Sodium-ion batteries have promising potential in large-scale electric storage applications due to their low cost, environmental friendliness, and similar working principles to lithium-ion batteries. O3-type layered oxides are used as a cathode material that determines the energy density of SIBs and stand out from other cathodes due to their high capacity and ease of synthesis. However, the migration of Na⁺ between octahedral positions in the O3 phase must overcome a large energy barrier, which results in complex reaction phase transitions and rapid capacity decay. Therefore, the Na⁺ de-intercalation behavior and the structural evolution of O3-type structure should be explored before developing high-performance cathodes. Herein, we systematically investigated the electrochemical properties, Na⁺ transport kinetics, and phase transition mechanism of O3-NaNi_0.4Fe_0.2Mn_0.4O₂ (O3-NFM). The O3-NFM cathode delivered a capacity about 201.9 mAh/g (corresponding to 0.84 mol of Na⁺ extraction) when charged to 4.3 V. After the cut-off voltage is set to 4.0 V, O3-NFM can achieve a stable reversible cycle. The improved cycling performance between 2.0 V and 4.0 V can be ascribed to the reversible transformation of O3-P3/O3-P3-P3/O3-O3 structural evolution, as determined by in situ X-ray diffraction. A fast kinetics of the Na⁺ diffusion in the O3 structure was revealed by cyclic voltammetry and galvanostatic intermittent titration technique techniques, which contributes to a good rate performance. This work provides a theoretical basis for investigating the structure modification and material design based on O3-NFM cathodes.

In this study, the effects of different contents of hexachlorocyclotriphosphazene (HCCP) on flame retardancy and electrochemical performance of sulfur cathode for lithium-sulfur batteries were examined. Combustion experiments show that the addition of HCCP resulted in excellent flame retardancy of the sulfur-positive electrode. In addition, the surface morphology, chemical composition and electrochemical properties of sulfur with and without HCCP were compared using scanning electron microscopy, X-ray diffraction and electrochemical performance testing techniques. The results showed that the sulfur-positive electrode exhibited the best cycling performance and Cullen efficiency when 10% HCCP was added to it. At the current density of 0.2 C, the discharge specific capacity of the lithium-sulfur battery with 10% HCCP added to the sulfur-positive electrode remained at 975.2 mAh/g after 100 cycle; this was better than lithium-sulfur battery without HCCP in the sulfur-positive electrode. In addition, the sulfur cathode material added with HCCP was uniformly dispersed, and even after 100 cycles, no obvious cracks and no obvious increase in impedance were observed. Moreover, the presence of HCCP helped the cathode material to anchor lithium polysulfide, an intermediate product of charge and discharge. This inhibited the shuttling of lithium polysulfide through the reaction experiments of HCCP and lithium polysulfide and improved the electrochemical performance of lithium-sulfur batteries. Thus, the findings of our study can help improve the electrochemical properties of flame-retardant lithium-sulfur cathode materials.

With the rapid development of portable electronic devices, new energy electric vehicles, and energy storage grids, the demand for developing economical and efficient electrochemical energy storage (EES) systems has increased. Lithium-sulfur batteries have become one of the most widely used EES system because of their low cost, wide range of materials, high efficiency, light weight, and zero sulfur pollution. However, their commercialization process has been seriously restricted due to the low utilization rate of positive sulfur, the growth of lithium dendrites, volume expansion, and the shuttle effect of long chain polysulfide. Therefore, there is a need for new sulfur host materials. This paper is devoted to the development of coal-based graphene oxide (GO) composites to solve the above problems. Herein, a coal-based GO containing oxygen functional group is designed to capture the spatial limit or physical range of polysulfide and used to assemble a complete button lithium-sulfur battery. After 500 long cycles at a high rate of 3 C, the specific capacity changes from the initial 622.5 mAh/g to 448.2 mAh/g, the specific capacity retention rate is 72%, and the specific capacity decay rate is 0.056%. Our findings show that coal-based GO containing rich functional groups can provide more abundant polar sites for the intermediate lithium polysulfide, showing higher sulfur affinity to a certain extent. After a series of electrochemical characterizations to prove the advantages of this material in lithium sulfur batteries, to provide reference and methods for the further development of lithium sulfur batteries.

Supercapacitors are a new type of energy storage device that have great development prospects owing to their higher power density, rapid charging and discharging, long cycle life, and other advantages. Research on electrode materials can lead to the development of supercapacitors, in which the microstructure of materials largely determines their electrochemical performance. In this study, NiMoO₄/NiCo₂S₄ composite was prepared using hydrothermal method and heat treatment and then applied to supercapacitor electrodes. The composition and microstructure of nanocomposites were characterized by X-ray diffraction, energy dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy, and N₂ adsorption and desorption. The prepared product shows excellent electrochemical performance: the specific capacitance was 847.2 F/g (higher than 576.1 F/g of NiMoO₄ electrode and 734.3 F/g of NiCo₂S₄ electrode) at a current density of 1 A/g, and 466.7 F/g at a high current density of 10 A/g. When NiMoO₄/NiCo₂S₄ composite material was used as the positive electrode and the active carbon as the negative electrode to form an asymmetric supercapacitor, the device retained 76% of the initial capacitance after 2000 cycles at a current density of 1 A/g, proving its excellent cycle stability. Thus, the present work can provide a reference for the development of NiMoO₄ as an electrode material for supercapacitors and serve as an experimental basis for the research of electrode materials with high specific capacitance and high cycle stability.

In this study, high ionic conductivity monomers and initiators were introduced into the silicon anode electrode electrolyte by taking advantage of the spontaneous polymerization of polymer monomers and initiators under heating. The in situ solidified silicon anode electrode cell was prepared by thermal polymerization after liquid injection. The cycle and rate properties of the cell were tested using charging and discharging equipment. The morphology and electrochemical properties of the silicon anode electrode were characterized using scanning electron microscopy, X-ray diffraction spectrometer, and electrochemical workstation and mercury porosimeter. The results show that the number of cycles of the solidified cell at room temperature of 0.5 C is 349 cycles, which is 51.74% higher than that of the liquid cell at 230 cycles. The swelling rate of the silicon anode electrode after solidification is 4.6% lower than that of the liquid cell, and the porosity of the electrode is 3.8% lower than that of the liquid cell. The EIS and DCIR growths after cycling are reduced, and the performance of the cell is significantly better than that of the liquid core. The electrode sheet characterization results show that solidification can improve the interface of the silicon anode electrode plate, form a layer of polymer electrolyte on the surface of the silicon anode electrode and in the hole of the electrode plate, prevent the silicon anode electrode plate from swelling, powdering and falling off when lithium is embedded, and stabilize the ion and electronic conductive network of the electrode plate. This research promotes the application of silicon anodes and provide an experimental basis for the research and development of battery technology involving high energy density.

In this study, a gel-like silica/carbon precursor was obtained by the hydrothermal method, with PEO-PPO-PEO(P123) as the structure directing agent, tetraethyl orthosilicate (TEOS) as the silicon source, and citric acid as the carbon source. The solvent was removed by rotary evaporation. The rod-like carbon-coated silicon oxide-negative material was obtained through high-temperature heat treatment, which improved the performance of the silicon-carbon material in the slurry system without a tight binding environment. The structure and morphology of this material were characterized by X-ray diffraction, inorganic element analyzer, specific surface area and porosity analyzer, and scanning electron microscope. The rod-like silicon-based material was joined end to end to form a lotus chain bundle having a length of about 1～3 μm, diameter of about 200 nm, pore size of 6.9 nm, and specific surface area of 282 m2/g This material and a single-walled carbon nanotube conductive agent with tube length >5 μm, specific surface area of 900 m²/g, and diameter of 1～2 nm form a multistage network of long and short range complementary in the electrolyte system. In addition, the presence of a large number of mesoporous materials was conducive to maintaining the suspension stability of slurry. The electrochemical performance test of the Swagelok battery showed that the initial discharge capacity was 1300 mAh/g, charging capacity was 726 mAh/g, and the coulombic efficiency was 55.8%. At 0.05 C, the charging capacity changed from 726 mAh/g to 557 mAh/g after 50 cycles, and the specific capacity retention rate was 76.7%. This work directly introduced carbon sources in the process of preparing silica with P123 as the structure guide agent and obtained silica-based materials with both carbon coating and carbon-reducing silica at the same time. Thus, this process avoided the complex technological process caused by magnesium thermal reduction of silica and recarbon coating.

In this study, a capacity calibration method at low current was introduced during cycling to eliminate the influence of polarization voltage and to better understand the degradation mechanisms of the composites containing silicon oxide and graphite. The electrochemical characteristics of the cathode and the anode at different cycles were compared by pre-embedding a reference electrode in the pouch battery. The evolution process and attenuation degree of silicon oxide and graphite were analyzed using the negative differential curves. In addition, AC impedance spectroscopy, scanning electron microscopy, energy dispersive spectroscopy, and plasma emission spectroscopy were discussed. The results demonstrate that capacity attenuation was caused due to the loss of active lithium and the decay of silicon oxide, and the resultant capacity loss was 0.45 Ah and 0.36 Ah, respectively. Moreover, the degradation rate of the anode was found to be faster than that of the cathode, while the attenuation of the graphite and the silicon oxide in the negative electrode was 2.2% and 30.3%, respectively, after 600 cycles. During cycling, a new interface impedance was generated, and all kinetic impedance parameters increased gradually. Serious volume expansion and side reactions occurred in the aged anode on disassembling the cycled battery, leading to lithium inactivation in the anode, thickening of the solid electrolyte interphase layer, and capacity degradation. The quantitative evaluation of the decay degree of silicon oxide and graphite during cycling is helpful for engineering applications of silicon-graphite composite electrode.

As a lithium-ion battery anode material, the Fe₃O₄ exhibits varying volume during charging and discharging, which results in serious capacity degradation. This problem can be solved using carbon coating. Thus, in this paper, three-dimensional graphene-coated Fe₃O₄ nanoparticle(3DG@Fe₃O₄) composites were synthesized by one-step hydrothermal method using graphene oxide (GO) and Fe²⁺ as raw materials. The composites were characterized by a Fourier transform infrared spectrometer, thermal gravimetric analyzer, X-ray diffractometer, Raman spectrometer and scanning electron microscopy. The results showed that the composites have a "sandwich" structure of graphene (G)-coated Fe₃O₄ nanoparticles. Meanwhile, electrochemical tests, including galvanostatic cycling with potential limitation, cyclic voltammetry, and alternating current impedance were used to investigate the influence of Fe₃O₄ content on the lithium-ion storage performance of 3DG@Fe₃O₄ composites. The 3DG@Fe₃O{}_{\mathrm{4}}^{}-2 electrode with about 83.2% Fe₃O₄ exhibited enhanced specific capacity and better cycle stability. It also delivered a high discharge specific capacity of 1412.33 mAh/g at a current density of 0.1 A/g and 577 mAh/g after 100 cycles, and this value was 6.5 times that of pure Fe₃O₄ electrode material after 100 cycles. The composites prepared by this method have simple synthesis and do not require additional reducing agent. The prepared composites have high capacity and good cycle stability compared with pure Fe₃O₄ nanoparticles, and this can promote the application of Fe₃O₄-based anode materials in the field of energy storage.

The urgent need for large-scale, low-cost, and long-term electric energy storage has again aroused people's interest in the research and development of iron-chromium redox flow battery (ICRFB). The efficiency of the ICRFB system can be improved and the operating cost can be reduced by inhibiting the hydrogen evolution side reaction and improving the electrochemical reaction activity of the negative electrode. The deposition of bismuth catalyst is an effective method to improve the performance of the negative electrode. However, there is a lack of systematic understanding and in-depth research on uniform bismuth deposition strategy and the impact of bismuth loading on battery performance. Thus, this paper proposes a slow-release deposition strategy that is realized by dissolving bismuth ions in the positive electrolyte in order to improve the uniformity of catalyst deposition. The ions gradually migrate across the membrane and are deposited on the negative electrode. The effect of deposition rate and loading of bismuth on the performance of an ICRFB was explored by varying the concentration of BiCl₃ in the positive electrolyte. Our results show that the continuous deposition of bismuth significantly and continuously improved due to the coulombic efficiency of the ICRFB because of the accompanied reduction in hydrogen evolution. In addition, the in situ deposition of bismuth also helps to improve the voltage efficiency of the ICRFB, indicating an enhanced reaction activity of Cr²⁺/Cr³⁺. With an initial 10 mmol/L Bi³⁺ in the positive electrolyte, the coulombic, voltage, and energy efficiency reach about 97%, 90%, and 87%, respectively.

Incorporating inorganic fillers into polyethylene oxide (PEO)-based solid polymer electrolytes is a low-cost and effective method to improve their mechanical and electrochemical properties. The solid electrolyte composite of zeolite imidazole skeleton material (ZIF-8) and PEO was prepared using flow-casting method to effectively improve the electrochemical performance of the PEO solid electrolyte. Physical characterizations of scanning electron microscopy, X-ray diffraction, and electrochemical measurement methods, such as electrochemical impedance spectroscopy, linear sweep voltammetry, and charge-discharge cycle, proved that the PEO-based composite solid electrolyte CPE20 with 20%ZIF-8 nanoparticles had the lowest resistance, a broader electrochemical stability window, and an activation energy of 8.4×10^-3 eV. At 20 ℃, the conductivity of CPE20 reached 4.9×10^-5 S/cm, which is one order of magnitude higher than that of pure PEO. When the temperature was increased to 70 ℃, the conductivity reached 1.08×10^-3 S/cm. The number of lithium-ion transference of CPE20 increased to 0.46, while that of pure PEO solid electrolyte is 0.36. Thus, the CPE20 preparation of LiFePO₄||Li battery has good capacity and cycle performance at room temperature, with a capacity rate of more than 96%. Therefore, adding an appropriate amount of ZIF-8 inert filler can effectively reduce the crystallinity and increase the amorphous zone of the polymer. It can also promote the dissolution of lithium salts and improve the mobility of lithium ions, which make the composite solid electrolyte has more excellent electrochemical performance. Thus, the findings show that the PEO-based solid polymer electrolytes with ZIF-8 have potential application in solid-state lithium batteries.

Currently, lithium/fluorinated carbon (Li/CF _x ) primary batteries are chemical power sources with the highest energy density and have stable output voltage, good safety, wide operating temperature range, and low self-discharge rate. These features are of irreplaceable importance in critical fields such as military (man-portable combat systems), medical (pacemakers), and space explorations (space stations). However, the poor electronic conductivity of CF _x largely affects the electrode process kinetics of electrochemical reactions, resulting in poor high-magnification discharge performance, severe delay in initial discharge voltage, and high heat generation during the discharge process of Li/CF _x primary batteries. In this paper, we first review the discharge mechanism of Li/CF _x primary batteries by examining the recent literature on the two-phase discharge reaction mechanism model, discharge reaction mechanism model for the generation of graphite interlayer compound intermediate phase, "core-shell" model reaction mechanism, edge propagation discharge reaction mechanism, and three-step discharge reaction mechanism. Second, the solutions to the problems faced in Li/CF _x primary batteries are analyzed by focusing on the selection of CF _x precursors, improvement of fluorination methods, construction of composite materials, and modification and optimization methods of electrolytes. Among them, the application of new fluorocarbon-based materials such as fluorinated carbon nanotubes, fluorinated fullerenes, and fluorinated graphene provides new prospects for the development of CF _x . Incorporating conducting polymers, metal nanoparticles, and oxides during the construction of composite materials can significantly reduce the voltage delay time and improve the rate performance. In the regulation strategy of electrolyte, the introduction of fluorine ion binding agent and the calculation of lithium-fluoride crystal growth kinetics play an important role in dissolving and controlling the growth of lithium-fluoride, which is expected to realize a wide temperature domain Li/CF _x primary battery with both high energy density and high power density.

Thermal energy is the most used form of energy, and thus, it is important to improve its utilization rate in practical applications. Phase-change materials are a thermal energy storage medium that can achieve a high utilization rate of energy by storing or releasing latent heat, thus reducing the emission of carbon dioxide. However, phase-change materials have certain limitations, such as subcooling, low thermal conductivity, liquid leakage, and corrosion problems, in practical applications. These materials can be wrapped by a certain packaging technology to prepare microcapsules in order to avoid any liquid leakage. Modification of shell materials can result in better mechanical strength, improved thermal stability, and high thermal conductivity. Phase-change microcapsules can be categorized into micron and nanomicrocapsules at the microscopic scale. Numerous scholars have studied the preparation and application of phase-change microcapsules in the field of thermal energy storage. Thus, this article presents a detailed review of the synthetic materials, preparation methods, and application fields of phase-change microcapsules, focusing on the types of core and shell materials and their advantages and disadvantages. In addition, this review emphasizes preparation methods such as physical methods (electrohydrodynamic encapsulation, spray drying method), chemical methods (emulsion polymerization, mini-emulsion polymerization, in situ polymerization and interfacial polymerization), and physical-chemical methods (coacervation and sol-gel method). Finally, the review introduces and prospects the application of phase-change microcapsules in the fields of construction, temperature-controlled textiles, and solar energy utilization.

Lithium-ion battery energy storage system has a fire safety problem that has become a key bottleneck restricting its large-scale promotion. The existing traditional gas fire extinguishing system based on fixed buildings has low fire extinguishing efficiency. Thus, this research work aimed at developing a prefabricated cabin-type lithium-ion battery energy storage system. Here, a targeted fire prevention and control equipment for an energy storage system was developed based on multi-layer collaborative early warning technology and different protection and fire-extinguishing strategies. First, a combustible gas sensor and Pack temperature sensor, which is an accurate, reliable, economical and practical multi-layer early warning technology, were built based on smoke/temperature detector. Second, lithium-ion battery fire-suppression system was added based on a heptafluoropropane fire-suppression system to meet the requirements of fire suppression of lithium batteries and the national standard electrical and fire protection design. The designed fire-fighting equipment supports multiple start of multi-point packs, which can effectively inhibit the re ignition of lithium battery fire. The combination of a fire-extinguishing system and a fire-suppression system ensure the safety of lithium battery energy storage system in all aspects.

In recent years, clean-energy heavy trucks have undergone rapid development because of their zero emission, long endurance, and other suitable characteristics. In addition, their fuel cells serve as their auxiliary power cell. In low-temperature environments, the performance degradation of auxiliary power batteries of heavy trucks is insufficient to bear the role of the auxiliary power source in peak shaving and valley filling. Therefore, to cope with cold environments, heavy trucks should consider heating the auxiliary power battery to recover their charge and discharge performance. In this paper, a square lithium-iron phosphate battery pack was considered as the research object, and the discharge conditions of a single lithium-iron phosphate battery at -10 ℃, 0 ℃, 10 ℃, and 20 ℃ were tested through experiments. The low-temperature thermal characteristics of the battery were obtained; a single-battery thermal model was established, and its effectiveness was verified. Based on this model, a dual-heat source heating system was proposed, in which the graphene heating film was the main heat source and the waste heat of the vehicle-mounted heat source was the auxiliary heat source. A linear time-varying model predictive controller (MPC) was established based on the heat transfer principle to reduce energy consumption of the battery heating system. The results show that, under the driving condition of the China-world transient vehicle cycle, the battery heating system can improve the heating rate of the power battery pack using the waste heat of the vehicle-mounted heat source through the heat exchanger. By using the heating film and heat exchanger, the heating system can increase the energy efficiency by 30% compared with the traditional PTC heating system. The heating system with MPC control strategy has 14% higher energy efficiency than that with the proportional-integral-derivative control.

In a running redox flow battery system, the state of charge (SOC) of the electrolyte in the tanks is not uniform and is different from that of the electrolyte in the outlet of the stack. The mixing of electrolyte with different SOC results in energy loss in tanks. Thus, this paper reports a model-based study on the performance of a redox flow battery under the conditions of complete mixing and nonmixing of electrolytes in the tanks in order to quantify the effect of electrolyte mixing in the tanks on the efficiency of the system. The transport of active species in a real tank is also analyzed and compared with that under complete mixing condition. A diversion structure is proposed to optimize the electrolyte flow in the tanks to minimize the mixing loss in the tank. The results show that the mixing of electrolytes with different SOC in the tanks reduces the utilization rate of electrolyte and the voltage efficiency of the redox flow battery system, and the influence on the voltage efficiency may reach more than 1%. The mass transfer correlated energy loss in the real tank is also affected by the dead zone, where the electrolyte is stagnant. The dead zone reduces the available volume in the tank and increases the concentration gradient adjacent to the dead zone; this leads to increased mixing loss. The use of partition contributes to the reduction of concentration gradient and cross-sectional area of diffusion. This paper also creates a preliminary design for a novel tank structure, aiming to provide ideas for the design of tanks from the perspective of reducing mixing loss.

A liquid flow battery has low long-term energy storage cost and high system security, and thus, it is suitable for large-scale long-term energy storage application scenarios. The intermittency and fluctuation of the new energy power generation system can be suppressed through reasonable planning and configuration of the liquid flow battery system; this is of great significance for ensuring the safe and stable operation of the power grid. At present, there is a lack of research on the new energy system and the optimization configuration method of liquid flow battery based on their technical characteristics and operation characteristics. With the rapid transformation of energy in China, giving importance to the technology and operation characteristics of liquid flow battery and optimizing their capacity in the new energy system play a positive role in establishing a new power system. Thus, this paper examines the local area network (LAN) of photovoltaic and liquid flow battery joint power generation and proposes the optimal configuration method of liquid flow battery energy storage for photovoltaic system. The initial investment, full life operation, maintenance costs of each module system in the liquid flow battery system were assessed through in-depth research and analysis of operation characteristics, based on the characteristics of liquid flow battery system that power and capacity modules are separated. The power and capacity ratio of large-scale liquid flow battery system were optimized. Our results show that the operation strategy of the LAN system for photovoltaic and liquid flow battery combined power generation is optimized. While ensuring the stable operation of the LAN power supply, the optimal configuration scheme of the liquid flow battery was obtained by taking the minimum sum of the initial investment of the liquid flow battery system and the full life operation cost as the objective function. This shows that the proposed method can obtain the optimal solution of the liquid flow battery energy storage configuration of the photovoltaic system, and the sum of the initial investment and the life-cycle operation and maintenance cost is the minimum. The most economical megawatt liquid flow battery module design is when the power and capacity configuration of large-scale liquid flow battery system is 1 MW/8 MWh, and the LCOE for 25 years of operation is 0.292 yuan/kWh. The objective function of energy storage optimization configuration in the LAN applied in this paper achieves the optimal solution when the energy storage configuration is 20 MW/160 MWh.

In recent years, with the development of energy Internet technology, there is a need for simulation methods to research energy Internet. Thus, this paper proposes a simulation modeling method for energy Internet based on RTplus (a real-time simulation software). In this method, the host computer of RTplus realizes the simulation of an information communication network. The server computer of RTplus depends on the basic component of multiple energy sources in MATLAB/SIMULINK. The modeling method for key equipment for electrical and thermal systems is based on on-site typical data. This method could recur on-site energy fluctuations completely. The energy Internet equipment connected to the simulation platform could be hardware-in-the-loop (HIL) tested in a more on-site manner. This paper uses an energy management system, which is the key equipment for distribution networks in a large industrial park, as an example. Finally, the correctness of the simulation modeling method was verified using an HIL simulation platform.

Given the estimations that carbon emissions will peak by 2030 and carbon neutrality will be achieved by 2060 in China, large-scale new energy sources, with wind and solar as the main force, are connected to the grid. The increase in energy consumption leads to serious environmental problems. This may be resolved by using new energy, and accordingly, the structure of power generation has undergone significant changes. The large-scale grid-connected new energy is associated with randomness and volatility. In addition, grid frequency fluctuation can be easily caused after penetrating the power grid, and this seriously threatens the safety of the grid. This issue can be resolved by improving the frequency modulation supported by the power generation side. An energy storage system integrated with thermal power units participates in the primary frequency modulation, resulting in improved security of power grids and improved economic efficiency. To realize the advantages of flywheel energy storage auxiliary frequency modulation of the power grid, the frequency modulation capability of the combined thermal power-flywheel system was analyzed based on the model, considering the influence of current energy storage on frequency modulation. In this regard, this paper proposes a control strategy for flywheel energy storage participating in frequency modulation division based on improving the power grid assessment index of the north China power grid. The strategy is calculated according to the current electric quantity of flywheel energy storage, and different output time limits are adopted in different electric quantities to meet the primary frequency regulation assessment index of the power grid. The frequency modulation effect of the system and the output of frequency modulation resources under load disturbance are analyzed using MATLAB/Simulink software. The results show that the proposed method can effectively improve the frequency modulation performance of the unit and improve the quantitative index of the unit with different discharge times under different conditions of the flywheel energy storage. Thus, the proposed method provides good support to the frequency modulation index at different power levels and effectively improves the economic assessment and efficiency of a power plant.

The electric phase of electrified railway constitutes a no-power zone, which hinders the energy transfer in each power supply area, is not conducive to the recovery and utilization of regenerative braking energy, and greatly affects the railway operation efficiency. In order to reduce the railway operation cost, the railway power conditioner (RPC) is connected in the electric phase, and the RPC DC link is convenient for the hybrid energy storage system (HESS) to access. On this basis, an optimal operation strategy of traction power supply system (TPSS) is proposed in this paper. By controlling the charge and discharge of HESS, the load peak is reduced and the braking energy is recovered, so as to realize the peak cutting and valley filling of traction load. The model aims to minimize the total operating cost of TPSS, and takes HESS charging and discharging power as decision variables. Furthermore, the nonlinear function in the model is linearized to obtain the mixed integer linear programming model, and then CPLEX is applied to obtain the charging and discharging strategy of HESS and the power purchase scheme of TPSS. Finally, based on the measured data, the cost-reduction effect of the proposed model is analyzed. Compared with the existing TPSS, the daily operating cost of the TPSS is significantly reduced after the HESS and RPC are connected, which provides a basis for the optimization operation of the TPSS.

An energy storage system equipped with a new energy station can smooth the fluctuation of output power and undertake the frequency regulation obligation of the new energy unit. Nevertheless, the energy storage may cause an insufficient active power reserve of the frequency modulation system if it considers only the single stabilizing fluctuation condition. Therefore, this paper proposes a strategy for wind power fluctuation stabilization considering frequent-modulated active power backup and state of charge restoration. First, a clustering algorithm was used to extract typical working conditions of energy storage fluctuation stabilization power. The energy storage required to smooth the fluctuation power demand and residual active power was calculated. Second, the energy storage frequency modulation reserve and wind power load reduction are used to provide active power reserve according to the national standard for active power reserve of wind farms, and the energy storage to stabilize the fluctuation power limit is set. Finally, the fuzzy control theory is used to design the strategy for restoring the state of charge at the edge of the energy storage system. Based on the actual wind farm operation data, the simulation results show that the proposed method can provide active power backup and restore the state of charge in the edge zone when the energy storage system suppresses wind power fluctuation.

This paper proposes an adjustable resource aggregation method and a coordinated scheduling strategy in distribution transformer station area based on time-of-use price and charge-discharge strategy for distributed energy storage considering the user's electricity cost and energy comfort. The proposed methods can realize the coordinated scheduling of adjustable resources and the coordinated optimization of different types of energy units in the distribution transformer station areas. First, the framework of the platform energy use management and control system is constructed, following the architecture of the distribution Internet of Things and based on the "cloud-edge" collaborative technology. Then, the platform loads are classified according to the response uncertainty, and the Monte Carlo algorithm is used to aggregate the power of typical adjustable resources. The effectiveness of the aggregation model is then analyzed. Finally, the load aggregator is introduced to interact with the station area. The linear weighting method is used to calculate the electricity cost and energy consumption comfort level of users, and the charge-discharge strategy of distributed energy storage is combined to model the adjustable resource scheduling model of the distribution transformer station area. The differential evolution algorithm is then used to solve the model. The example analysis shows that the adjustable resource aggregation model and the coordinated scheduling strategy proposed in this paper can effectively reduce the energy consumption cost of users, improve the energy consumption comfort level, promote the enthusiasm of users to participate in grid response and improve the station area's ability to control the adjustable resources.

Accurate prediction of remaining useful life (RUL) of lithium-ion batteries is an important research topic as it can help reduce the risks of lithium-ion battery accidents. Thus, this research proposes a prediction model of RUL of lithium-ion batteries that comprises an attention mechanism and combines the advantages of residual neural network (ResNet) and bidirectional short-term memory network (Bi LSTM). For this, the characteristic parameters that can represent the battery life were selected as the input quantity. ResNet was used to extract the implicit characteristic information of the input data and Bi LSTM was used to predict the time series information. The attention mechanism was used to distribute the weight of the prediction results so as to obtain the final RUL prediction results of lithium-ion batteries. The RUL prediction test of lithium-ion batteries was carried out using the open-source dataset provided by the University of Maryland (CALCE) of the United States, and the obtained results were compared with that of the existing prediction models. The test results show that the proposed model can accurately predict the RUL of lithium-ion batteries, with relatively low errors and good accuracy. Finally, the generalization experiment was carried out using the open-source dataset of lithium-ion batteries provided by NASA, and its results confirmed that the proposed model has good accuracy in predicting the RUL of different batteries and, thus, has wide applications.

Accurate estimation of capacity plays an important role in the health management and predictive maintenance of lithium-ion batteries. In recent years, data-driven methods have been widely used in the capacity estimation of lithium-ion battery. However, most of these methods assume that the training and test data obey the same distribution, resulting in a rapid decline in accuracy when the test conditions change. The existing transfer learning methods for lithium-ion battery capacity estimation aim to align the global distribution of source and target domains, while ignoring the transferability of features within different layers. Thus, this study proposes a hierarchical alignment transfer learning method for lithium-ion battery capacity estimation and examines the feature transferability among different layers of the deep transfer learning. First, a feature extractor based on a convolutional neural network was designed. Considering the feature transferability within different layers, the maximum mean discrepancy constraint and channel attention consistency constraint were imposed at different layers of the feature extractor. Thus, the features extracted from the source and target domain are similar, and the feature extractor focuses more on domain-invariant features. A predictor then obtains a capacity estimation value. The experimental results were validated on a public lithium-ion battery dataset and compared with other methods. Our findings show that the proposed method has higher estimation accuracy and is significantly better than other methods. In addition, the findings demonstrated the effectiveness and superiority of the transfer learning method in cross-domain capacity estimation.

In this study, a state of charge (SOC) estimation method is proposed based on a combination of data preprocessing and algorithm optimization in order to improve the efficiency and accuracy of data-driven method in predicting SOC. The open data was selected as the training set, and the random forest (RF) algorithm was used to determine the influence degree of each feature of the training set on SOC. For this, optimal training samples were selected, and the rationality of the optimal samples was verified. Limit learning machine (ELM) was used to predict SOC, aiming at the instability of random weights and thresholds generated by ELM in the prediction process. This leads to the unsatisfactory accuracy of SOC estimation. Sparrow search algorithm (SSA) was selected for optimize parameters and improve estimation accuracy. Subsequently, the effectiveness of SSA parameter optimization was verified using the BJDST simulation test. Under the constant current discharge and DST working conditions, the improved extreme learning machine (SSA-ELM), ELM, support vector machine, and back-propagation neural network were used to predict the SOC. The results show that the SSA-ELM algorithm has the best prediction effect and a prediction error \ within 1.5%, thus achieving high-precision SOC prediction.

Lithium batteries have high energy density, high output voltage, and no memory effect, but their overcharge and over-discharge can cause accidents. In this regard, accurate prediction of the state of charge (SOC) of lithium batteries serves as the best condition. In this paper, a method based on an adaptive noise integrated Empirical Mode decomposition (CEEMDAN) and data-driven model is proposed to predict the state of charge of lithium-ion batteries. The original voltage data of lithium-ion batteries were modally decomposed to obtain the modal components of multiple sub-sequences. An improved Seagull algorithm (ISOA) based on the inertia weight and the Levy flight mechanism was proposed. The parameters of the extreme learning machine prediction model were optimized, and ISOA-ELM lithium battery prediction model was built. The SOC prediction results of the lithium batteries were obtained by training the model. The experimental results show that the model can better fit the actual SOC in practice and is more conducive to the lithium battery working in the best state.

Lithium-ion batteries are an important energy storage sources, and it is of great practical importance to predict their remaining useful life (RUL). First, the battery data are treated as matrices, and singular value decomposition (SVD) is introduced to extract the potential health indicator (HI) from the measured data and the feature extraction objects containing more degradation information. This will address the drawbacks of traditional feature extraction methods that rely on parameter settings and poor adaptability to different lithium-ion battery datasets. Second, the redundancy and deficiency of potential HIs affect the prediction of RUL, and thus, a fused HI is obtained by processing HIs using Spearman correlation analysis and stacked autoencoder, considering the shortcomings of principal component analysis (PCA). Accordingly, a model between fused HI and capacity is constructed using the Gaussian process regression algorithm, and the final prediction results with uncertainty expression are obtained. Finally, the feasibility and validity of the proposed prediction model are verified by four aging batteries provided by NASA. The MIT battery dataset is used to verify the adaptability of the feature extraction method. The experimental results show that the proposed RUL prediction framework has good prediction performance and that the SVD feature extraction method has good adaptability while avoiding parameter settings. The HI extracted in this paper has significantly improved the prediction accuracy compared with the HI after PCA fusion and other HIs.

Thermal runaway (TR) of lithium-ion battery (LIB) is caused due to various factors. Therefore, it is of great significance to obtain the degree of importance of the factors affecting the TR of LIB to improve battery safety. Thus, this paper used COMSOL to analyze the influence of the penetrated position, speed of penetration, nail diameter, and state of charge (SOC) on the TR of LIB. Based on the results of penetration test of a single LIB, the influence of different penetrated diameters (R), SOC of the battery, and the number of penetrated cells (N) on the thermal diffusion of the battery module were analyzed. Subsequently, an orthogonal test was designed to analyze the penetrated conditions of battery modules, and it considers the N, R, SOC, and the interaction among these three factors. The results show that the battery SOC and penetrated diameter R significantly influence the TR of the battery, compared with the penetrated position and speed. Based on our findings, the smaller the R is, the more severe is the TR, and the larger the SOC is, the more uneven is the temperature distribution of the TR. In addition, the larger the R is, the longer is the thermal diffusion time for the battery module. The maximum TR temperature of each battery in the module changes when SOC varies within 100%～85%. The larger the N is, the more severe is the TR of the module. However, the maximum temperature of the battery located in the middle of the module decreased. For the battery module, the significance of the factors on the TR temperature and diffusion time is N>R>SOC*R>SOC* N>N*R>SOC. The number of penetrated cells significantly affected the thermal diffusion of the battery module, and the interaction between the factors cannot be ignored. This research paves a way to improve battery safety and design.

In this paper, the impedance analysis method was used to detect the lithium evolution threshold of lithium-ion batteries at different temperatures and charging rates. Comparison test and analysis with the nondestructive testing method and relaxation voltage analysis method (dV/dt method) were conducted. The impedance value obtained through intermittent sleep during battery charging is taken as the analysis data. The inflection point of impedance decline at the end of charging represents the beginning of the lithium evolution of the battery. The corresponding voltage and state of charge are the lithium evolution threshold of the battery. The results show that the impedance analysis method can realize nondestructive detection of lithium evolution from batteries. The detection results of the method for lithium evolution from batteries are consistent with those of the relaxation voltage analysis method. The impedance analysis method accurately determines whether lithium evolution occurs in batteries and also measures the threshold voltage or the state of charge of the battery at which lithium evolution begins, thus providing a basis for the optimization of the charging system. By using impedance analysis method, this paper further uses this method to detect the lithium evolution threshold voltage of a cylindrical ternary battery and lithium iron phosphate battery. Here, the lithium evolution boundary of the battery in combination with different temperatures and charging rates are analyzed. The results show that lithium evolution easily occurs in the low-temperature environment for lithium iron phosphate and nickel cobalt aluminum ternary batteries, and the threshold of lithium evolution of the battery gradually increases with the increase in temperature. Thus, this improves the phenomenon of lithium precipitation. However, for the nickel-cobalt aluminum ternary battery, lithium begins to separate from the battery, when the rate is increased to 0.6 C at room temperature. Thus, the monitoring and analysis of the battery using the lithium evolution threshold method significantly affects the formulation of subsequent battery charging strategy.

Electrode materials are the key structural components of lithium-ion batteries, and their structural stability directly determines the electrochemical performance of lithium-ion batteries. Nevertheless, it is challenging to characterize their microstructure and structure since the electrode materials are sensitive to air and moisture, not resistant to electron beam irradiation, and the electrode itself and its chemical environment are constantly changing during the charging and discharging process. Focused ion beam-scanning electron microscope is an important means of preparing transmission samples and has been widely used in semiconductor, biology, and other fields. Based on the discussion of related literature in recent years, this paper summarizes the solutions of focused ion beams in the field of lithium-ion batteries, focusing on the latest progress of focused ion beams in three-dimensional (3D) reconstruction, freezing processing, the construction of single-particle batteries. 3D reconstruction technology can obtain 3D characteristic information on pore networks, multi-phase structure, and volume change in electrode materials; perform a quantitative evaluation; and establish a microstructure model to predict battery performance. Based on cryogenic processing technology, the liquid electrolyte, Li metal, and other beam-sensitive materials are frozen to maintain their original morphology and chemical properties, which can effectively characterize the intrinsic information of the Li metal anode and solid-liquid interface. The construction of a single-particle microbattery can realize the in situ observation of microstructure evolution during a single-particle cycle; avoid the influence of binders, conductive additives, etc. on the intrinsic properties of the material; and determine the intrinsic characteristics of the electrode material. Thus, this paper introduces the processing process of focused ion beam, analyzes the shortcomings in the processing process, and presents the associated challenges. The findings of this article provides insights for researchers based on the characteristics of lithium-ion battery materials and focused ion beam experimental methods.

In recent years, compressed air energy storage (CAES) has garnered much research attention as an important type of new energy storage. Since 2021, several 10 MW CAES projects were completed and connected to power systems. This technology has gradually matured and industrialized. In this study, the main technology roadmaps and four key parts of CAES are briefly introduced. Then the study focuses on advanced adiabatic CAES (AA-CAES), which is currently the most widely used technology. After the technical and economic data of the existing and planning projects are analyzed, the characteristics and development trends of CAES are summarized. With respect to its technical aspects, CAES has long operation lifespan, system-friendly performance, and low security risk. In the future, CAES can be developed in a larger scale, with improved efficiency and increased system application. With respect to its economic aspects, CAES has relatively high cost of construction. With further development in the industry and progress in technology, CAES based on salt-cave-air-storage and artificial-chamber-air-storage will be cheaper than the current large-and-middle-sized pumped storage, and CAES based on pipeline-steel-air-storage may become as cheap as small-and-middle-sized pumped storage of comparable scale. In the end, this paper discusses the investment payback of CAES. Under the current market environment, CAES projects can hardly receive reasonable profits. Therefore, there is a need for supporting policies. Thus, it is recommended that policies can first be implemented on several demonstration projects and then price support can be offered to a certain extent.