Table of Content

25 February 2025, Volume 45 Issue 1

Previous Issue   

For Selected:

Download Citations EndNote Reference Manager ProCite BibTeX RefWorks

Expert Column:Key Technologies and Applications of Electrochemical Energy Storage Systems

Select

Research on Battery Life Prediction Based on Early Aging and Transfer Learning

YANG Tian, SHEN Jinran, GUAN Yibiao, GAO Fei, JIANG Tian, LIU Qing

2025, 45(1):  1-7.  doi:10.3969/j.issn.1008-0198.2025.01.001

Asbtract ( 67 )   PDF (6633KB) ( 42 )  

References | Related Articles | Metrics

To address the problems of insufficient reliability and poor generalization in life prediction of energy storage batteries, a large-capacity energy storage battery remaining life prediction method based on LSTM is proposed, which only adopts the early aging data of the batteryfrom the first 150 cycles as the inputand realizes accurate prediction of the remaining life of energy storage batteries through the model training method of the sliding-window method. This approach achieves a remarkable root mean square error (RMSE) of 0.11% over a full national standard testing period of 1000 cycles. Additionally, a transfer learning module is developedand for the new model of energy storage batteries, the 150th to 250th cycles are used for the migration correction of the basic model, which reduces RMSE of the battery life prediction from 0.50% to 0.10%. This advancement enhances the generalization of the life prediction model, providing a solution for the practical application of the life prediction technology in the field of energy storage battery production, testing and evaluation.

Select

SOH Evaluation of Electrochemical Energy Storage Batteries Based on Operational Data

GENG Mengmeng, FAN Maosong, GUAN Yibiao, WEI Bin

2025, 45(1):  8-13.  doi:10.3969/j.issn.1008-0198.2025.01.002

Asbtract ( 46 )   PDF (4921KB) ( 25 )  

References | Related Articles | Metrics

To address the issue of limited accuracy of state of health (SOH) of electrochemical energy storage batteries evaluation, firstly, through the analysis of data correlation, the voltage variation values in 10 minutes after the voltage reaches 3.25 V, 20 minutes before reaching 3.35 V and 30 minutes before reaching 3.4 V during the charging process are selected as health factors. These factors are utilized as input parameters of the model in a long short-term memory neural network optimized through genetic algorithms to facilitate SOH assessment for energy storage batteries. To validate the effectiveness of this evaluation method, five soft pack LiFePO4 batteries are subjected to cyclic aging experiments, obtaining health factors alongside actual SOH values for model development. The evaluation results are then compared with the actual SOH values obtained from testing. The evaluation results are quantified using mean square error (MSE) and mean absolute percentage error (MAPE), which shows that the SOH evaluation of the model is accurate,and MSE and MAPE are reduced by 48.3% and 74.1% respectively, compared with the unoptimized long short-term memory neural network.

Select

Platform Designing and Realization on Lithium-Ion Battery Health StatePrediction Based on Single and Multivariate Features

ZHOU Chidong, YU Jing, YU Yajuan, CHANG Zeyu, CHEN Lai, SU Yuefeng

2025, 45(1):  14-20.  doi:10.3969/j.issn.1008-0198.2025.01.003

Asbtract ( 43 )   PDF (5908KB) ( 26 )  

References | Related Articles | Metrics

A hybrid model combining single and composite features is proposed to address the problem of the state-of-health(SOH) assessment and remaining useful life (RUL) prediction of lithium-ion batteries. This method first uses the EEMD-LSTM-LightGBM model to effectively predict battery capacity regeneration by analyzing capacity degradation curves, and the goal that the error of RUL is less than 2 cycles and root mean square error(RMSE) SOH prediction is as low as 1.2%. Secondly, a gradient boosted desicion tree model based on composite features is developed, where feature selection is performed through correlation analysis and principal component analysis, and hyperparameters are optimized, resulting in an SOH prediction accuracy with an RMSE of 0.014. Next, based on these algorithms, a lithium-ion battery SOH prediction platform is developed on a local server, integrating both single and multi-feature models. It provides a user-friendly interface that visually displays key indicators such as capacity degradation curves and prediction errors. The experimental results show that through innovative feature extraction and algorithm integration the proposed method, significantly improves the accuracy of lithium-ion battery SOH assessment and RUL prediction, which can be used as a reference for the development and application of related platforms.

Select

Research Progress and Prospects of Insulation Coating Material for Lithium-Ion Battery

LAI Yilin, MA Xiaoming, QU Zhanzhan, LIU Hao, ZENG Xing

2025, 45(1):  21-28.  doi:10.3969/j.issn.1008-0198.2025.01.004

Asbtract ( 46 )   PDF (7768KB) ( 17 )  

References | Related Articles | Metrics

With the development of energy storage systems towards high voltage, the existing insulation protection measures for lithium-ion storage batteries are facing severe challenges. Based on the characteristics of PET blue film insulation coating material currently used in lithium-ion batteries, the causes of insulation coating material failure in batteries are analyzed from two aspects of material aging and external impact, and a risk analysis of insulation coating material failure is conducted. On this basis, a coating material system suitable for battery insulation protection is explored, and the advantages and disadvantages of epoxy system, phenolic system, polyester system, hot melt adhesive system and polyimide system are analyzed, providing new ideas for insulation coating materials research.

Select

Acoustic Characterization of Lithium-Ion Batteries State of Charge Based on Flexible Piezoelectric Fiber Array

LIU Xuan, LYU Yan, GAO Jie

2025, 45(1):  29-36.  doi:10.3969/j.issn.1008-0198.2025.01.005

Asbtract ( 40 )   PDF (9996KB) ( 16 )  

References | Related Articles | Metrics

Lithium-ion batteries under complex service conditions are prone to local abnormal state of charge(SOC) problems, which seriously affects their safety and stability.Traditional electrical measurement methods are difficult to fully evaluate the distribution of health status of lithium-ion batteries in multiple regions, which can easily lead to missed detection of local weak performance areas or potential abnormal state areas of individual cells.To address the above issues, a ultrasonic guided wave detection method based onpiezoelectric fiber array is proposed. The acoustic characteristic parameters of lithium-ion batteries in different regions are experimentally extracted to explore the distribution differences of lithium-ion batteries SOC in different regions. Subsequently, a complete database is formed by combining acoustic and electrical characteristic parameters, and a neural network intelligent inversion model is used to quantitatively evaluate SOC with an error of less than 0.25%. The proposed detection method can provide a new technical solution for nondestructive quantitative evaluation of lithium-ion batteries SOC.

Source and Grid Coordination ＆ Conversion and Utilization

Select

A Review of Unit Commitment in High Proportion Renewable Energy Power Systems

CUI Yiyang, LI Canbing, PAN Dounan, LI Zhenkai, LIU Hang

2025, 45(1):  37-45.  doi:10.3969/j.issn.1008-0198.2025.01.006

Asbtract ( 34 )   PDF (7859KB) ( 18 )  

References | Related Articles | Metrics

As a key link in the clearing of the power market, unit commitment(UC) is of great significance for preparing power generation plans and ensuring the safe and economic operation of the power systems. With the construction of a unified national power market and the increasingly complex operating environment of power grids, the requirements for optimal operation of power systems continue to increase, and the research and application of UC problems have received increasing attention and concern.In this context,the modes, mathematical models and solving methods of UC are summarized, an overview of its current applications at home and abroad is provided, the challenges faced by unit commitment nowadays are analyze, and its future developmentis anticipated.

Select

Research on Investment Benefits Calculation of Conventional Pumped Storage Projects Based on Regional Power Supply and New Energy Consumption

QIN Zhengbin, ZHANG Wuyin, TIAN Haiping, CHEN Yanqi

2025, 45(1):  46-53.  doi:10.3969/j.issn.1008-0198.2025.01.007

Asbtract ( 34 )   PDF (6272KB) ( 8 )  

References | Related Articles | Metrics

The economic benefits of pumped storage power plants can be effectively assessed by measuring the investment benefits of conventional pumped storage projects that take into account the needs of regional power grids and new energy sources to maintain power supply. Firstly, a large-scale conventional pumped storage power plant in operation is fully investigated, and based on the actual data, its operation conditions are introduced, its operation characteristics in different seasons are analyzed, and the participation of the power plant in the electricity market is introduced.Secondly, the initial investment cost, the operation cost, and various types of income of the pumped storage power plant are measured, and the economic indicators of the system under different utilization hours are analyzed.Finally, based on the measured data, the social and economic benefits of the calculations are further studied from the dimensions of power supply protection benefits, new energy consumption benefits, etc. The results show that the pumped storage power plant has excellent operational benefits and social benefits, which can provide a certain reference for the actual pumped storage investment calculations and economic benefits calculations.

Select

Comparative Analysis of Aggregation Boosting Methods for Offshore Wind Power HVDC Power Transmission

GAO Yue, CHEN Heng, WANG Zhengwei, LEI Jing

2025, 45(1):  54-60.  doi:10.3969/j.issn.1008-0198.2025.01.008

Asbtract ( 37 )   PDF (6483KB) ( 19 )  

References | Related Articles | Metrics

With the gradual development of offshore wind farms to the deep and distant ocean and the increasing single machine capacity of wind turbine generator in offshore wind farms, problems such as changeable operating environment and increasing construction difficulty of offshore wind farms also arise.Aiming at these problems, a variety of aggregation boost methods of offshore wind power under the condition of HVDC transmission are theoretically analyzed. From the perspective of the economy and energy loss, the construction cost of each program and energy loss in the process are calculated respectively by applying several aggregation boost methods to practical concrete engineering cases. The calculation results are summarized, and the influence of different voltage levels and power types on the offshore wind power collection system is compared and analyzed, and the advantages of DC aggregation boost system in the future development of offshore wind power are proved.

Select

Analysis of Load Regulation Characteristics for Cement Industry

REN Bing, WANG Yi, LIU Chaozhi, LENG Jiehua, DAI Zhongzhi, PENG Deya

2025, 45(1):  61-67.  doi:10.3969/j.issn.1008-0198.2025.01.009

Asbtract ( 31 )   PDF (7011KB) ( 10 )  

References | Related Articles | Metrics

The precise assessment of the dispatchable potential of high energy-consuming industries, the establishment of dispatch models, and the optimization of dispatch strategies can meet the refined requirements of power load management. The article focuses on users in the cement industry in the Yongzhou region and conducts in-depth research and analysis. By using a three-level load classification method, a power load model for the cement industry is constructed, systematically reflecting the load characteristics of this industry. By combining actual data, a simulation study and verification of the segmental rotation stop mode in the cement industry is conducted. The results indicate that the load adjustment strategy based on time-of-use electricity pricing is effective in peak shaving and valley filling, providing strong theoretical support for the optimization of the load model in the cement industry.

Select

Research on Electricity Prediction Model of Power Purchasing Agent Based on K-means Clustering Algorithm and BP Neural Network

YU Zhicheng, MU Shicai, LIANG Ye, LI Jiachen, LIN Hua, CHEN Jichen, JIN Xin

2025, 45(1):  68-72.  doi:10.3969/j.issn.1008-0198.2025.01.010

Asbtract ( 44 )   PDF (4161KB) ( 20 )  

References | Related Articles | Metrics

Through the in-depth portrait analysis of power purchasing agents in a certain region, the influence of different factors on the power consumption of power purchasing agents is studied, and the classification of user groups is realized through the clustering algorithm. Through the neural network algorithm, the longitudinal time series electricity and horizontal influencing factors are incorporated into the prediction formula, and the prediction models conforming to the characteristics of different clusters are constructed. Finally, the models are integrated to achieve high accuracy prediction of the overall electricity.

Power Grid Operation and Control

Select

Simulation Study on White Powder Ablation Characteristics in Buffer Layer of High-Voltage Cross-Linked Polyethylene Cables

ZHONG Lipeng, LIU Yufeng, DUAN Xiaoli, LIU Sanwei, LI Wenjie, LI Shaobin, GAO Zhiyi, LI Bin

2025, 45(1):  73-78.  doi:10.3969/j.issn.1008-0198.2025.01.011

Asbtract ( 50 )   PDF (5776KB) ( 12 )  

References | Related Articles | Metrics

Aiming at the ablation of the buffer layer of high-voltage cross-linked polyethylene (XLPE) cables, the influence of white powder produced by the moisture in the buffer layer on the ablation condition of the radial current concentration of the buffer layer of the cables is explored, and the degree of distortion of the electric field at the defects of the buffer layer of the cables in this condition are investigated. Using mult-physical field simulation software, a three-dimensional electro-thermal field simulation of the cableis is conducted to analyze the impact of the white powder on the internal electro-thermal field distribution of the cable. The results show that buffer layer is affected by water ingress and moisture, and the chemical reaction between water molecules and buffer layer and aluminum sheath couses the ablation of buffer layer of the cableis. At the same time, it intensifies the degree of distortion of the electric field near the defects of the buffer layer of the cable under the condition of radial current concentration ablation, which easily leads to partial discharge and subsequently triggers ablation.

Select

Research Progress of Nano-Modification Effect on Polyimide Films Properties

ZHANG Liang, ZHANG Shumeng, LIU Daosheng, XIN Rong

2025, 45(1):  79-85.  doi:10.3969/j.issn.1008-0198.2025.01.012

Asbtract ( 44 )   PDF (6013KB) ( 13 )  

References | Related Articles | Metrics

In order to meet the requirements of insulation properties of rapidly developing electric power equipment, the research achievements on electrical, thermal and mechanical properties of polyimide films by domestic and foreign researchers are reviewed. The research achievements and engineering applications of nano-particle modification technology on thermal conductivity, thermal insulation, transparency, mechanical properties, corrosion resistance and electrical properties of polyimide films are summarized.

Select

CNN-LSTM Power System Load Prediction Based on Embedded Wavelet

WANG Caiqian, HU Qian, MIAO Wenjie, LU Shenxiong

2025, 45(1):  86-92.  doi:10.3969/j.issn.1008-0198.2025.01.013

Asbtract ( 46 )   PDF (7176KB) ( 10 )  

References | Related Articles | Metrics

To address the issue of the accuracy of power consumption prediction at the load end in power systems, a prediction method combining convolutional neural networks and long short-term memory networks is proposed. By utilizing the principle of wavelet transform, the downsampling method in the convolutional neural network is improved, allowing time-frequency characteristicsinformation to be theoretically preserved and enhanced during the downsampling process. Experiments are conducted using actual power consumption data, and the results show that compared with traditional methods, the proposed method significantly improves various evaluation index and the accuracy of short-term load prediction.

Select

Remote Decomposition Method for Residential Load Based on Improved K-means++ and LSTM algorithm

LIAO He, YU Wei, XIONG Zheng, DOU Longlong, ZHOU Guanheng

2025, 45(1):  93-99.  doi:10.3969/j.issn.1008-0198.2025.01.014

Asbtract ( 36 )   PDF (7395KB) ( 18 )  

References | Related Articles | Metrics

In response to the large number of low-voltage residential users and the high cost of installing additional monitoring equipment or upgrading existing monitoring equipment, an improved K-means++ and long short-term memory algorithm based on advanced measurement system for large-scale minute level data collection is proposed for remote load decomposition of residents. Firstly, in order to capture changes in data more accurately and efficiently, and in real-time a sliding window based bilateral accumulation and algorithm monitoring is designed. Secondly, in order to identify representative loads and ensure computation speed, an improved K-means++ algorithm is adopted. Finally, using long short-term memory algorithms, data that undergoes regular changes over time are captured to complete load decomposition. At a low sampling frequency of 1 minute, the applicability of the proposed algorithm is fully validated through the collection of daily load data from residents.

Select

Diagnosis Method of Mechanical Defects in GIS Disconnector Based on Drive Motor Power

LIN Zizhao, LIN Fengyi, FENG Yuhui, YU Huang, YE Weijie, LIU Yufei, CHENG Shunli

2025, 45(1):  100-105.  doi:10.3969/j.issn.1008-0198.2025.01.015

Asbtract ( 40 )   PDF (5042KB) ( 13 )  

References | Related Articles | Metrics

To address the safety hazards of GIS disconnector, the physical relationship between motor power and GIS contact position is established by analyzing the mechanical structure of GIS disconnector, and test platform is built. When there is a jamming defect, the power amplitude of the entire process increases. A meshing point identification method based on multi-window slope is proposed to realize the segmentation of power curves, and then the diagnosis of the mechanical state of GIS disconnector is realized according to empirical comparison. The online monitoring case proves that the accurate judgment of the mechanical state and the opening and closing position of GIS disconnector can be realized by motor power in engineering.

Select

Effects of Different Moisture Intrusion Directions on Insulation Performance of Resin Impregnated Paper Bushing Core

ZHANG Cheng, CAI Guangyi, YOU Shaohua, XU Zuoming, LIU Taiwei

2025, 45(1):  106-111.  doi:10.3969/j.issn.1008-0198.2025.01.016

Asbtract ( 43 )   PDF (7915KB) ( 13 )  

References | Related Articles | Metrics

In order to study the effects of different moisture intrusion directions on the insulation performance of resin impregnated paper(RIP) bushing core, four types of test blocks with different directions of insulating varnish protection are prepared by utilizing real RIP bushing core, and the parameters such as dielectric loss factor(tanδ), capacitance, insulation resistance and frequency domain dielectric spectroscopy(FDS) of the blocks are measured at different humidity levels. The results show that tanδ, capacitance and insulation resistance have small and slow changes in light moisture, while they show cliff-like changes in heavy moisture, and tanδ and insulation resistance are more sensitive to moisture than capacitance.Due to the hindering effect of aluminum foil on moisture, the axial moisture of the RIP bushing core has a greater effect on the insulating performance than the radial moisture, and the difference becomes more significant with the increase of the degree of moisture. The results can provide a reference for the evaluation of moisture intrusion of RIP bushing.

Distribution Network and Using Energy Technology

Select

Multi-Time Scale Control Technology for Flexible Resources in Distribution Networks Within Voltage-Load Regulation Framework

AO Fei, YU Bin, LI Zukun, WU Jinbo, HU Sijia, LI Yong

2025, 45(1):  112-120.  doi:10.3969/j.issn.1008-0198.2025.01.017

Asbtract ( 40 )   PDF (8655KB) ( 9 )  

References | Related Articles | Metrics

Aiming at the problems of limited voltage adjustment margin, high penetration rate of variable frequency air conditioners and their low sensitivity to voltage changes for conservation voltage reduction(CVR) technology, a multi-time scale control technology for flexible resources in distribution networks within the framework of voltage-load regulation is proposed. Firstly, CVR is modeled and its energy-saving benefits in the distribution network are analyzed. Secondly, a load model for variable frequency air conditioners is established to assess its regulation and control potential. On this basis, a multi-time scale optimization control strategy for the distribution network is proposed and formulated. In the day-ahead scheduling phase, the regulation and control schemes for onload tap changers(OLTC), air conditioning loads, and distributed resources are planned in advance to reduce the peak regulation pressure of the distribution network on the upper grid. In the intra-day optimization phase, in response to potential voltage limit violations, the OLTC gear is adjusted in real time, and flexible and adjustable resources in the distribution network are controlled in real time based on electrical distance to realize rapid recovery of grid voltage, thereby enhancing the stability and robustness of the system. Finally, a case study based on the IEEE 33-node system is conducted to verify the effectiveness of the proposed strategy.

Select

Improved Dual-Vector Model Predictive Torque Control Strategy Based on Extended Sliding-Mode Disturbance Observer for Permanent Magnet Synchronous Motor

LI Xiaobao, LIU Juntao, ZHOU Weilong, LIANG Denghui, LONG Huan, ZHAO Zhe, LUO Zhaoxu

2025, 45(1):  121-129.  doi:10.3969/j.issn.1008-0198.2025.01.018

Asbtract ( 46 )   PDF (7222KB) ( 12 )  

References | Related Articles | Metrics

Aiming at the problems of large computation, obvious torque fluctuation, and prediction error due to parameter mismatch in traditional dual-vector model predictive torque control for permanent magnet synchronous motor, an improved dual-vector model predictive torque control strategy based on novel extended sliding-mode disturbance observer is proposed. Firstly, in order to reduce the control computation, a fast voltage vector selection tableis proposed with a graph of 12 sector voltage vector, the number of iterations is greatly reduced from 14 to 3. Then, to address the undesirable effects of motor parameter mismatch, the stator inductance value is estimated by the amount of error variation between the predicted and actual measured values at adjacent moments, the inductance updating mechanism is integrated, and a novel extended sliding-mode observer is proposed to enhance the robustness of the prediction model in the case of parameter mismatch. The MATLAB/Simulink simulation results show that the proposed strategy can reduce the rotor torque volatility, effectively reduce the unfavorable influence of the parameters change, and improve the stability of the prediction model.

Select

Power Coordination Control Strategy for Islanded Hybrid Microgrid Group Based on Droop Control

ZHI Ming, YANG Fei, FU Rui, ZOU Jie, CHEN Xiao, XIA Lei, XU Xun

2025, 45(1):  130-135.  doi:10.3969/j.issn.1008-0198.2025.01.019

Asbtract ( 37 )   PDF (7399KB) ( 21 )  

References | Related Articles | Metrics

Interconnecting multiple AC/DC hybrid microgrids to form a hybrid microgrid cluster is a common way to supply loads, and how to utilize the autonomy of the sub-microgrids and realize the interactive power support between sub-microgrids is one of the key issues in AC/DC hybrid microgrid cluster power management. For this reason, this paper proposes a power management strategy consisting of three layers: power autonomy control layer of subgrids, power interaction support layer between neighboring subgrids, and power balance layer of the hybrid microgrid cluster for the AC/DC hybrid microgrid cluster with islanded operation. The coordinated control among the three layers can effectively improve the power supply reliability and quality of the isolated AC/DC hybrid microgrid cluster and reduce the power loss of the microgrid cluster. Finally, the proposed control strategy is verified by building an experimental platform, and the experimental results show that the proposed strategy has better robustness under normal communication and communication failure.

Artifical Intelligence and Digitizatrion in Electrical Power

Select

Light Weight Visual Recognition Method of Small Target Hardware for Transmission Lines Based on Improved YOLO Algorithm

ZOU Dehua, ZHANG Hongwei, JIANG Wei, GONG Chuang

2025, 45(1):  136-143.  doi:10.3969/j.issn.1008-0198.2025.01.020

Asbtract ( 64 )   PDF (7320KB) ( 32 )  

References | Related Articles | Metrics

Aiming at the problem that deep learning-based transmission line hardware detection methods can not ensure the lightweight model while improving the detection accuracy of small targets, a lightweight detection method for small target hardware on transmission lines is proposed. Based on YOLOv4, the method firstly combines density-based spatial clustering of applications with noise and the anchor frame optimization strategy with multiple K-means to optimize the preset frame selection according to the characteristics of the small target data, speed up the network convergence and improve the detection accuracy. Secondly, GhostnetV2 is used to achieve model light weighting. Then the network of small object enhanced multi-scale detection network, is designed to enhance the feature extraction ability, strengthen the fusion of shallow and deep features, and solve the problem of feature loss caused by down sampling cross-step convolution. Finally, focal loss function is used to optimize sample allocation and depth-wise separable convolution is used to reduce model complexity. The mean average precision(mAP) of this algorithm on the self-constructed small hardwaredataset reaches 64.73%, and the model computation and parameter counts are reduced by 78% and 71% compared to the pre-improvement period, while there is almost no loss of detection accuracy. The mAP reaches 38.43% on the public dataset VisDrone2019, which gives the algorithm a superiorsmall target detection performance compared to other algorithms.

Select

Research on Miniaturization Device for Ultra-High Frequency Partial Discharge Detection Carried by Unmanned Aerial Vehicles

DENG Wei, ZHONG Yuming, LIU Weidong, TANG Xin, WEI Shaodong, YANG Wentao

2025, 45(1):  144-148.  doi:10.3969/j.issn.1008-0198.2025.01.021

Asbtract ( 47 )   PDF (6605KB) ( 14 )  

References | Related Articles | Metrics

Aiming at the problem that UHF partial discharge detection device carried by UAV is affected by the charged distance of substation equipment, it is necessary to miniaturize the device from the three aspects of small sensors, expansion interfaces and data processing. By combining laboratory and on-site test results, PRPD-PRPS spectra of three types of discharges are obtained, including suspended, tip and surface discharge. The relationship between discharge signals and distance is studied, and the device is verified to have good sensitivity, high reliability and convenient operation at the substation site. This device can provide a reference for the UHF detection method through UAV and a new method of intelligent inspection for partial discharge of power equipment.