Table of Content

25 August 2026, Volume 46 Issue 4

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Source-Grid Coordination and Energy Conversion and Utilization

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Resource Dispatch Methods of Operation and Maintenance for Offshore Wind Farms Under Multiple Operating Conditions and Task Schedules

DONG Bin, FU Yanbo, ZOU Yueming, YANG Shiqi, PAN Qiaobo, LING Jili

2026, 46(4):  1-8.  doi:10.3969/j.issn.1008-0198.2026.04.001

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Traditional operation and maintenance(O&M) resource scheduling strategies for offshore wind turbine clusters are inefficient, and restricted by harsh environmental and meteorological conditions. The tight O&M working time further intensifies the O&M pressure. Aiming at the above O&M difficulties, this paper proposes a cooperative path optimization model for mother-daughter ships in offshore wind turbine cluster O&M. Firstly, the principle and implementation method of the fuzzy C-means clustering method(FCM) are analyzed and introduced. Then, according to the actual layout characteristics of the offshore wind turbine cluster, the wind turbines requiring maintenance are divided into k groups based on FCM. Finally, taking k dynamic O&M centers as key input nodes, a multi-objective mathematical model is constructed with the core objectives of minimizing the total O&M cost, shortening the O&M time, and minimizing the power generation loss of wind turbines. The model elaborately considers complex constraints such as the cooperative paths of O&M mother ships and daughter ships, the load capacity and personnel limits of ships, the limited daily operation time window, and the penalty cost for delayed O&M. The simulation results show that when the number of O&M centers is 3, the total O&M cost is the lowest, which is 5.8% lower than the path planning scheme with 2 O&M centers, and 9.8% lower than the scheme with 4 O&M centers. This research provides theoretical support for offshore wind power O&M path planning, and has important reference value for improving O&M efficiency and reducing O&M costs.

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An Operational Maintenance System for Dispatch Models Integrating Knowledge Graph and Visual Engine

HE Xiling, ZHENG Zi, WANG Yun, ZHOU Yang

2026, 46(4):  9-14.  doi:10.3969/j.issn.1008-0198.2026.04.002

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Current maintenance of smart grid dispatch models faces challenges such as low operational efficiency, high reliance on manual intervention, and difficulties in quality control. A novel intelligent operation and maintenance system is designed and implemented by integrating knowledge graph technology with the Node-RED visual workflow engine, constructing a structured operation knowledge base and dynamic process guidance. It can guide operation and maintenance personnel step by step to accurately and efficiently carry out dispatching model maintenance tasks. The system employs natural language processing techniques to extract entity relationships from operation manuals and dispatch system domain data, forming the inferable operation knowledge graph. Leveraging Node-RED’s visual programming interface, it enables flexible configuration of operation workflows. Real-time verification algorithms covering data integrity, electrical rationality, and other dimensions are developed. Through a practical case study of a municipal-level power grid, it has been demonstrated that the system improves operational efficiency by 62.5%, with a model accuracy rate exceeding 99%, providing a verifiable quality assurance mechanism for the dispatching automation system.

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Failure Analysis of Shaft Sticking Caused by Shaft Seal Water Ingestion During Steam Turbine Shutdown

ZAI Jun, LIU Xia, YI Chao

2026, 46(4):  15-19.  doi:10.3969/j.issn.1008-0198.2026.04.003

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During the sliding parameter shutdown of an 80 MW steam turbine unit in a steel cogeneration power plant, a sudden failure characterized by excessive vibration and severe shaft sticking occurred. A comprehensive retrospective analysis is presented covering the fault evolution process, realtime operational data, and the structural characteristics of the equipment system, thereby accurately identifying the triggering factors and thoroughly investigating the root causes of the failure. After comprehensive measures such as cylinder sealing, drainage, turning, and shaft calibration, the unit gradually recovered within about 6 hours, and the peak eccentricity of the shaft system decreased from 442.32 μm to 28.37 μm. Based on the actual site conditions, a targeted corrective scheme is formulated, which includes replacing the original check valve with a swingtype structure, optimizing the layout of the drainage pipeline, and adding interlock protection logic for the emergency drain electric valve of the shaft seal heater, along with several other technical modifications and operational improvements. The fault analysis methodology, troubleshooting procedure, and rectification experience presented in this paper can serve as a valuable reference for the sliding parameter shutdown control, equipment hazard management, and routine maintenance of similar cogeneration units.

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Optimization of Active Power Allocation Based on Fatigue Damage Characteristics of Wind Power

QU Junhui, JI Hongzhen, DOU Di, LIAO Xiaoyu

2026, 46(4):  20-25.  doi:10.3969/j.issn.1008-0198.2026.04.004

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For the significant fatigue damage to critical components such as the main shaft and tower of wind turbines in wind power generation, as well as the issue where the traditional active power average allocation strategy in wind farms leads to certain turbines operating under high loads for extended periods, this paper proposes an active power optimization allocation method based on fatigue damage characteristics of wind power. First, to account for the influence of the geographical environment on turbine fatigue damage, a novel calculation model is established for main shaft torque and tower thrust based on environmental temperature, wind speed, and altitude by combining the ideal gas equation of state with force analysis of air units. Second, by improving the three-point rain-flow counting method, the effective cycle count, load amplitude, and mean load can be calculated more accurately. On this basis, a nonlinear time-varying fatigue damage model considering wind power generation characteristics is further constructed. Finally, the FATA optimization algorithm is employed to solve the wind farm active power optimization allocation problem, aiming to minimize the fatigue damage level of wind turbines. Simulation results from actual case studies demonstrate that, compared to the traditional average allocation strategy, this method significantly reduces turbine fatigue damage while ensuring accurate tracking of grid dispatch commands by the wind farm’s delivered power. This provides valuable theoretical and applied references for the safe and economic operation of wind farms.

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Application Status of Evaporative Cooling Technology in Energy Conservation and Carbon Reduction for Power Plants

ZHANG Chongwen, XUE Yu

2026, 46(4):  26-33.  doi:10.3969/j.issn.1008-0198.2026.04.005

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The principles and advantages of direct, indirect and composite evaporative cooling systems are elaborated regarding their application in power plants. Combined with domestic and overseas engineering cases of power plants, the application of evaporative cooling technology in various scenarios is analyzed. Revit modeling and CFD numerical simulation are adopted for scheme optimization to compare the cooling performance of different ventilation systems during operation. Engineering practices demonstrate that evaporative cooling technology features low power consumption, water conservation, environmental friendliness and low cost. It can satisfy the ventilation and air conditioning demands of main power plant buildings, power distribution rooms and office buildings, as well as the cooling requirements of core equipment in thermal and hydropower plants. The technology delivers prominent benefits in arid and semi-arid regions, and can also be deployed in high-humidity areas after refined parameter adjustment. Its comprehensive benefits outperform those of some traditional cooling technologies.

Power Grid Operation and Control

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A Novel Ground Fault Suppression Method Based on Thyristor High-Speed Closing and Neutral-Point Voltage Regulation

DUAN Xujin, LIU Baiyang, XIANG Hong, YANG Hanhao, LIU Ximeng

2026, 46(4):  34-40.  doi:10.3969/j.issn.1008-0198.2026.04.006

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To address the issues of high single-phase-to-ground fault current, intense transient processes, and slow operation of traditional mechanical switches in distribution networks, a novel ground fault suppression method based on thyristor high-speed closing and neutral-point voltage regulation is proposed. Firstly, a single-phase ground fault suppression model is established, unifying the calculation methods for three-phase unbalance and single-phase ground faults, thereby revealing the coupling relationship among neutral-point voltage, ground fault current, and line-to-ground parameters. Furthermore, the neutral-point voltage is taken as the control variable, the current flowing into the neutral point as the state variable, and the inherent line-to-ground parameters as disturbance variables. Introducing the concept of fault suppression degree based on neutral-point voltage regulation, a ground current suppression strategy centered on real-time neutral-point voltage control is constructed. Finally, considering the slow operation of traditional mechanical switches, a thyristor high-speed interrupter circuit is introduced to achieve rapid blocking of the neutral-point voltage and millisecond-level adjustment of the current path. Validation on an experimental platform shows that this method can effectively reduce the peak fault current in the initial fault stage, shorten the transient recovery time, and significantly enhance the system's ground fault suppression capability and operational stability.

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Cause Analysis and Correction Strategies for Multiple Reporting of Fault Phases in Transformer Differential Protection

SHE Changjia, SUN Zichang, CHEN Hao, CHEN Yuanxin, DU Xiao

2026, 46(4):  41-46.  doi:10.3969/j.issn.1008-0198.2026.04.007

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To address the issues of misjudging fault types and multiple reporting of fault phases after the differential protection of main transformers in substations, the current phase compensation principle for reducing unbalanced currents in the differential circuit of main transformers is first analyzed. Combined with this compensation algorithm, the causes of multiple reporting of fault phases in main transformer protection are examined. Subsequently, at the algorithmic level, a strategy based on current variation for fault phase selection as an auxiliary criterion is proposed to correct the phase selection results of the protection device, and the effectiveness of the correction strategy is verified through practical examples. Finally, based on the cause analysis and correction strategy, a solution to address this issue is provided. The fault handling method prompt card has been implemented in several 500 kV substations in Jiangsu, offering guidance for the operational and maintenance handling of main transformer accidents in substations.

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Microgrid Energy-Reserve Joint Market Bidding Strategy Based on Cost Mapping

ZHU Junfei, WU Jinbo, XU Min, LI Long, GONG Yusheng, LIU Ruoqi

2026, 46(4):  47-56.  doi:10.3969/j.issn.1008-0198.2026.04.008

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To address the high-dimensional coupled bidding decision-making challenges and internal privacy leakage risks faced by microgrids when participating in the energy-reserve joint market, a day-ahead market bidding strategy is proposed for microgrid based on cost mapping. Firstly, the internal refined operation model of the microgrid is reconstructed as a multi-parameter programming problem with the market bidding volume as the parameter. Through analytical solution, an explicit piecewise linear mapping relationship between the bidding volume and the operation cost is generated. Secondly, a Stackelberg game bidding-clearing two-layer model based on this internal cost domain is constructed. By using the KKT conditions and strong duality principle of the lower-level clearing model, the original problem is efficiently transformed into a solvable single-layer mixed-integer linear programming model. The case study shows that the proposed method can accurately represent the real operation cost of the microgrid with zero deviation, effectively protect sensitive information such as internal equipment parameters and operation status, and has good computational efficiency.

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Risk Assessment and Collaborative Optimization Method of Transmission-Distribution-Microgrid Considering Dual-Domain Constraints

QIAN Jun, HUANG Jiyuan, WU Jinbo, LI Shuaihu, ZHENG Junfeng, LI Lin

2026, 46(4):  57-68.  doi:10.3969/j.issn.1008-0198.2026.04.009

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To address the security operation risks caused by the complex uncertainties arising from the integration of massive distributed renewable energy sources into low-voltage grids, a multi-layer risk assessment and coordinated optimization method is proposed that accounts for the dispatchable region of microgrids and the security region of transmission-distribution networks. First, a multi-level risk assessment index system and framework are established from the perspectives of the transmission, distribution network, and microgrid. Second, stochastic models for key uncertain factors such as distributed wind power, photovoltaic generation, load, and component failures are developed, and a set of system operational states is generated using sequential Monte Carlo simulation. Then, a collaborative operation optimization model for the transmission, distribution, and microgrid is constructed based on the dispatchable domain of microgrids and the security domain of main and distribution networks. The stochastic power flow is rapidly solved using the semi-invariant method and Cornish-Fisher series expansion, and an opportunity-constrained optimization scheduling model is introduced to ensure economic operation while effectively managing operational risks. Finally, the method is validated using an improved transmission-distribution-microgrid system based on IEEE 9-bus and IEEE 33-bus configurations. The results demonstrate that the proposed method achieves optimal economic benefits while effectively controlling operational risk levels at all levels, providing theoretical support and methodological references for the collaborative operation and risk assessment of main-distribution-microgrids with high renewable energy penetration.

Distribution Network and Using Energy Technology

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A Comprehensive Operational Flexibility Evaluation Method for Distribution Networks With High-Penetration Emerging Source-Load Integration

LI Shiwei, ZHANG Hui, WANG Xuli, LING Ru, CHENG Xiao, ZHANG Changwen, QIN Liang

2026, 46(4):  69-78.  doi:10.3969/j.issn.1008-0198.2026.04.010

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To address the intensified net-load fluctuations, strengthened source-load uncertainty, and insufficient flexibility of distribution networks under high renewable energy penetration and the rapid development of emerging loads such as electric vehicle charging facilities, a comprehensive operational flexibility evaluation method for distribution networks is proposed. First, an evaluation index system consisting of four dimensions, namely economy, security, source-load matching, and fluctuation suppression, and 12 secondary indices is constructed. Second, Latin hypercube sampling is adopted to generate typical scenarios considering the uncertainties of renewable energy generation, output conventional load demand, and electric vehicle charging load, and the value of each index is calculated based on a source-grid-load-storage coordinated optimization model for distribution networks. Then, the combined weights are determined by the AHP-entropy weighting method, and TOPSIS is employed to realize the comprehensive evaluation and ranking of different operating schemes. A modified IEEE 33-bus system is used for case verification. The results indicate that the proposed method can comprehensively reflect the operational flexibility differences of distribution networks under high renewable energy and emerging load integration scenarios, and provide a quantitative basis for operating mode selection and flexibility resource allocation.

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Research on Adaptive Trajectory Tracking Control of Pole Drilling and Erecting Machines for Distribution Network Pole Erection Construction

HE Jilin, CHEN Wei, YANG Miao, YIN Peng

2026, 46(4):  79-88.  doi:10.3969/j.issn.1008-0198.2026.04.011

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To enhance the automation level of distribution network pole erection construction and power equipment transport operations, aiming at the problems of insufficient trajectory tracking accuracy and poor stability during high-speed transfer of pole drilling and erecting machines, an adaptive trajectory tracking control method integrating time-domain parameter adaptation and weight matrix dynamic optimization is proposed. Firstly, based on a two-degree-of-freedom error model, a predictive control architecture suitable for power construction machinery is constructed, and the performance limitations of fixed-parameter controllers on precise pole positioning and stable equipment transport during vehicle speed changes are analyzed. On this basis, to address the contradiction between system dynamic response and stable control under mediumand high-speed conditions, a fuzzy adaptive adjustment strategy for time-domain parameters is proposed, combined with an improved particle swarm optimization(PSO) algorithm to achieve online optimization of the weight matrix. Through dynamic matching of the prediction time domain and control time domain as well as real-time adjustment of the weight matrix, the controller's adaptability to power construction tasks under different vehicle speeds is enhanced. Finally, based on a CarSim-Simulink co-simulation platform, double lane change tracking conditions of a pole drilling and erecting machine under typical power construction paths are simulated. Experimental results show that the proposed control method reduces the maximum lateral deviation by 81.4% and 55.1% under medium-and high-speed conditions, respectively, significantly improving trajectory tracking accuracy and comprehensive control performance during pole erection and equipment transport.

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Analysis Method of Low Voltage Distributed Photovoltaic Coupling Impedance Characteristics Under Asymmetric Faults in Medium Voltage Distribution Lines

YU Haidong, LIU Yang, WANG Feng, HUANG Min, LIU Wenbin

2026, 46(4):  89-95.  doi:10.3969/j.issn.1008-0198.2026.04.012

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To address the lack of quantitative analysis regarding line resonance and directional protection misoperation caused by sudden impedance changes of low-voltage grid-connected photovoltaic(PV) inverters under voltage asymmetry resulting from phase-to-phase short-circuit faults in medium-voltage distribution lines, an analytical method for inverter positive and negative sequence impedance and quantitative error evaluation considering control loop effects is proposed. Based on the harmonic linearization principle, the analytical models of positive and negative sequence impedance of the inverter, incorporating the phase-locked loop(PLL) and current control loop, are derived, which theoretically clarifies the impedance frequency-domain evolution and multi-frequency coupling mechanisms under asymmetric faults. Hardware-in-the-loop(HIL) simulation experiments based on StarSim are performed to investigate the impedance distortion characteristics under various control parameters and asymmetric voltage amplitudes. The experimental results show that in the dominant frequency band of 100 Hz to 800 Hz, the mean absolute percentage errors(MAPE) of the positive and negative sequence impedance magnitudes between the established model and the measured data are within 5%, and the maximum absolute error(MAE) of the phase does not exceed 5°. These results demonstrate that the proposed analytical model possesses high theoretical calculation accuracy and can accurately reveal the internal physical mechanisms of high-order harmonic back-injection and the polarization angle deviation of protection elements.

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Research on Orderly EV Charging Strategy Based on User Guidance and Multi-Stakeholder Interests

NING Zhihao, WANG Xiaoyuan, ZHU Jiran, XIA Tian, ZHANG Zhidan

2026, 46(4):  96-105.  doi:10.3969/j.issn.1008-0198.2026.04.013

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To address the peak-valley imbalance and safety risks posed to distribution network operations by the disorderly integration of a high proportion of electric vehicles, an orderly charging strategy is proposed for electric vehicles that integrates the quantification of user psychological perceptions with the coordination of multi-stakeholder interests. Firstly, addressing the limitations of traditional demand price elasticity models in capturing users' multidimensional perceptions, fuzzy logic theory and the Weber-Fechner law are introduced to construct a quantitative model for user guidance difficulty,centred on charging price and current multiplier as core inputs, thereby achieving a refined representation of user response willingness. Secondly, based on the heterogeneous interests of the grid, operators, and users, a two-layer Stackelberg game model‘grid (upper layer)-operator-user (lower layer)’is constructed. Aiming to maximise benefits for all parties, the model employs the method of extremes to generate dynamically optimal electricity prices. Finally, case study analysis demonstrates that the proposed strategy effectively smooths load curves, reducing peak-to-off-peak differences by 38.9%. This achieves synergistic growth in grid, operator, and user revenues while enhancing grid operational security and economic efficiency.

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Leakage Identification Method Based on Neutral and Live Line Currents in Residential Electricity Meters

WANG Shaohuai, YIN Youpeng, WENG Wei, JIANG Zhuochen, YIN Yijiang

2026, 46(4):  106-112.  doi:10.3969/j.issn.1008-0198.2026.04.014

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To address the challenges of the high concealment of fixed leakage currents on the consumer side of the meter, low efficiency in on-site troubleshooting, and the limitations of existing methods which rely heavily on monitoring the total residual current of the transformer district and face constraints in practical application, a method for identifying fixed leakage currents based on the neutral and live line currents of residential electricity meters is proposed. This method utilizes only the daily data of the 24-point neutral and live line currents from residential meters to construct a sequence of absolute differences between neutral and live line currents, thereby characterizing the degree of circuit imbalance. The ratio of the difference between adjacent time points and the root mean square deviation from 1 is introduced to construct a difference consistency index. On this basis, a hierarchical analysis strategy is established that combines extreme imbalance criteria, difference amplitude criteria, and difference consistency criteria, and a method combining statistical analysis and ROC curve optimization is adopted to determine key thresholds. Field application results indicate that, among a sample of 40 residential users verified to have leakage currents across four power supply stations, 37 households were successfully identified, achieving a detection rate of 92.50%. The proposed method requires no additional monitoring equipment or transformer substation modifications, demonstrating good engineering practicality and potential for widespread adoption.

Artifical Intelligence and Digitization

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Cable Fault Diagnosis Method Based on Multi-Granularity Koopman Modal Graph Perception Structure

ZHANG Rui, HU Xuguang, DU Hangyuan, ZHAO Jiance

2026, 46(4):  113-120.  doi:10.3969/j.issn.1008-0198.2026.04.015

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To address the strong dependence on model parameters, limited adaptability to non-typical faults, and insufficient interpretability of deep learning-based methods in cable fault diagnosis, a novel cable fault diagnosis approach based on a multi-granularity Koopman modal graph-perception structure is proposed. First, approximate Koopman modes, amplitudes, and growth rates of system signals are extracted via dynamic mode decomposition(DMD) as shallow features to characterize the temporal dynamics of the cable fault diagnosis system. Then, a graph convolutional network(GCN) is constructed to extract deep features from node voltage and current signals under the power grid topology, enabling the modeling of spatial information and local dependencies. Finally, shallow Koopman modal features at both local and global scales are fused with the deep features learned by the GCN to form a composite representation that integrates physical interpretability with data-driven learning, thereby enhancing the model’s robustness and its capability to identify complex and non-typical faults. Simulation results on the IEEE 14-bus system demonstrate that the proposed method outperforms the comparative approaches in terms of diagnostic accuracy and stability. The proposed framework exhibits strong potential for embedded deployment and shows promising engineering applicability in online cable monitoring and intelligent operation and maintenance scenarios.

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Charging Station Layout Optimization Based on Voronoi Diagram and Improved Immune Clonal Selection Algorithm

PENG Shibo, XIAO Hui, LEI Jiale, ZENG Linjun

2026, 46(4):  121-128.  doi:10.3969/j.issn.1008-0198.2026.04.016

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Aiming at the problems of imprecise service scope division and insufficient algorithmic optimization ability in the layout optimization of electric vehicle charging stations, a charging station site selection and capacity determination method based on Voronoi diagram and improved immune clone selection algorithm is proposed. Firstly, a charging station planning model is constructed with the goal of minimizing annual total costs by considering the economics of charging station construction and operation and maintenance, the power constraints of the regional power grid, and the convenience of charging for users. Secondly, a Voronoi diagram is introduced to classify the service scope of the planning area, and the service area is dynamically generated based on the location of charging stations to ensure that the coverage of each station is reasonable and the degree of overlap is controllable. On this basis, the immune clonal selection algorithm is improved by introducing affinity calculation between antibodies and polynomial variation strategy to improve its global search capability and convergence speed, so as to solve the joint optimization problem of charging station siting and capacity determination efficiently. Finally, the effectiveness of the proposed model and algorithm is verified by MATLAB simulation examples, and the results show that the method can reduce the comprehensive cost of charging stations under the premise of satisfying the coverage and grid constraints.

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A Transformer Life Cycle Carbon Emission Measurement Model Based on SSA-LSTM Data Imputation

XIN Cheng, ZHOU Xiaoyu, WANG Shuo, SHI Xinyu, CHEN Tianqiong, HUO Huijuan

2026, 46(4):  129-135.  doi:10.3969/j.issn.1008-0198.2026.04.017

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To achieve accurate measurement of carbon emissions throughout the transformer life cycle and address the issue of missing data, a carbon emission measurement model is constructed. The sparrow search algorithm is introduced to optimize the long short-term memory model(SSA-LSTM) and compensate for missing data in key stages. A typical transformer is used to validate the model, and the results show that the model can accurately calculate carbon emissions across each stage. Among them, the raw material stage has the highest emissions (185.81 tCOe), followed by the operation stage (11.075 tCOe), while the retirement and recycling stage can achieve a carbon reduction of approximately 45 tCOe. The SSA-LSTM model used for imputing missing data outperforms traditional methods, achieving a mean absolute error(MAE) of 0.44 tCOe, a root mean square error(RMSE) of 0.53 tCOe, and a mean absolute percentage error(MAPE) of 2.35%. This study provides a methodological basis for the accurate accounting of carbon emissions across the transformer supply chain life cycle and the imputation of missing data in key links.

Electric Power Prevention and Reduction

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Dynamic Response Characteristics of Transmission Towers Under Collapse Action in the Western Sichuan Mountain Area

REN Zhichao, ZENG Wenhui, REN Guangming, SHEN Guozhuo, TANG Yang

2026, 46(4):  136-143.  doi:10.3969/j.issn.1008-0198.2026.04.018

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Taking the mountainous area of western Sichuan as the study area, this study identifies the distribution characteristics of geological collapse hazards in the region through field investigation and statistical analysis, summarizes two modes of interaction between collapses and transmission towers-impact-collision and traction-and establishes corresponding geomechanical models. Numerical simulation is used to investigate in detail the dynamic response mechanisms of transmission towers and their coupled systems under rockfall impact, revealing the damage threshold of transmission towers and the protective capacity of growth piles under impact. The results show that the dynamic response process can be divided into two stages: elastoplastic indentation and unloading rebound. The damage threshold of the transmission tower is approximately 96 kJ. The damage mode of growth piles changes from localized surface spalling under low impact energy to penetrative perforation under high impact energy, and the energy dissipation mechanism gradually transitions from plastic deformation-dominated to brittle fracture-dominated. The variation in pile-top displacement of growth piles is governed by the respective proportions of energy dissipated by failed concrete elements and the participation of steel reinforcement, and their impact energy capacity can reach 1 500 kJ. Growth piles can be used as a mitigation measure for collapse-induced rockfalls with relatively low post-failure velocity and limited bounce height along transmission line corridors, ensuring the safe and stable operation of transmission engineering.

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Differential Impacts of Ceramic Coatings on Separators for Lithium Iron Phosphate Battery Performance

LIU Jingju, WANG Jiangfeng, CHEN Kuo, CHEN Luojia, CHEN Baohui

2026, 46(4):  144-151.  doi:10.3969/j.issn.1008-0198.2026.04.019

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This study systematically compares the effects of aluminum oxide-coated separator and boehmite-coated separator on the performance of 280 A·h prismatic aluminum-shell lithium iron phosphate batteries. The results show that after 423 cycles, the discharge energy retention rate and energy efficiency of the battery are improved by 0.87 percentage points and 0.39 percentage points, respectively compared to the boehmite-coated separator battery. In three types of abuse tests such as namely overcharging, external heating, and needle puncture, the safety valve opening time, voltage drop time, and thermal runaway triggering time of the 9AS battery are delayed by 1.9~131 min, 1.3~1.8 min, and 0.26~2.04 min, respectively compared to the boehmite-coated diaphragm battery, and the thermal runaway triggering temperature was increased by 2~7.7 ℃. These performance advantages are mainly attributed to the superior ion conductivity, higher electrochemical stability, and stronger mechanical and thermal properties of alumina coatings. This study provides critical data support for the selection of separators and performance optimization of lithium iron phosphate batteries, particularly for applications with high safety and long life requirements such as energy storage systems.

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Experimental Study on the Suppression Effect of Rapid Cooling on Thermal Runaway in LFP Battery Modules

LIU Meilin, WU Chuanping, CHEN Baohui, ZHOU Tiannian

2026, 46(4):  152-158.  doi:10.3969/j.issn.1008-0198.2026.04.020

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Focousing on chain thermal runaway, a typical hazard in energy storage power stations, its heat propagation process and suppression strategies is investigated. Under simulated thermal abuse conditions induced by a heating plate, thermal runaway is triggered in a single cell within an air-cooled battery module. Liquid nitrogen is applied as an emergency cooling medium to evaluate the effectiveness of external rapid cooling in mitigating inter-cell heat transfer. Based on experimental research on thermal runaway suppression in air-cooled modules, this study identifies typical locations of thermal runaway propagation, selects evaluation indicators for thermal runaway and its propagation characteristics, and a temperature change-centric evaluation model is constructed to achieve quantitative assessment of emergency cooling suppression effects. The findings provide theoretical foundations and methodological support for evaluating and optimizing the safety protection of emergency cooling in energy storage power stations.