportions, and incorporating additives. For anodes, sodium supplementation techniques include direct sodium supplementation, electrochemical presodium method, hard carbon modification. This review summarizes the current progress of sodium supplement technology, elaborates on their advantages and disadvantages, evaluates their commercial viability, and offers guidance for the development of sodium supplementation strategies in sodium-ion batteries.

Aqueous zinc-ion batteries (AZIBs) have emerged as promising candidates for large-scale and long-term energy storage because of their low cost, nontoxicity, and high theoretical capacity. However, issues such as uncontrolled Zinc (Zn) dendrite growth, surface corrosion, and hydrogen evolution at the Zn anode hinder their practical applications. In this study, a composite separator was developed by coating polypropylene (PP) separators with polyanionic covalent organic frameworks (COFs) nanosheets to stabilize the Zn anode. The prepared COF material, featuring unique nanopores and abundant anionic groups, exhibits ion-sieving properties that inhibit the migration of SO₄^2- ions while homogenizing the Zn²⁺ flux. This unique architecture induces a preferential orientation of Zn²⁺ deposition on the (002) plane. As a result, cells using the COF-PP separator achieved a high zinc-ion transference number (0.68) and high ionic conductivity (13.8 mS/cm). The Zn/Zn symmetric cell using COF-PP separators demonstrated cycling stability, exhibiting highly reversible plating/stripping behavior that exceeded 600 h at 1 mA/cm²/1 mAh/cm². Furthermore, when paired with a NaV₃O₈·1.5H₂O cathode, the full cell achieved an impressive initial capacity of 261.5 mAh/g while retaining remarkable stability over 900 cycles. This study provides a novel approach for the development of separators for aqueous batteries, enabling the realization of high-capacity, dendrite-free, and scaleable aqueous zinc-ion batteries.

Pre-lithiation technology can significantly enhance the initial coulombic efficiency and cycle life of batteries. Among the various prelithiation approaches, cathode lithium replenishment agent technology is one of the simplest and most effective methods. Li₂NiO₂ (LNO) is a widely used additive owing to its simple preparation process, low cost, and environmental friendliness. However, Li₂NiO₂ currently faces issues such as low specific capacity and poor environmental stability, which limit its wide application. To address these issues, the study prepared a lithium-rich nickelate GP-LNO with high environmental stability and specific capacity through vacuum sintering. For comparison, a lithium-rich nickelate NM-LNO sintered under atmospheric pressure using identical processes. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses revealed that GP-LNO exhibited superior particle integrity, higher crystallinity, and lower NiO impurity peaks. The results of potentiometric titration show that GP-LNO had better environmental stability, After 360 minutes in an environment with a temperature of 25 ℃ and humidity of 38%, the total Li content of GP-LNO increased by only 0.04%, compared to a 0.94% increase for NM-LNO under the same conditions. Electrochemical performance analysis revealed that GP-LNO achieved a higher first-cycle charge capacity. In the voltage range of 2.8—4.3 V, using constant current and constant voltage charging and discharging at a rate of 0.05 C, GP-LNO recorded a first-cycle capacity of 434.21 mAh/g, surpassing NM-LNO's capacity by 28.2 mAh/g. As the rate increased, the first-cycle charging capacity of GP-LNO first increased and then decreased. At a rate of 0.5 C, the first-cycle charge capacity of GP-LNO reached 438.64 mAh/g. This work significantly improved the first-cycle charge capacity and irreversible capacity of LNO material through vacuum sintering, by preventing Ni oxidation and impurity formation, and effectively enhanced the environmental stability of LNO, which provide valuable insights for advancing industrial application.

The rapid growth of industries like electric vehicles, mobile communications, and energy storage has led to a significant yearly increase in spent lithium batteries. These batteries contain high-value materials such as cobalt, lithium, and graphite, making their recycling essential for resource regeneration and environmental protection. Traditional recycling methods, including pyrometallurgical and hydrometallurgical processes, are effective but are often associated with high energy consumption, severe pollution, and lengthy recovery procedures. Magnetic separation technology offers a a green and efficient alternative for recycling, leveraging the physical property differences between materials to achieve separation. Frequently integrated with other recycling techniques, it shows great potential for recovering cathode and anode materials from spent lithium-ion batteries. This paper reviews the current applications of magnetic separation technology in battery recycling, highlighting the fundamental principles behind methods such as high-gradient magnetic separation, eddy current separation, and wet magnetic separation. It also examines how these technologies contribute to material separation and metal impurity removal. Challenges in scaling up magnetic separation technologies for industrial applications are also discussed, such as limitations in magnetic field strength, low levels of equipment integration, and limited adaptability to battery compositions. Finally, this paper provides insights into future development trends aimed at promoting green and closed-loop recycling of spent lithium-ion battery materials.

With the rapid development of energy storage industry, the market share of lithium batteries has gradually increased. Due to the limited service life of lithium batteries, a large number of waste lithium batteries have been generated. If these batteries cannot be properly treated, it will not only result in resource depletion, but also cause serious ecological contamination. Therefore, the recycling of waste lithium batteries has become the key. By analyzing the failure mechanism of waste lithium batteries, the paper finds the potential risks of waste lithium batteries, and reviews the recycling technology of positive electrode materials, negative electrode materials and electrolytes, so as to provide effective reference for the resource recovery of waste lithium batteries.

To effectively enhance the thermal storage performance of phase change thermal storage units, this study employs numerical simulation methods to analyze the melting performance and structural optimization of an eccentric three-tube phase change thermal storage unit filled with composite phase change materials (PCMs)/ metal foam. The study examines the effects of three key factors: eccentricity, the temperature difference between the heat transfer fluid and the phase transition temperature (ΔT),and the pore density of the metal foam on thermal energy storage performance. The results reveal that eccentricity plays a critical role in the thermal storage performance of the three-tube heat reservoir. The melting synergy between the top and bottom regions of the structure is optimal when the positive eccentricity is low. In addition, the melting rate of PCMs increases first and then decreases as eccentricity rises, with the optimal eccentricity determined to be 2/15. Under this condition, the complete melting time is shortened by 12.36% compared to a concentric tube structure. However, at eccentricities of H≤-1/15 or H≥4/15, the eccentric setting inhibits heat transfer compared to the concentric tube structure. Further findings indicate that increasing ΔT significantly improves thermal storage efficiency. The optimal ΔT for different eccentric structures is identified as 10 ℃. Reducing the pore density of the metal foam improves natural convection heat transfer within the pores during the PCM melting process. With ΔT=10 ℃ and an eccentricity of 2/15, reducing the pore density from 50 PPI to 30 PPI increases the melting rate by 4.52%.

With the rapid development of the cold chain logistics industry, the demand for efficient, energy-saving, and environmentally friendly refrigeration technologies is increasing day by day. Phase change energy storage materials (PCM), as a new type of refrigeration material, exhibit unique thermal effects in cold chain logistics transportation. This article provides a detailed analysis of the thermal effect mechanism of phase change energy storage materials in cold chain logistics transportation, including their roles in maintaining low-temperature environments, reducing energy consumption costs, improving refrigeration efficiency, and energy conservation and environmental protection. By combining theoretical exploration with practical application cases, this article aims to reveal the enormous potential and application value of phase change energy storage materials in cold chain logistics, providing scientific reference and inspiration for the industry.

To address the stator cooling challenges in the 500 kW flywheel energy storage motor, a spiral water jacket was installed on the outside of the stator. By simplifying the heat source and heat transfer model, an equivalent composite heat exchange model was established to optimize the liquid cooling design of the motor stator. Numerical simulations were conducted to validate the design, and the internal temperature distribution of the stator and friction resistance of the water jacket were calculated. When either the channel height or the channel width is fixed, increasing the other dimension increases the channel width or height, resulting in a reduced pressure drop and increased stator temperature. The optimized water channel dimensions establish critical operational limits, requiring the coolant flow rate and temperature to remain below certain values to meet the stator temperature requirements. Increasing the design temperature rise of the cooling water slightly decreased the maximum allowable inlet temperature of the cooling water. This simple and efficient design method provides a reference for the development of stator cooling systems for flywheel energy storage applications.

Compressed air energy storage (CAES) systems are recognized for their large-scale capacity and high efficiency, making them one of the most promising technologies for large-scale energy storage. Within a CAES system, the stability of the double-cantilever rotor in the integral gear compressor is a critical focus area. To address rotor vibration alarms caused by the unbalance of the suspended impellers at both ends of the rotor, the multibalance plane field dynamic balancing is usually employed. However, to simplify the balancing process and prolong the service life of double-cantilever rotors, this study investigates the unbalance characteristics and dynamic balancing methods of double-cantilever rotors in CAES systems. First, a model analysis of the double-cantilever rotor of the compressor was carried out using finite element analysis software. The research shows that unbalance at both ends of the double-cantilever rotor can be decoupled into single-end unbalances. This approach eliminates the need for complex dynamic balancing during production. Next, a field dynamic balancing experiment was performed, focusing on one end of the impeller. The study compared the effects of different test weights on the shafting's dynamic balance performance. Experimental results show that greater vibration amplitude and phase changes caused by the addition of test weights led to improved balance effects when determining counterweights. Finally, at the other end of the impeller, the original unbalance of the impeller was completely simulated based on real-world conditions. This validated the effectiveness and universality of the research method. The balance efficiency reached 84.01%.

Against the backdrop of global energy transition, the microgrid, as a flexible and effective integration solution for distributed renewable energy, is crucial for the sustainable development of energy systems. The microgrid can not only improve the flexibility and reliability of the power system, but also provide a practical way to achieve the goal of low-carbon economy. This paper aims to improve the economic efficiency, stability, and low-carbon characteristics of microgrid operation, focusing on the optimal double-layer configuration of a microgrid with electricity-hydrogen energy storage under multi-source coupling uncertainties. Specifically, based on analyzing the operation characteristics of various units in the microgrid, the study utilizes scenario generation and the improved K-means clustering algorithm to construct typical scenario sets for wind power, photovoltaic output, and power load to address uncertainty issues. Furthermore, considering the carbon trading mechanism, a double-layer optimization configuration model is proposed for the microgrid, with the objective of minimizing overall costs in the upper layer and minimizing total operation costs of the system in the lower layer. Finally, the double-layer optimization model is solved by combining an improved shearwater algorithm and mixed-integer linear programming method, and then the optimal capacity configuration of the microgrid is determined. The effectiveness and superiority of the proposed method are verified by an example analysis based on annual meteorological and load data in a certain area of central China.

This study investigates an inertial flywheel system based on electromagnetic couplers. The topological structure and principle of the inertial flywheel system are first introduced, and the advantages of using electromagnetic couplers are highlighted, followed by mathematical modeling of the system. The traditional fixed-parameter proportional-integral-derivative (PID) control mode exhibits significant output power fluctuations during sudden active command changes. To address this limitation, this study proposes a variable-parameter PID active power control strategy for inertial flywheels based on reinforcement learning (RL). The proposed method uses an RL algorithm without a model reference to train the neural network RL Agent, which dynamically adjusts the PID parameters. The neural network processes four input variables: active power deviation, differentiation of the active power, rotational speed, and acceleration, while outputting optimized parameters P, I, and D. The PID parameters dynamically adapt to the changes in the system state. To verify the feasibility of the control strategy and the advantages of the control performance, the control strategy was compared with the traditional fixed-parameter PID control method on the MATLAB/Simulink simulation platform. The simulation results demonstrate that the P and I parameters in the variable-parameter PID control strategy significantly change when the system receives an active power adjustment instruction, resulting in corresponding adjustments in the output torque reference values. As a result, the overshoot and fluctuation of the system power output are reduced, and the dynamic response performance is improved.

To address the performance degradation of air source heat pumps in low-temperature environments, this paper proposes an air source heat pump system featuring quasi-two-stage compression coupled with an energy storage device. The energy storage device is a phase change heat accumulator that uses phase change materials to absorb or release large amounts of latent heat during the phase change process. This allows for efficient heat storage within a relatively stable temperature range. Key parameters, including heating capacity, coefficient of performance (COP), refrigerant mass flow, exhaust temperature, and system energy efficiency at different ambient temperatures, were experimentally tested. The economic performance of the system was also analyzed. Experimental results revealed that with decreasing ambient temperature, both the refrigerant mass flow rate and heat production significantly reduced. However, when compared to conventional systems with economizers, the proposed quasi-two-stage compression and energy storage coupling system demonstrated superior performance in terms of COP, heat generation, even in harsh ambient temperatures. At an ambient temperature of -30 ℃, the COP, heat generation, and the exergic efficiency of the coupled system increased significantly by 39.9%, 43.46%, and 41.8%, respectively. The daily operating costs were reduced by 4.63 yuan, including an 11% reduction under cold weather conditions, showcasing the system's economic feasibility and strong market competitiveness. In addition, in the ambient temperature range of -5 ℃ to -30 ℃, the exhaust temperature was lowered by 4.55—12.78 ℃, while the refrigerant mass flow rate increased by 11.8%—48.7%.

Establishing accurate electromagnetic transient simulation models for energy storage units in power stations is critical for effectively regulating and operating renewable energy and energy storage facilities. It is also a key strategy for enhancing renewable energy utilization and ensuring the safe operation of power grids. Currently, most electromagnetic transient modeling for energy storage systems relies on foreign simulation platforms, with limited analysis or accuracy verification based on the localized Advanced Digital Power System Simulator (ADPSS) electromagnetic simulation platform. Using a specific energy storage power station as an example, this paper employs the ADPSS platform to develop an electromagnetic transient simulation model for the energy storage power plant. Through hardware-in-the-loop (HIL) testing of the energy storage system's real controller, a simulation model is constructed that accurately reflects the steady-state and transient operational characteristics of the actual energy storage system. Comparative analyses are conducted between results from real single turbine tests and those of the ADPSS-HIL encapsulated model under different operational conditions. The study evaluates transient characteristics such as low voltage ride-through (LVRT) and high voltage ride-through (HVRT) performance. By adjusting the parameters of the ADPSS-HIL encapsulated model, the wave ADPSS-HIL encapsulation model shape data and turbine test error are adjusted to comply with relevant standards, resulting in the establishment of an accurate electromagnetic transient-based model. The proposed electromagnetic transient simulation model for the energy storage unit improves the accuracy of grid simulation calculations and ensures that results can effectively guide production operations.

With the rapid development and widespread application of new energy technologies, the role of energy storage systems in the power grid has become increasingly important. Traditional energy storage system operation and maintenance usually relies on manual experience, which has problems such as low efficiency, delayed response, and inaccurate fault diagnosis. This paper proposes an intelligent operation and maintenance model for energy storage systems based on big data. This model integrates multiple data sources for information collection and monitoring to achieve real-time collection and in-depth analysis of massive data. Combining machine learning and deep learning algorithms to conduct fusion analysis of real-time data and historical data, the system can identify fault patterns and patterns, and then predict equipment performance and health status. Through this intelligent operation and maintenance model, potential faults can be effectively predicted and intervention measures taken in advance, thereby improving equipment reliability and operating efficiency.

The flywheel energy storage system (FESS) is becoming increasingly important in power grid frequency regulation owing to its fast response speed, high energy conversion efficiency, high energy density, long service life, and eco-friendly properties. At present, the power and energy output of a single flywheel are insufficient to fully support frequency fluctuations in the power grid. To compensate, it is necessary to combine multiple flywheels in parallel, forming an array for frequency modulation response. This study addresses two critical challenges in FESS operation during grid connection: uneven energy distribution among flywheel units and poor bus voltage stability in grid-integrated control systems. To resolve these issues, a power allocation method for the flywheel array and a coordinated control strategy for flywheel units are proposed. These strategies ensure consistent operation across all flywheel units while adhering to the power and capacity limits of the FESS. The proposed approach includes a DC bus voltage outer loop control strategy based on linear active disturbance rejection control and a current inner loop control strategy using model predictive control. Model development on both the motor and grid sides of the FESS is conducted to analyze the system's overall control performance. Simulation results confirm the effectiveness of the proposed energy management and control strategies for grid-connected FESS operations.

Hydrogen energy storage plays a crucial role in balancing the load of renewable energy sources. Owing to the intermittent and volatile nature of wind and solar energy, combined with the variability in hydrogen storage, salt cavern hydrogen storage usually covers a wide range of injection and production frequencies. These cycles can span weeks, months, quarters, or even years. This is a unique feature of hydrogen storage in salt caverns. However, the impact of varying frequencies on the tightness of salt cavern storage remains unclear and requires further investigation. This study aims to evaluate the effects of injection and production frequency, internal pressure of hydrogen storage, and burial depth on the tightness of salt caverns under high-frequency operational conditions. To achieve this, a two-cavity three-dimensional model of a salt cavern was established and simulated using FLAC3D.The key outputs include the hydrogen seepage range, interlayer pore pressure variation, and cumulated hydrogen leakage rate after 30 years of operation under various conditions. Based on this, the influence of various factors on the tightness of salt cavern is analyzed. The results show that the cumulative leakage of hydrogen increases as injection and production frequency rise. As the injection and production frequency increase, the interlayer pore pressure near the salt cavern area near the salt cavern decreases, while the interlayer pore pressure farther from the salt cavern rises. At the same frequency, hydrogen leakage rates also increase with greater burial depths. Furthermore, higher injection and production frequencies result in a lower minimum operating pressure for the salt cavern, which leads to increased hydrogen leakage. Interlayer permeability significantly impacts the air tightness of the salt cavern, with interlayer hydrogen leakage accounting for more than 90% of the total leakage. When salt cavern is used for hydrogen storage, the interlayer permeability should be less than 1.0×10^-18 m².

In recent years, with the increasing popularity of distributed generation technology in the power network, its high penetration rate has posed significant challenges to the stable operation of the power system. As one of the key technologies to address the challenges of distributed energy grid connection, virtual synchronous machine (VSG) control technology has received deep attention from both academia and industry. VSG accurately simulates the core operating mechanism of traditional synchronous generators, including electromagnetic dynamics, mechanical motion characteristics, and frequency and voltage regulation mechanisms, endowing distributed generation units with a "behavior pattern" similar to traditional generators, thereby effectively improving their compatibility and stability in the power grid. This technological innovation not only provides technical support for the widespread access of distributed energy, but also opens up new paths for the safe and efficient operation of the power system. In order to provide the inertia and frequency modulation capabilities required by VSG, it is usually necessary to add energy storage units. In this regard, this study focuses on the research review of VSG control strategy based on energy storage state of charge. Based on the analysis of the current basic control model, it further demonstrates the application of several latest control strategies, including grid connected energy storage SOC control of VSG, SOC coordinated control of VSG and diesel generator networking system, and SOC balance control of multi VSG parallel system.

To address the low round-trip efficiency of traditional Carnot battery systems, this study proposes a dual-pressure condensation/evaporation Carnot battery (DCB) system. This innovative system integrates dual-pressure evaporation organic Rankine cycle (DORC) and dual-pressure condensation heat pump (DHP) technologies, effectively reducing irreversible losses in the heat exchange process of the CB system. System modeling and analysis were conducted to evaluate the operating characteristics of the DCB system under varying conditions, exploring its feasibility. The results show that the energy efficiency coefficient of DHP and the power generation efficiency of the DORC module increase first and then decline as intermediate water temperature rises. Across varying heat sources and ambient temperatures, the round-trip efficiency of the DCB system is higher than that of the CB system. Taking Harbin, Nanjing, and Guangzhou as examples shows distinct benefits of the DCB. Harbin displayed the greatest improvement in annual round-trip efficiency, reaching 70.5%, while Guangzhou achieved the highest operational revenue. Under daily power generation conditions of 100 kWh, the annual revenue of the DCB system increases by 18077 RMB compared to the CB system. The proposed DCB system effectively addresses the low round-trip efficiency of CB systems and holds significant potential for balancing grid loads and promoting efficient utilization of renewable energy. It also offers a more efficient solution for renewable energy storage under the dual carbon strategy.

In weak-export grids with a high proportion of clean energy, the lack of sufficient outbound transmission capacity and limited flexible, adjustable resources significantly exacerbates the curtailment of wind and solar power during peak renewable generation periods. Additionally, the high penetration of clean energy further reduces the operating range of traditional synchronous generators, weakening grid regulation capabilities and increasing the risks to load supply reliability. These conditions intensify the interconnected challenges of renewable energy curtailment and load power shortages, making the conflict more complex and severe. Electrochemical energy storage emerges as a key solution for smoothing renewable energy fluctuations and addressing supply-demand imbalances. It plays a critical role in ensuring the safe, stable, and flexible operation of power grids. This paper proposes an optimized energy storage configuration and operational strategy designed to balance both load supply reliability with renewable energy utilization. First, this study focuses on clean energy systems with high renewable penetration, identifying two critical requirements: ensuring reliable load supply and maximizing renewable energy utilization. Based on these objectives, three risk assessment indices are established to evaluate grid balance, clean energy utilization, and load supply reliability. Second, leveraging the proposed risk assessment framework, objective functions, and constraints are formulated to address both load supply reliability and renewable energy utilization. A bilevel optimization model is developed. The upper-level model determines the energy storage planning and configuration, while the lower-level model optimizes the operational strategy of the energy storage system. This approach integrates the dual objectives of ensuring supply reliability and promoting renewable energy utilization. Finally, the feasibility and effectiveness of the proposed strategy are validated through four case studies conducted on a high-proportion clean energy grid in Western China. Results show that compared to strategies focusing solely on renewable energy accommodation or power supply assurance, the proposed strategy significantly improves both power supply reliability and renewable energy utilization rates. Additionally, it effectively reduces operational costs and enhances the economic efficiency of the power grid.

In multi-energy systems, the complexity of interconnections and the profound impact of system dynamics and uncertainties often lead to conflicts and trade-offs between components. These challenges make it difficult to maintain a dynamic balance between energy supply and demand. To address this challenge, a coupled optimization and control method for source network load storage multi-energy networks based on integrated neural networks is proposed. In addition, the proposed method considers the carbon emissions of multiple links in multi-energy systems, including source, grid, load, and storage, enabling comprehensive and accurate emission assessment. By combining a bidirectional weighted gated recurrent unit neural network with the Bagging ensemble algorithm, an ensemble neural network model can be constructed to capture contextual information about the time series data. By combining multiple weak learners, the proposed model significantly reduced the prediction error, achieving accurate carbon emission predictions in multi-energy networks. The regulation process focuses on three core optimization objectives: minimizing carbon emissions, and power generation costs, and maximizing the consumption of new energy. To address these challenges in complex multi-energy systems, the NSGA-II algorithm was applied to achieve comprehensive optimization regulation. The experimental results demonstrate that the proposed method accurately predicts carbon emissions. Furthermore, a regulation test demonstrated that the proposed method significantly improved the energy utilization efficiency, optimized the energy consumption, and enhanced the unit output stability. This research achievement is of great significance for sustainable development and efficient operation of multi-energy systems.

As power systems are increasingly adopting renewable energy sources, the power quality and stability of microgrids are impacted by the volatility of photovoltaic (PV) power generation. To address this issue, a power optimization management method for PV microgrids based on the state of charge (SOC) of hybrid energy storage systems is proposed herein. It dynamically allocates power between the PV system, energy storage system, and microgrid by monitoring the SOC of the supercapacitor and battery. The supercapacitor handles transient power regulation to respond to sudden load changes, thereby reducing the instantaneous response stress on the battery and extending its lifespan. The battery primarily manages average power regulation and ensures sustained system stability. Simulation results show that when the PV irradiance suddenly decreases from 1000 to 600 W/m², the DC bus voltage is restored to 100 V within 0.15 s and the voltage overshoot is controlled within 1%. The total harmonic distortion (THD) of the grid current is reduced to 1.11%, meeting IEEE 519 standards. The system frequency deviation is controlled within ±0.01 Hz under varying loads, meeting the voltage and frequency stability requirements of IEEE 929. The results demonstrate that the proposed method considerably enhances the power quality and stability of PV microgrids.

Energy storage technology plays an extremely important role in modern agricultural e-commerce cold chain logistics transportation. This article mainly summarizes the research progress of phase change energy storage technology, including the latest research on energy storage materials. Based on the research, it can be found that the core materials of phase change energy storage technology currently include aqueous phase change energy storage materials and functionally enhanced energy storage materials. Different types of materials have their own advantages and limitations, and need to be flexibly selected according to the situation. In addition, the article proposes some optimization solutions for existing energy storage technologies and agricultural e-commerce distribution strategies, including strengthening energy storage technologies, establishing logistics networks, optimizing cold chain logistics resource allocation, and enhancing cold chain logistics talent training. It has been proven that cold chain logistics is an important guarantee for the transportation and distribution of agricultural products, and plays a significant role in the sales of agricultural products in China. In the future, we should continue to deepen our requirements, improve logistics efficiency, and reduce logistics costs.

The State of Health (SOH) of electric vehicle (EV) power batteries is a critical factor in ensuring efficient operation and extending service life. However, accurately assessing SOH is challenging owing to the complex and variable charging patterns in real-world EV usage, large sampling intervals in individual charge-discharge cycles, and missing feature data. To address these challenges, this study proposes a multisource feature fusion method for SOH estimation method using real-world vehicle operation data. The proposed method utilizes the soft dynamic time warping (Soft-DTW) algorithm to dynamically fuse parameters from weekly charging segment incremental capacity (IC) curves, generating an overall weekly IC fusion feature. By integrating these fused IC curve features with statistical features, a multisource feature set is constructed. Furthermore, a real-world SOH estimation model based on the Bidirectional Gated Recurrent Unit-eXtreme Gradient Boosting (BiGRU-XGBoost) is proposed. The model was tested using a real-world dataset comprising 20 EVs. K-fold cross-validation results demonstrates that the proposed SOH estimation method achieves a root mean square error (RMSE) within 1.21% and a mean absolute error (MAE) below 0.9%. Comparative experiments with GRU-XGBoost and long short-term memory (LSTM) models further validate the superiority of the BiGRU-XGBoost model, showing 36.1% and 47.6% reductions in RMSE. These findings highlight the enhanced robustness and generalization capabilities of the BiGRU-XGBoost model.

This study examines mechanical abuse-induced thermal runaway in on-board lithium batteries and evaluates the effects of water mist on the suppression of electric vehicle (EV) fires under different working conditions. We constructed an EV fire model using Fire Dynamics Simulation Software to simulate full-vehicle combustion dynamics and assess the fire suppression strategies. Through numerical simulations, we investigated the development law of EV fire, determined the optimal working conditions for water mist, and analyzed the effect on the interior temperature suppression of the vehicle under optimal conditions. The results reveal that in the absence of any preventive and control measures, EV fires spread rapidly and on a significant scale, with a peak heat release rate (PHRR) of 5740 kW, generating high temperatures, smoke, and flames that pose a serious threat to occupant safety. The smoke generation time lag relative to the flame and heat release rate (HRR) was also determined. Through systematic evaluation of the mitigation effect and delay time of the fine water mist system under different working conditions, this study determined that a fine water mist injection flow rate of 5 L/min and a droplet diameter of 500 μm are optimal working conditions. Under this optimal condition, the delay time of the PHRR was extended by 16.5 s, and the mitigation rate of the PHRR reached 23.69% compared to scenarios without fire prevention and control measures. The comparative analysis of the changes in the interior temperature of the EV fires with no fine-mist system and under the optimal fine-mist condition revealed that the system not only significantly reduced the interior temperature but also delayed the temperature rise time, thus significantly improving safety. This study provides an in-depth discussion of the effects of fine water mist on EV fires under different operating conditions, offering valuable scientific guidance for EV fire prevention and control, enhancing the safety performance of EV fires, and reducing the potential damage of fires to people and property.

Accurately measuring the voltage of lithium-ion batteries is crucial for improving the reliability of battery state management. Traditional Kalman filter algorithms face limitations, as the Kalman gain does not account for sudden innovation changes, and the state variable estimation process ignores valuable historical data. This leads to unsatisfactory results in the estimation of sampled voltage filtering based on the traditional Kalman algorithm. Therefore, a sampling voltage estimation method based on an improved Kalman filter algorithm incorporating multi-innovation theory has been proposed. This approach extends the single-moment innovation to a multivariate innovation matrix, incorporating information from both current and historical observations. During the system error covariance calculation, the multivariate innovation matrix of current and past observation moments is introduced. For prior estimation corrections, historical state variables, Kalman gains, and the observation moment innovation matrix are added into the process. These improvements refine the traditional algorithm's error covariance and estimation correction procedures, enabling the Kalman gain and state variable estimates to adapt dynamically to changes in innovation. At the same time, a correction factor is introduced to adjust the correction weight of data at different moments. The improved Kalman filter algorithm based on multi-innovation theory is constructed, resolving key limitations of the traditional method by accounting for sudden innovation changes and incorporating historical data. A comparative analysis was performed between the sampled voltage estimated by the improved algorithm and the traditional algorithm. Furthermore, the relationship between voltage and state of charge (SOC) is utilized to calculate the battery SOC. The results show that under constant current discharge conditions, the maximum error of battery sampled voltage decreases from 8.09 mV to 3.71 mV. Moreover, the SOC error calculated using the sampled voltage is significantly reduced. The improved method reduces the average error and root mean square error (RMSE) for sampled voltage and SOC. These results validate the effectiveness of the improved Kalman filter algorithm and provide new ideas for improving the accuracy of battery sampled voltage filtering estimation and SOC calculation.

As the core of power resource application and development, energy storage systems are constantly becoming more complex and precise. How to improve the accuracy of energy storage system fault detection and diagnosis has become the key to the development of modern power technology. The article provides a detailed overview of new energy storage system fault prediction methods based on big data and artificial intelligence technology, based on common faults in modern energy storage systems. Through analysis and research, it can be clarified that the current fault prediction and diagnosis methods for energy storage systems mainly include data model diagnosis and data-driven diagnosis. The former constructs data models through big data technology, determines problem data, and obtains diagnostic results, while the latter relies more on artificial intelligence technologies such as machine learning to obtain diagnostic results through knowledge driven and data-driven approaches. Future research tends to focus more on mining and summarizing physical quantity data, establishing more accurate comparative models, and achieving rapid diagnosis of energy storage system faults.

Energy storage systems and thermal power plants working together to handle frequency regulation in power systems are increasingly becoming standard practice in modern grid operations. Optimizing the coordinated use of thermal power and energy storage resources for frequency regulation is crucial for ensuring the safe and cost-effective operation of modern power systems. This paper proposes a method for allocating frequency regulation reserve capacities between thermal power plants and energy storage systems using marginal rate of substitution (MRS) analysis. First, a frequency response model is established a power system where thermal power and energy storage collaboratively perform frequency regulation. Using the root mean square error of the area control error (ACE) as an evaluation index for frequency regulation, an allocation method is developed based on MRS analysis. This method evaluates the frequency regulation reserves of thermal power and energy storage, leveraging the Gaussian process regression algorithm to reduce computational complexity during configuration. A multisegment fitting approach is used to generate the marginal substitution curve, capturing the effectiveness of thermal-storage frequency regulation. Furthermore, the method considers the different prices of frequency regulation reserves for thermal power and energy storage. It optimizes the allocation of these reserve capacities with the objective of minimizing overall costs. The proposed method is validated through a real-world case study examining daily load fluctuations.

To address the low utilization rate of waste heat from low-temperature flue gas in the steel industry, this study proposed a coupling system combining a heat pump and an organic Rankine cycle (HP-ORC) for low-temperature waste heat recovery. Thermal and economic models of the proposed HP-ORC system were established. R601a was selected as the circulating working medium for the heat pump (HP), while R1233zd(E), R600a, R1336mzz(Z), and R1224yd(Z) were selected as working mediums for the ORC. The study investigated how HP condensation temperature, heat storage temperature, and ORC evaporation temperature affect the thermal and economic performance of the HP-ORC system under various ORC working mediums. Results showed that decreasing the HP condensation temperature and increasing both heat storage temperature and ORC evaporation temperature improved the power-to-power efficiency (η_P2P) and exergy efficiency (η_ex) of the system. However, the total heat transfer capacity per unit temperature (Q_UA) of the HP-ORC system first decreased and then increased as the HP condensation and heat storage temperatures rose. Furthermore, the Q_UA of HP-ORC system increased nonlinearly with higher ORC evaporation temperatures. Using R1233zd(E) as an example, the study found that when the HP condensation temperature increased by 2 ℃, η_P2P and η_ex of decreased by an average of 1.54% and 0.58%, respectively. Conversely, when the HP condensation temperature rose by 2 ℃, η_P2P and η_ex increased by an average of 0.4% and 0.15%, respectively. When the ORC evaporation temperature rose 2 ℃, η_P2P and η_ex increased by an average of 0.93% and 0.64%, respectively. For the fixed the thermal parameters of HP-ORC system, the working medium with R1233zd(E) exhibited the largest η_P2P and η_ex in the ORC subsystem. However, its economic performance was relatively poor, demonstrating that the working medium with the best thermal performance may not necessarily offer optimal economic performance. During actual operation, selecting appropriate thermal parameters and a suitable working medium enables the HP-ORC system to achieve higher η_P2P and η_ex and smaller Q_UA.

As China advances its "dual carbon" strategy and transitions toward a cleaner energy structure, energy storage technology has become increasingly important for supporting the development of new productive forces. To meet this growing demand, universities must prioritize the cultivation of highly trained energy storage professionals. Energy storage science and engineering is an interdisciplinary field that involves materials science, energy and power engineering, physics, chemistry, and electrical engineering, and it places higher demands on traditional teaching models and methods in universities. This study reviews the characteristics and development status of energy storage science and engineering disciplines. Taking the Energy storage science and engineering program at the School of Energy and Power Engineering, Chongqing University as a case study, this study highlights the importance of guiding interdisciplinary literacy during the training of students at the undergraduate, masters, and doctoral levels. In addition, it analyzes the main challenges facing the program, such as the lack of knowledge structures, outdated teaching methods, and lagging training models. Based on the professional requirements for cultivating high-quality interdisciplinary talent, this study proposes new ideas for creating a multidisciplinary curriculum system and cutting-edge interdisciplinary research topics to guide training during undergraduate, master's, and doctoral stages. Finally, this study emphasizes the steps for implementing cutting-edge interdisciplinary research and related outcomes through specific case studies, underscoring the significant role of interdisciplinary training in advancing the development of energy storage science and engineering programs.