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Fault Diagnosis Method of Rolling Bearing Based on MSCNN-LSTM

Computers, Materials & Continua 2024年第6期79卷 4395-4411页

作者： Chunming Wu Shupeng Zheng Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Ministry of Education Northeast Electric Power UniversityJilin132012China

Deep neural networks have been widely applied to bearing fault diagnosis systems and achieved impressive success *** address the problem that the insufficient fault feature extraction ability of traditional fault diagnosis methods results in poor diagnosis effect under variable load and noise interference scenarios,a rolling bearing fault diagnosis model combining Multi-Scale Convolutional Neural Network(MSCNN)and Long Short-Term Memory(LSTM)fused with attention mechanism is *** adaptively extract the essential spatial feature information of various sizes,the model creates a multi-scale feature extraction module using the convolutional neural network(CNN)learning *** learning capacity of LSTM for time information sequence is then used to extract the vibration signal’s temporal feature *** parallel large and small convolutional kernels teach the system spatial local *** gathers temporal global features to thoroughly and painstakingly mine the vibration signal’s characteristics,thus enhancing model ***,bearing fault diagnosis is accomplished by using the SoftMax *** experiment outcomes demonstrate that the model can derive fault properties entirely from the initial vibration *** can retain good diagnostic accuracy under variable load and noise interference and has strong generalization compared to other fault diagnosis models.

关键词： Bearing fault diagnosis convolutional neural network short-long-term memory network feature fusion

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Unmanned Ship Identification Based on Improved YOLOv8s Algorithm

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Computers, Materials & Continua 2024年第3期78卷 3071-3088页

作者： Chun-Ming Wu Jin Lei Wu-Kai Liu Mei-Ling Ren Ling-Li Ran Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology School of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Biomedical Engineering Taiyuan University of TechnologyTaiyuan030600China

Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm(R_YOLO).The algorithm incorporates the Efficient Multi-Scale Attention mechanism(EMA),the efficient Reparameterized Generalized-feature extraction module(CSPStage),the small target detection header,the Repulsion Loss function,and the context aggregation block(CABlock),which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model *** algorithm is validated in detail on two vessel *** comprehensive experimental results demonstrate that,in the infrared dataset,the YOLOv8s algorithm exhibits improvements in various performance ***,compared to the baseline algorithm,there is a 3.1%increase in mean average precision at a threshold of 0.5(mAP(0.5)),a 5.4%increase in recall rate,and a 2.2%increase in mAP(0.5:0.95).Simultaneously,while less than 5 times parameters,the mAP(0.5)and frames per second(FPS)exhibit an increase of 1.7%and more than 3 times,respectively,compared to the CAA_YOLO ***,the evaluation indexes on the visible light data set have shown an average improvement of 4.5%.

关键词： Unmanned ships R_YOLO EMA CSPStage YOLOv8s

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Mobile Hybrid Distribution Transformer Deployment Strategy Based on Spatial Coordinate system Mapping Optimization 11

Mobile Hybrid Distribution Transformer Deployment Strategy B...

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11th China International Conference on Electricity Distribution, CICED 2024

作者： Wang, Yibo Liu, Kaipu Liu, Chen Liu, Yu Du, Zhanhui Wang, Yuan Northeast Electric Power University The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Jilin China

ISBN: (纸本)9798350368345

Under the background of 'double carbon', the power system is facing green change, and the distribution network is facing the challenge of distributed generation and diversified load. Traditional distribution transformers are unable to cope with local load peaks and sudden load growth. In order to cope with the problem of heavy overload caused by seasonal load, mobile hybrid distribution transformer (MHDT) has gradually attracted attention as an innovative solution. In this paper, the deployment strategy of MHDT is discussed, and an optimization method based on spatial coordinate system mapping is proposed to reduce the amount of calculation and improve the computational efficiency. Through the practical application case of an agricultural irrigation area in Jilin Province, the actual effect of this method in solving the problem of transformer heavy overload is verified. The results show that MHDT can effectively improve flexibility response ability of distribution system. © 2024 IEEE.

关键词： Distribution transformers

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Optimal Bidding Strategy for PV and BESSs in Joint energy and Frequency Regulation Markets Considering Carbon Reduction Benefits

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Journal of modern power systems and Clean energy 2024年第2期12卷 427-439页

作者： Jing Bian Yuheng Song Chen Ding Jianing Cheng Shiqiang Li Guoqing Li Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education Northeast Electric Power UniversityJilin 132000China Datang Northeast Electric Power Test&Research Institute Co. Ltd.Changchun 130102China

Photovoltaic(PV)and battery energy storage systems(BESSs)are key components in the energy market and crucial contributors to carbon emission reduction *** systems can not only provide energy but can also generate considerable revenue by providing frequency regulation services and participating in carbon *** study proposes a bidding strategy for PV and BESSs operating in joint energy and frequency regulation markets,with a specific focus on carbon reduction benefits.A two-stage bidding framework that optimizes the profit of PV and BESSs is *** the first stage,the day-ahead energy market takes into account potential real-time forecast *** the second stage,the real-time balancing market uses a rolling optimization method to account for multiple ***,a real-time frequency regulation control method is proposed for the participation of PV and BESSs in automatic generation control(AGC).This is particularly relevant given the uncertainty of grid frequency fluctuations in the optimization model of the real-time balancing *** control method dynamically assigns the frequency regulation amount undertaken by the PV and BESSs according to the control interval in which the area control error(ACE)*** case study results demonstrate that the proposed bidding strategy not only enables the PV and BESSs to effectively participate in the grid frequency regulation response but also yields considerable carbon emission reduction benefits and effectively improves the system operation economy.

关键词： Photovoltaic(PV) battery energy storage system(BESS) energy market carbon market frequency regulation service bidding strategy

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Abnormal Data Identification and Reconstruction Based on Wind Speed Characteristics

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CSEE Journal of power and energy systems 2025年第2期11卷 612-622页

作者： Mao Yang Tian Peng Wei Zhang Xin Su Chao Han Fulin Fan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin 132012China Department of Electronic and Electrical Engineering University of StrathclYdeGlasgow G11XWUnited Kingdom

High availability of wind power data is the basis for wind power research, but there are a large number of abnormal data in actual collected data, which seriously affects analysis of wind power law and reduces prediction accuracy. Measured power data of wind farm are analyzed, influence of wind speed fluctuation characteristics on wind power is discussed, and abnormal points are identified for data of different wind types. The Cluster-Based Local Outlier Factor (CLOF) algorithm based on K-means is used to identify outlier abnormal points, and conditional constraints based on physical background are used to identify accumulation abnormal points. Reconstructed data segment is divided according to fluctuation of wind speed. The Bidirectional Gate Recurrent Unit (BiGRU) model with wind speed as input reconstructs fluctuation segment data, and bi-directional weighted random forest model reconstructs stationary segment data. Based on analysis of measured data of a wind farm, results show the method can effectively identify various abnormal data, and complete high-quality reconstruction of data, thereby improving accuracy of wind power prediction.

关键词： Abnormal data bidirectional weighted random forest BiGRU CLOF reconstruction wind power prediction wind speed characteristics

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Combined Wind-Storage Frequency Modulation control Strategy Based on Fuzzy Prediction and Dynamic control

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energy Engineering 2024年第12期121卷 3801-3823页

作者： Weiru Wang Yulong Cao Yanxu Wang Jiale You Guangnan Zhang Yu Xiao Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology of the Ministry EducationJilin132012China State Grid Songyuan Electric Power Supply Company Songyuan138000China

To ensure frequency stability in power systems with high wind penetration,the doubly-fed induction generator(DFIG)is often used with the frequency fast response control(FFRC)to participate in frequency ***,a certain output power suppression amount(OPSA)is generated during frequency support,resulting in the frequency modulation(FM)capability of DFIG not being fully utilised,and the system’s unbalanced power will be increased during speed recovery,resulting in a second frequency drop(SFD)in the ***,the frequency response characteristics of the power system with DFIG containing FFRC are ***,based on the analysis of the generation mechanism of OPSA and SFD,a combined wind-storage FM control strategy is proposed to improve the system’s frequency response *** strategy reduces the effect of OPSA and improves the FM capability of DFIG by designing the fuzzy logic of the coefficients of FFRC according to the system frequency index in the frequency support *** the speed recovery stage,the energy storage(ES)active power reference value is calculated according to the change of DFIG rotor speed,and the ES output power is dynamically adjusted to reduce the ***,taking the IEEE 39-bus test system as an example,real-time digital simulation verification was conducted based on the RTLAB OP5707 simulation *** simulation results showthat theproposedmethodcan improve theFMcapabilityofDFIG,reduce the SFDunder thepremise of guaranteeing the rapid rotor speed recovery,and avoid the overshooting phenomenon so that the systemfrequency can be quickly restored to a stable state.

关键词： Doubly-fed induction generator frequency fast response control output power suppression amount frequency response characteristics second frequency drop combined wind-storage

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Ladder Time Stepwise Inertia Coordinated control Method of Multiple Wind Farms to Suppress system Frequency Secondary Drop

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energy Engineering 2024年第8期121卷 2293-2311页

作者： He Li Xianchao Liu Jidong Li Yuchen Qiu Tongliao PowerSupply Company State Grid East Inner Mongolia Electric Power CompanyTongliao028000China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Northeast Electric Power UniversityJilin132012China

Currently,both regulated and deregulated power trading exist in China’s power system,which has caused imbalanced funds in the electricity *** this paper,a simulation analysis of the electricity market with wind energy resources is conducted,and the calculation methods of unbalanced funds are investigated *** detail,the calculation formulas of unbalanced funds are illustrated based on their definition,and a two-track electricity market clearing model is ***,the concept of the dual-track system is explained,and the specific calculation formulas of various types of unbalanced funds are ***,considering the renewable energy consumption,the market clearing model based on DC power flow is constructed and solved;by combining fitting methods of mid-and long-term curves,the unbalanced funds are calculated based on clearing results and formulas.

关键词： Wind power stepwise inertial frequency control secondary drop

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Fault Location Detection of Transmission Lines in Noise Environments Based on Random Matrix Theory

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CSEE Journal of power and energy systems 2022年第4期8卷 1233-1241页

作者： Jun An Zihan Deng Haipeng Chen Gang Mu Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012.Jilin ProvinceChina

Fault detection and location are critically significant applications of a supervisory control system in a smart *** methods,based on random matrix theory(RMT),have been practiced using measurements to detect short circuit faults occurring on transmission ***,the diagnostic accuracy is infuenced by the noise signal in the *** relationship between mean eigenvalue of a random matrix and noise is detected in this paper,and the defects of the Mean Spectral Radius(MSR),as an indicator to detect faults,are theoretically determined,along with a novel indicator of the shifting degree of maximum eigenvalue and its *** comparing the indicator and the threshold,the occurrence of a fault can be ***,an augmented matrix is constructed to locate the fault *** proposed method can effectively achieve fault detection via the RMT without any influence of noise,and also does not depend on system *** experiment results are based on the IEEE 39-bus ***,actual provincial grid data is applied to validate the effectiveness of the proposed method.

关键词： Fault detection maximum eigenvalue noise random matrix theory smart grid

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Novel integrated three-port DC/DC converter for different operating modes between renewable energy,electrolyser and fuel cell/battery

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Clean energy 2023年第1期7卷 174-189页

作者： Lilei Jiang Jianxin Qu Lingguo Kong Hejianuig Qian Chuang Liu Guowei Cai Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin 132012China State Grid Harbin Power Supply Company HarbinHeilongjiang ProvinceChina

Due to the slow dynamic power-regulation characteristics of the electrolyser(EL),a novel integrated three-port DC/DC converter topology based on a phase-shifted full-bridge converter and dual active-bridge converter is proposed in this ***,the proposed converter can achieve a fast auxiliary response to the *** topology has the features of single-stage conversion,high system integration and compatibility with multiple operation *** operational principles and a hybrid modulation scheme of the proposed converter are analysed in *** addition,the power-transmission characteristics of each port and the soft-switching range are *** these bases,six operation modes suitable for a hydrogen energy-storage system are *** simulation and a 2-kW scaled-down experimental prototype are established to verify the feasibility and effectiveness of the proposed topology in different operation modes.

关键词： renewable energy electrolyser fuel cell three-port DC/DC converter

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Infrared and Visible Image Fusion Based on Res2Net-Transformer Automatic Encoding and Decoding

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Computers, Materials & Continua 2024年第4期79卷 1441-1461页

作者： Chunming Wu Wukai Liu Xin Ma Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology School of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China School of Aeronautical Engineering Jilin Institute of Chemical TechnologyJilin132022China

A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The networkcomprises an encoder module, fusion layer, decoder module, and edge improvementmodule. The encoder moduleutilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformerto achieve deep-level co-extraction of local and global features from the original picture. An edge enhancementmodule (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy isintroduced to enhance the adaptive representation of information in various regions of the source image, therebyenhancing the contrast of the fused image. The encoder and the EEM module extract features, which are thencombined in the fusion layer to create a fused picture using the decoder. Three datasets were chosen to test thealgorithmproposed in this paper. The results of the experiments demonstrate that the network effectively preservesbackground and detail information in both infrared and visible images, yielding superior outcomes in subjectiveand objective evaluations.

关键词： Image fusion Res2Net-Transformer infrared image visible image

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