检索结果-内蒙古大学图书馆

Harmonic State-Space Based AC-Side Impedance Model of MMC and High Frequency Oscillation Characteristics Analysis

energy Engineering 2023年第4期120卷 831-849页

作者： Hui Fang Jingsen Zhou Haozheng Wang Yanxu Wang Hongji Xiang Yechun Xin State Grid Chongqing Electric Power Company Research Institute Chongqing401120China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Northeast Electric Power University) Jilin132012China

Recently,high-frequency oscillation of themodularmultilevel converter(MMC)based high-voltage direct current(HVDC)projects has attracted great *** order to analyze the small-signal stability,this paper uses the harmonic state-space(HSS)method to establish a detailed frequency domain impedance model of the AC-side of the HVDC transmission system,which considers the internal dynamic *** addition,the suggested model is also used to assess the system’s high-frequency oscillationmechanism,and the effects of the MMC current inner loop control,feedforward voltage links,and control delay on the high-frequency impedance characteristics and the effect of higher harmonic ***,three oscillation suppression schemes are analyzed for the oscillation problems occurring in actual engineering,and a simplified impedance model considering only the highfrequency impedance characteristics is established to compare the suppression effect with the detailed impedance model to prove its reliability.

关键词： Modular multilevel converter impedance modeling small-signal stability suppression strategy

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Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

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energy Engineering 2024年第3期121卷 703-728页

作者： Yue Yang Jiarui Zheng Long Cheng Yongnan Zhu Hao Wu Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Siping Suburban Power Supply Company State Grid Jilin Electric Power Co.Ltd.Siping136000China

To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)*** on the traditional distribution network evaluation system,a comprehensive evaluation system has been *** fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid *** analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment *** subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum *** the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different *** setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.

关键词： Distributed PV grid-connected comprehensive evaluation evaluation indicator system combined subjective and objective empowerment TOPSIS-RSR method

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GENERATIVE ADVERSARIAL NETWORKS FOR REMOTE SENSING IMAGE DEHAZING WITH COLOR FEATURE RESTORATION

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International Journal of Innovative Computing, Information and control 2025年第2期21卷 323-338页

作者： Zhao, Liquan Qin, Yuqing Jia, Yanfei Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University No. 169 Changchun Road Jilin132012 China College of Electric and Information Engineering Beihua University No. 3999 Beijing Road Jilin132013 China

Remote sensing images are often affected by atmospheric factors such as haze during the acquisition process, resulting in blurring and low contrast in the collected remote sensing images. This problem impacts the image quality, thereby affecting the analysis of remote sensing images. To mitigate the impact of haze on remote sensing images, a generative adversarial network is proposed. It comprises a generative network and an adversarial network. Firstly, a novel feature extraction module is designed to enhance the capability of extracting useful information from remote sensing images. It enables the network to focus more on regions with dense haze, allowing it to extract more important information while filtering out irrelevant details. Secondly, a residual attention module is designed which can allocate different weights based on varying haze density in the feature map. This module readjusts features outputted by the encoder, facilitating better image restoration. Thirdly, a multi-scale module is also incorporated to extract feature information across various image scales. Lastly, a color feature extraction module is designed to extract color features. The novel feature extraction module, residual attention module, multi-scale module, and color feature extraction module are utilized for constructing the generative network. Besides, an adversarial network is also designed to indirectly enhance the dehazing capability of the generative network. Synthetic and real datasets are used to test six different methods for dehazing remote sensing images, respectively. The proposed method achieves higher PSNR, SSIM, and lower MSE on the synthetic remote sensing dataset. On the other hand, it achieves lower PIQE, BRISQUE, and higher MetaIQA on the real remote sensing dataset. The proposed method has best performance in dehazing remote sensing images than other methods. © 2025, Int. J. Innov. Comput. Inf. control. All rights reserved.

关键词： Generative adversarial networks

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Study on Insulation Characteristics of Moisture in the Buffer Layer of 66 kV AC XLPE Cables 19th

Study on Insulation Characteristics of Moisture in the Buffe...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Cao, Kangyangyong Xing, Hongquan Huang, Dawei Wei, Zhenhao Liu, Shili State Grid Changchun Power Supply Company Jilin China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9789819613861

To address the frequent failure issues caused by defects in the buffer layer of high-voltage cross-linked polyethylene (XLPE) cables, research on buffer layer has become a hot topic at present. This paper first introduces the input impedance model of the 66 kV cable buffer layer and the corrugated aluminum sheath. The water content can change its resistance and capacitance, thereby affecting the resistivity and dielectric constant. Secondly, the paper introduces the intrinsic principles of frequency domain dielectric spectroscopy technology, where changes in water content alter the relaxation time of the Debye model, thereby changing the dielectric loss factor. Then, by conducting resistance and capacitance measurement experiments on a 6 cm long cable buffer layer, the paper derives the resistivity and dielectric constant variation curves. Through dielectric loss factor measurement experiments, it derives the dielectric loss factor curve, demonstrating the correlation between water content and the dielectric loss factor. The paper concludes that the dielectric loss factor curve is more sensitive to insulation conditions at low frequencies. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Dielectric losses

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Study on the Effects of Moisture on Dielectric Loss and Capacitance Parameters of 66 kV AC XLPE Cable Insulation 19th

Study on the Effects of Moisture on Dielectric Loss and Capa...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Cao, Kangyangyong Xing, Hongquan Huang, Dawei Zong, Guanbo Liu, Shili State Grid Changchun Power Supply Company Jilin China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9789819613861

Long-term operation or external forces may cause damage to the outer sheath of the cable, allowing moisture to enter the cable body and affecting the insulation and dielectric performance of the main XLPE insulation of the cable. For 66 kV cables, there are no clear values provided for the changes in the dielectric loss tangent and capacitance after water ingress into the main insulation. Using a self-built experimental platform, dielectric spectroscopy curves were plotted for the main insulation under 1 kV voltage, showing the variation of the dielectric loss tangent with water content and frequency. The unit capacitance changes of the main insulation due to moisture were also measured. The study indicates that at 0.01 Hz, when the water content in the main insulation increases from 0.86% to 1.29%, the dielectric loss tangent value changes by several times. Additionally, this value is not affected by the location of the moisture—whether it is accumulated, evenly distributed, or symmetrically distributed, the dielectric loss tangent remains unchanged. When the volumetric water content increases by 0.48%, the unit capacitance value increases by 0.8%. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Dielectric losses

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

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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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Stackelberg Game for Bilateral Transactions between energy Storage and Wind Farms Considering the Day-Ahead Electricity Market

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energy Engineering 2025年第5期122卷 1645-1668页

作者： Xingxu Zhu Guiqing Zhao Gangui Yan JunhuiLi Hongda Dong Chenggang Li Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Electric Power Research Institute of State Grid Jilin Electric Power Co. Ltd.Jilin130021China

The participation of wind farms in the former energymarket faces challenges such as power fluctuations and energy storage construction *** this end,this paper proposes a joint energy storage operation scheme for multiple wind farms based on a leasingmodel,which assistswind farms in bidding for participation in the former energy market through leasing services,thereby enhancing energy storage efficiency and maximizing economic *** this paper,based on theWeibull probability distribution to portray the uncertainty of wind power,and considering the lifetime capacity loss caused by charging and discharging of energy storage,we construct a bilateral transaction model aiming at maximizing the multi-objective revenue of wind farms and shared energy *** trading strategy is designed based on the Stackelberg game framework and solved jointly by the improved genetic algorithm and interior *** exploring the effects of different lease price intervals on the overall systemperformance,and analyzing the systemstate undermultiple charging and discharging *** results show that a reasonable lease price range can significantly improve the energy storage system utilization and wind *** new ideas to enhance the economic benefits of wind farms and promote the application of shared energy storage,and promotes the wide application of shared energy storage systems.

关键词： energy storage wind power uncertainty energy market stackelberg game leasing price

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FAULT DIAGNOSIS METHOD FOR DC DISTRIBUTION NETWORKS BASED ON SEMITENSOR PRODUCT BAYESIAN NETWORKS 6

FAULT DIAGNOSIS METHOD FOR DC DISTRIBUTION NETWORKS BASED ON...

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6th International Scientific and Technical Conference Relay Protection and Automation, RPA 2023

作者： Wang, He Li, Shiqiang Yu, Huanan Bian, Jing Wei, Bo Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

ISBN: (纸本)9798350382334

关键词： Bayesian networks

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power Source Flexibility Margin Quantification Method for Multi-energy power systems Based on Blind Number Theory

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CSEE Journal of power and energy systems 2023年第6期9卷 2321-2331页

作者： Bai Xiao Jialiang Wang Zhiwen Xiao Gangui Yan Ling Dong Maochun Wang Hongzhi Yang the Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China Chengde Power Supply Company State Grid Jibei Electric Power CompanyChengde 067000China State Grid Qinghai Electric Power Company Xining 810008China

The grid connection of a high proportion of re-newable energy generation increases the uncertainty in power ***,the flexibility margin of different energy sources needs to be quantified to cope with the uncertainty change and maintain the dynamic balance of power system *** this paper,first,the flexibility characteristics of source,net,load and power and load community(PLC)are *** dynamic equilibrium relationship among them is briefly ***,taking into full consideration the complex output characteristics of different energy sources and combining their respective flexibility characteristics,a quantitative model of the power source flexibility margin for thermal power,hydro-power,gas power and concentrating solar power is established.A quantitative model for a power source flexibility margin in PV and wind power based on blind number theory is ***,the calculation method of theoretical power generation capacity,which can reflect different characteristics of output power of various energy sources,is *** actual output power of each power source in each period is ***,a case study shows that the model and method can consider the operating characteristics of different types of power sources,and quickly and accurately quantify the adjustable range of flexibility margins of each power source at different periods of time,which can provide an important basis for evaluating the capacity of renewable energy consumption and the optimal operation of multi-energy power systems(MEPSs).

关键词： Load forecasting multi-energy power system power generation capacity power source flexibility margin

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