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A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

Computers, Materials & Continua 2024年第9期80卷 4497-4512页

作者： Tianqing Yuan Na Li Hao Sun Sen Tan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Department of Electrical Engineering Northeast Electric Power UniversityJilin132012China College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China Center for Research on Microgrids Department of EnergyAalborg UniversityAalborg9220Denmark

To improve the estimation accuracy of state of charge(SOC)and state of health(SOH)for lithium-ion batteries,in this paper,a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm(GA)combined with back propagation(BP)neural network is proposed,the research addresses the issue of data manipulation resulting ***,anomalous data stemming fromcyber-attacks are identified and eliminated using the isolated forest algorithm,followed by data ***,the incremental capacity(IC)curve is derived fromthe restored data using theKalman filtering algorithm,with the peak of the ICcurve(ICP)and its corresponding voltage serving as the health factor(HF).Thirdly,the GA-BP neural network is applied to map the relationship between HF,constant current charging time,and SOH,facilitating the estimation of SOH based on ***,SOC estimation at the charging cut-off voltage is calculated by inputting the SOH estimation value into the trained model to determine the constant current charging time,and by updating the maximum available *** show that the root mean squared error of the joint estimation results does not exceed 1%,which proves that the proposed method can estimate the SOC and SOH accurately and stably even in the presence of false data injection attacks.

关键词： Lithium-ion batteries state of charge state of health cyber-attacks genetic algorithm back propagation neural network

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An Improved Solov2 Based on Attention Mechanism and Weighted Loss Function for Electrical Equipment Instance Segmentation

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Computers, Materials & Continua 2024年第1期78卷 677-694页

作者： Junpeng Wu Zhenpeng Liu Xingfan Jiang Xinguang Tao Ye Zhang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China Baishan Power Supply Company State Grid Jilin Electric Power CoLtd.Jilin134300China

The current existing problem of deep learning framework for the detection and segmentation of electrical equipment is dominantly related to low *** of the reliable,safe and easy-to-operate technology provided by deep learning-based video surveillance for unmanned inspection of electrical equipment,this paper uses the bottleneck attention module(BAM)attention mechanism to improve the Solov2 model and proposes a new electrical equipment segmentation ***,the BAM attention mechanism is integrated into the feature extraction network to adaptively learn the correlation between feature channels,thereby improving the expression ability of the feature map;secondly,the weighted sum of CrossEntropy Loss and Dice loss is designed as the mask loss to improve the segmentation accuracy and robustness of the model;finally,the non-maximal suppression(NMS)algorithm to better handle the overlap problem in instance *** results show that the proposed method achieves an average segmentation accuracy of mAP of 80.4% on three types of electrical equipment datasets,including transformers,insulators and voltage transformers,which improve the detection accuracy by more than 5.7% compared with the original Solov2 *** segmentation model proposed can provide a focusing technical means for the intelligent management of power systems.

关键词： Deep learning electrical equipment attention mechanism weighted loss function

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Multi-task learning and single-task learning joint multi-energy load forecasting of integrated energy systems considering meteorological variations

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Expert systems with Applications 2025年 288卷

作者： Nantian Huang Shicheng Ren Jianfei Liu Guowei Cai Liang Zhang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin 132012 Jilin Province China School of Electrical Engineering Northeast Electric Power University Jilin 132012 Jilin Province China The Economic and Technical Research Institute of State Grid Inner Mongolia Eastern Electric Power Company Hohhot 010010 Inner Mongolia Province China

Accurate multi-energy load forecasting is pivotal for achieving supply–demand balance and enabling economic dispatch in Integrated energy systems (IES). However, prediction accuracy is significantly compromised by meteorological fluctuations, seasonal coupling variations, and multi-energy interactions affecting multi-energy loads. This study proposes a joint multi-energy load forecasting framework integrating meteorological variation rate features with multi task learning (MTL) and single task learning (STL). First, historical load variation rates and meteorological variation rates are calculated, with rapid maximal information coefficient (RapidMIC) employed to identify dominant meteorological variation rates influencing multi-load fluctuations. Subsequently, a weighted average of correlation analysis method quantifies both linear and nonlinear impacts of meteorological variation rates on load fluctuations, enabling precise screening of critical meteorological input features. Second, addressing potential accuracy degradation in MTL models caused by coupling strength disparities among multi-energy loads, a joint forecasting method based on MTL-STL is proposed to enhance prediction precision. Furthermore, a loss function optimization strategy combining homoscedastic uncertainty (HU) and dynamic weight averaging (DWA) achieves real-time weight allocation in MTL. Finally, validation through case studies on IES at Arizona State University (ASU) and an industrial park in Gansu Province, China demonstrates the model’s effectiveness and generalizability: Across all seasons, MAPE values for electricity, cool, and heating loads remain stable within 1.068%-3.022%, 1.877%-5.331%, and 1.697%-3.999% respectively.

关键词： Multi-task learning

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An Optimized control Strategy for Distributed energy Storage system to Reduce the Peak-valley Difference of Distribution Network 4

An Optimized Control Strategy for Distributed Energy Storage...

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4th IEEE China International Electrical and energy Conference, CIEEC 2021

作者： Saren, Gaowa Sun, Zhebin Liang, Tao Li, Hengzhen Liu, Pengxuan Ma, Dexuan Zhang, Hao Sun, Dapeng Yan, Jiaqi Li, Cuiping Li, Junhui Inner Mongolia Power Technology Research Institute Hohhot China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Ministry of Education Jilin China

ISBN: (纸本)9781728171494

Accompanied by energy structure transformation and the depletion of fossil fuels, large-scale distributed power sources and electric vehicles are accessed to distribution network that result in the load peak-valley gap increasing. energy storage system (ESS) possessed the characteristics such as quick response, precise control and energy bidirectional flow. Therefore, the configuration of ESS in grid is a feasible measure to reduce the difference between peak load and valley load. This paper presents a superior control strategy that uses distributed energy storage to smooth load fluctuation of grid. Set the time scale to one day, constraints such as energy storage capacity, power and state of charge are taken into account, and the calculation examples are designed based on the proposed the evaluation index compares the effect of optimized control strategy given in this paper with the current common constant power strategy, which proves the feasibility and effect of the presented method. © 2021 IEEE.

关键词： simulation platform

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Antenna Design Based on Minkowski Like Fractal Structure 19

Antenna Design Based on Minkowski Like Fractal Structure

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19th International Conference on Optical Communications and Networks, ICOCN 2021

作者： Zheng, Xuemei Li, Songqi Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China College of Electrical Engineering Northeast Electric Power University Jilin China

ISBN: (纸本)9781665424462

Antenna is widely used in wireless communication equipment, which is developing towards miniaturization and high frequency. The application of fractal theory in antenna design can make the antenna more miniaturized and multifrequency, so the research of fractal microstrip antenna has very important theoretical significance and practical value. Based on Minkowski like fractal structure, a dual band fractal microstrip antenna is designed, which works in WLAN and WiMAX band. The center frequency is 2.4GHz and 2.7GHz, and the isolation near the center frequency is more than 15dB. © 2021 IEEE.

关键词： Fractals

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Short-Term Prediction of Wind Farm Cluster power Based on Load Risk Scenarios and Improved Weighted Loss During Peak and Valley Load Periods 7

Short-Term Prediction of Wind Farm Cluster Power Based on Lo...

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7th IEEE Conference on energy Internet and energy system Integration, EI2 2023

作者： Yang, Mao Guo, Yunfeng Wang, Bo Wang, Zhao Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin132012 China China Electric Power Research Institute National Key Laboratory of Renewable Energy Grid-Integration Beijing100192 China

ISBN: (纸本)9798350345094

Load peak and valley periods as the key scheduling scenarios, the effectiveness of wind power prediction becomes extremely important, in order to minimize the impact of wind power on the power system due to prediction errors, a short-term prediction method of wind farm cluster power considering risk scenarios and improved loss function is proposed. Firstly, the coupled correlation mechanism between meteorological type and load demand is explored, and the load risk scenario and meteorological correlation are derived. Second, according to the risk scenarios of load demand, the traditional loss function is improved and used to train the power prediction model under the risk scenarios. Then, a dynamic division strategy of wind farm clusters considering the meteorological similarity of the previous day is proposed to obtain the sub-clusters of similar output. Finally, the model with improved weighted loss function is used to predict the wind power for different regional sub-clusters and extended to wind farm clusters. The above method is validated using the wind farm clusters in West Inner Mongolia, China. and the results show that in the low-risk load scenario, the accuracy of the model with improved loss is higher, and the accuracy decreases with the increase of the load risk level, but the overall risk indexes are significantly lower than the method with traditional loss function, which proves the validity of the proposed method. © 2023 IEEE.

关键词： Risk assessment

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A Novel Directional Pilot Protection for Flexible DC Distribution Grid 9

A Novel Directional Pilot Protection for Flexible DC Distrib...

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9th Asia Conference on power and Electrical Engineering, ACPEE 2024

作者： Wei, Xiuyan Zou, Guibin Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Ji'nan250061 China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin132012 China

ISBN: (纸本)9798350309638

The existing directional pilot protection (DPP) is susceptible to the line distributed capacitance and the fault resistance, and mostly rely on the current limiting reactance (CLR) at the line ends. To solve the above problems, the line-mode fault component power (LFCP) based DPP is proposed for flexible DC distribution grid (FDCDG). First, the characters of LFCP are discussed under different faults. The theoretical analysis show that the polarity of the LFCP under internal fault is same, while the polarity of the LFCP is opposite under external fault. Then, the LFCP is built as the directional criterion, and the corresponding protection scheme is constructed. The electromagnetic transient simulations of the PSCAD/EMTDC verify that the proposed DPP is less affected by the noise, and has low requirement on the sampling rate, strong engineering applicability. © 2024 IEEE.

关键词： Electric power distribution

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CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

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Computers, Materials & Continua 2024年第8期80卷 2857-2872页

作者： Chun-Ming Wu Mei-Ling Ren Jin Lei Zi-Mu Jiang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationSchool of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China School of Electronic Information Engineering Bozhou UniversityBozhou236800China

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is *** region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature *** the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image *** study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional *** methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other *** algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)*** experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

关键词： Image fusion deep learning auto-encoder(AE) infrared visible light

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Economic Analysis and Visual simulation Platform Construction of Distributed energy Storage on Load Peak-shaving and Valley-filling in Distribution Network 4

Economic Analysis and Visual Simulation Platform Constructio...

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4th IEEE China International Electrical and energy Conference, CIEEC 2021

作者： Sun, Zhebin Saren, Gaowa Liang, Tao Li, Hengzhen Liu, Pengxuan Sun, Dapeng Yan, Jiaqi Ma, Dexuan Zhang, Hao Li, Cuiping Li, Junhui Inner Mongolia Power Economic Technology Research Institute Hohhot China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Ministry of Education Jilin China

ISBN: (纸本)9781728171494

This paper proposes an economic analysis method for distributed energy storage applications in distribution networks, and constructs a visual simulation platform. Firstly, the influence of photovoltaic / wind power fluctuation on load peak-valley difference in distribution network under different permeability is analyzed, and the technical and economic characteristics of different distributed energy storage systems are compared. Secondly, in order to facilitate the analysis and display the analysis results, a visual simulation platform is constructed based on MATLAB / Simulink software. The simulation results of IEEE 33-Bus system show that the method described in this paper can effectively analyze the economy of load peak-shaving and valley-filling by different energy storage configuration methods, and the visualization platform can clearly and intuitively show the results of the above analysis method. © 2021 IEEE.

关键词： MATLAB

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Dynamic Behavior of Suspended Bubbles in Insulating Oil Correlation with Flow Field Distribution 4th

Dynamic Behavior of Suspended Bubbles in Insulating Oil Corr...

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4th International Symposium on Insulation and Discharge Computation for power Equipment, IDCOMPU 2023

作者： Zhang, Ning Hao, Jian Liu, Shili Zhang, Junyi Chen, Houhe Liao, Ruijin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9789819974122

In recent years, arcing faults inside large oil-immersed power transformers have been frequent. Suspended bubbles, as the main product of high temperature, high humidity, material aging and cracking gas production inside transformers, are one of the main causes of arcing inside transformers. However, due to the complex structure of the oil channel and the large fluctuation of the internal flow field distribution, the resulting bubble morphology evolution and movement law is not clear. In this paper, the influence of the initial position of bubbles and the relative position between bubbles on the flow field distribution is fully considered, and the dynamic behavior of suspended bubbles in oil under two fluid forms of natural oil circulation and forced oil circulation is simulated and studied by combining laminar and turbulent flow models and bubble force control equations, and the correlation mechanism between suspended bubbles and flow field distribution characteristics is analyzed. The simulation results show that the flow field in the laminar state affects the bubble aggregation and trajectory, while the turbulent state affects the bubble distortion and motion time, and a reasonable model in the simulation of bubble dynamic behavior is more beneficial to improve the simulation accuracy. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Flow fields

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