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A Temporal Convolutional Network Based Hybrid Model for Short-term Electricity Price Forecasting

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1119-1130页

作者： Haoran Zhang Weihao Hu Di Cao Qi Huang Zhe Chen Frede Blaabjerg school of mechanical and electrical engineering University of Electronic Science and Technology of ChinaChengduChina Department of Energy Technology Aalborg UniversityAalborgDenmark IEEE

Electricity prices have complex features,such as high frequency,multiple seasonality,and nonlinearity.These factors will make the prediction of electricity prices difficult.However,accurate electricity price prediction is important for energy producers and consumers to develop bidding strategies.To improve the accuracy of prediction by using each algorithms’advantages,this paper proposes a hybrid model that uses the Empirical Mode Decomposition(EMD),Autoregressive Integrated Moving Average(ARIMA),and Temporal Convolutional Network(TCN).EMD is used to decompose the electricity prices into low and high frequency components.Low frequency components are forecasted by the ARIMA model and the high frequency series are predicted by the TCN model.Experimental results using the realistic electricity price data from Pennsylvania-New Jersey-Maryland(PJM)electricity markets show that the proposed method has a higher prediction accuracy than other single methods and hybrid methods.

关键词： Autoregressive integrated moving average model electricity price forecasting empirical mode decomposition temporal convolutional network

Deep neural network-enabled battery open-circuit voltage estimation based on partial charging data

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Journal of Energy Chemistry 2024年第3期90卷 120-132,I0005页

作者： Ziyou Zhou Yonggang Liu Chengming Zhang Weixiang Shen Rui Xiong State Key Laboratory of mechanical Transmission for Advanced Equipment&College of mechanical and Vehicle engineering Chongqing UniversityChongqing 400000China Department of Vehicle engineering School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China Department of electrical engineering Harbin Institute of TechnologyHarbin 150000HeilongjiangChina school of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVictoria 3122Australia

Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion batteries.The main function of the BMSs is to estimate battery states and diagnose battery health using battery open-circuit voltage(OCV).However,acquiring the complete OCV data online can be a challenging endeavor due to the time-consuming measurement process or the need for specific operating conditions required by OCV estimation models.In addressing these concerns,this study introduces a deep neural network-combined framework for accurate and robust OCV estimation,utilizing partial daily charging data.We incorporate a generative deep learning model to extract aging-related features from data and generate high-fidelity OCV curves.Correlation analysis is employed to identify the optimal partial charging data,optimizing the OCV estimation precision while preserving exceptional flexibility.The validation results,using data from nickel-cobalt-magnesium(NCM) batteries,illustrate the accurate estimation of the complete OCV-capacity curve,with an average root mean square errors(RMSE) of less than 3 mAh.Achieving this level of precision for OCV estimation requires only around 50 s collection of partial charging data.Further validations on diverse battery types operating under various conditions confirm the effectiveness of our proposed method.Additional cases of precise health diagnosis based on OCV highlight the significance of conducting online OCV estimation.Our method provides a flexible approach to achieve complete OCV estimation and holds promise for generalization to other tasks in BMSs.

关键词： Lithium-ion battery Open-circuit voltage Health diagnosis Deep learning

mechanical and magnetocaloric adjustable properties of Fe3O4/PET deformed nanoparticle film

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Chinese physics B 2024年第3期33卷 589-595页

作者：范凤国段林彤 school of physics and electrical Information Shangqiu Normal UniversityShangqiu 476000China

The flexibility of nanoparticle films is a topic of rapidly growing interest in both scientific and engineering researches due to their numerous potential applications in a broad range of wearable electronics and biomedical devices.This article presents the elucidation of the properties of nanoparticle films.Here,a flexible film is fabricated based on polyethylene terephthalate(PET)and magnetic iron oxide at the nanoscale using layer-by-layer technology.The 2D thin flexible film material can be bent at different angles from 0°to 360°.With an increase in elastic deformation angles,the magnetocaloric effect of the film gradually increases in the alternating magnetic field.The test results from a vibrating sample magnetometer and a low-frequency impedance analyzer demonstrate that the film has a good magnetic response and anisotropy.The magnetocaloric effect and magnetic induction effect are controlled by deformation,providing a new idea for the application of elastic films.It combines the flexibility of the nanoparticle PET substrate and,in the future,it may be used for skin adhesion for administration and magnetic stimulation control.

关键词： nanoparticle film deformation magnetic properties flexible substrates

Switching,explosion,and chaos of multi-wavelength soliton states in ultrafast fiber lasers

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Science China(physics,Mechanics & Astronomy) 2024年第7期67卷 82-90页

作者： Zhi-Zeng Si Yue-Yue Wang Chao-Qing Dai College of Optical Mechanical and Electrical EngineeringZhejiang A&F UniversityLin’an 311300China

Because of the complexity and difficulty of realizing a multi-wavelength soliton state,reports on its internal dynamic characteristics are scarce.In this study,the switching and periodic soliton explosion processes of the multi-wavelength soliton state in a negative dispersion passively mode-locked fiber laser are realized.The generation of the multi-wavelength soliton state undergoes the process of noise,oscillation,and stable mode-locking,and the splitting and annihilation of solitons with different group velocities directly impact the generation and disappearance of three wavelengths.Positive and negative dispersion lead to different group velocities of solitons.The presence and displacement of solitons with different group velocities cause soliton collisions,which lead to soliton explosions.A soliton experiences relative phase oscillation,chaos,and oscillation,as well as convergence and separation before and after an explosion.With an increase in parameters related to pump power,single-soliton oscillation,multi-wavelength solitons,and chaos are found in experiments and simulations,proving the relevance and reliability between simulation and experimental results.This work promotes the dynamical study of multi-soliton collisions in nonlinear science and the development of chaos theory in multi-comb lasers.

关键词： multi-wavelength fiber laser soliton explosion chaos state switching real-time dynamics

Layer-by-layer epitaxy growth of thickness-controllable two-dimensional tungsten disulfide

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Science China(Information Sciences) 2024年第5期67卷 302-310页

作者： Jieyuan LIANG Zixing ZOU Junwu LIANG Di WANG Biao WANG Anshi CHU Jiali YI Cheng ZHANG Lizhen FANG Tian ZHANG Huawei LIU Xiaoli ZHU Dong LI Anlian PAN Key Laboratory for Micro-Nano physics and Technology of Hunan Province State Key Laboratory of Chemo/Biosensing and Chemometrics Hunan Institute of Optoelectronic IntegrationCollege of Materials Science and Engineering School of Physics and ElectronicsHunan University school of Electronic Information and electrical engineering Changsha University school of physics and Telecommunication engineering Yulin Normal University Units Semiconductor Technology Co. Ltd. school of physics and Electronics Hunan Normal University

Bilayer transition metal dichalcogenides（TMDs） balance the high mobility of single layers with the high state density of multilayers and therefore have promising application prospects in high-performance electronics. However, the layer-controlled growth of 2D materials is still confronted with challenges such as poor repeatability between different labs and a limited understanding of the growth mechanism at the atomic scale. Herein, we report a new carbon-assisted chemical vapor deposition process that can realize the growth of WS2sheets with high yield, precise thickness controllability, and repeatability. We show that carbon can act as a reducing agent and catalyst that preferentially reacts with the WO3precursor to form intermediate WO3-xproducts with low-valence state W. The resulting oxycarbide gas has a low surface adsorption energy when deposited on the surface of as-grown WS2, which provides nucleation sites for the subsequent layer of WS2growth and leads to the vertical growth of WS2sheets. The growth mechanism is thoroughly investigated. electrical transport measurements show that the produced bilayer WS2possesses a high carrier mobility(up to 58 cm2·V-1·s-1) and small subthreshold swing（estimated to be 148 mV/decade）,which are among the best reported results for TMDs produced using CVD.

关键词： WS$_2$ thickness-controlled growth chemical vapor deposition additive carbon

Research on modeling and self-excited vibration mechanism in magnetic levitation-collision interface coupling system

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 873-890页

作者： Jinghu TANG Chaofeng LI Jin ZHOU Zhiwei WU school of mechanical engineering&Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion Systems of Ministry of Education of China Northeastern UniversityShenyang 110819China school of mechanical and electrical engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

The modeling and self-excited vibration mechanism in the magnetic levitation-collision interface coupling system are investigated.The effects of the control and interface parameters on the system's stability are analyzed.The frequency range of self-excited vibrations is investigated from the energy point of view.The phenomenon of self-excited vibrations is elaborated with the phase trajectory.The corresponding control strategies are briefly analyzed with respect to the vibration mechanism.The results show that when the levitation objects collide with the mechanical interface,the system's vibration frequency becomes larger with the decrease in the collision gap;when the vibration frequency exceeds the critical frequency,the electromagnetic system continues to provide energy to the system,and the collision interface continuously dissipates energy so that the system enters the self-excited vibration state.

关键词： magnetic levitation coupling system self-excited vibration mechanical interface vibration frequency

Introducing electrolytic electrochemical polymerization for constructing protective layers on Ni-rich cathodes of Li-ion batteries

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Rare Metals 2024年第6期43卷 2536-2545页

作者： Lin-Tao Dou Bei Li Hao-Long Nie Dong-Dong Xiao Chao-Qun Shang Xiao-Min Wang Zhan-Hui Zhang Katerina E.Aifantis Pu Hu school of Materials Science and engineering Wuhan Institute of Technology Huairou Division Institute of PhysicsChinese Academy of Sciences Department of mechanical and Aerospace engineering University of Florida

LiNi0.8Co0.1Mn0.1O2（NCM811） is the most promising cathode for high-energy Li-ion batteries,despite its poor cycling stability that originates from the reactions that occur with the electrolyte.Herein,to solve this interfacial issue,a facile electrolytic electrochemical polymerization process was introduced in this paper,and a uniform conductive electrolyte interface（polyaniline） was successfully constructed on the surface of the NCM811 porous electrode（PANI-NCM）,which facilitated the charge transfer during charge/discharge.The side reactions at the interface between the cathode and the electrolyte are suppressed,and thereby,the cycling performance and rate capability are considerably improved.PANI-NCM delivers an initial capacity of 157.2 mAh·g-1as well as excellent cyclability（capacity retention of 88% after 500 cycles at 2C）,whereas the capacity of the bare NCM811 has dropped to 31.3 mAh·g-1.In addition,polypyrrole and polythiophene also can be formed through electrolytic electrochemical polymerization process,which provides a practicable tactic to modify the interfacial stability of cathodes for high-energy Li-ion batteries.

关键词： Lithium-ion battery Ni-rich cathode In-situ polymerization Conductive polymer Electrochemical performance

Level pinning of anti-PT-symmetric circuits for efficient wireless power transfer

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National Science Review 2024年第1期11卷 215-224页

作者： Zhiwei Guo Fengqing Yang Haiyan Zhang Xian Wu Qiong Wu Kejia Zhu Jun Jiang Haitao Jiang Yaping Yang Yunhui Li Hong Chen MOE Key Laboratory of Advanced Micro-Structured Materials School of Physics Sciences and Engineering Tongji University Department of electrical engineering Tongji University school of Automotive Studies Tongji University

Wireless power transfer(WPT) technology based on magnetic resonance(a basic physical phenomenon)can directly transfer energy from the source to the load without wires and other physical contacts, and has been successfully applied to implantable medical devices, electric vehicles, robotic arms and other fields.However, due to the frequency splitting of near-field coupling, the resonant WPT system has some unique limitations, such as poor transmission stability and low efficiency. Here, we propose anti-resonance with level pinning for high-performance WPT. By introducing the anti-resonance mode into the basic WPT platform, we uncover the competition between dissipative coupling and coherent coupling to achieve novel level pinning, and construct an effective anti-parity-time(anti-PT)-symmetric non-Hermitian system that is superior to previous PT-symmetric WPT schemes. On the one hand, the eigenvalue of the anti-PT-symmetric system at resonance frequency is always pure real in both strong and weak coupling regions, and can be used to overcome the transmission efficiency decrease caused by weak coupling, as brought about by, for example, a large size ratio of the transmitter to receiver, or a long transmission distance.On the other hand, due to the level pinning effect of the two kinds of coupling mechanisms, the working frequency of the system is guaranteed to be locked, so frequency tracking is not required when the position and size of the receiver change. Even if the system deviates from the matching condition, an efficient WPT can be realized, thereby demonstrating the robustness of the level pinning. The experimental results show that when the size ratio of the transmitter coil to the receiver coil is 4.29(which is in the weak coupling region), the transfer efficiency of the anti-PT-symmetric system is nearly 4.3(3.2) times higher than that of the PT-symmetric system when the matching conditions are satisfied(deviated). With the miniaturization and integration of devices in mind, a synthetic anti-PT-symmetric sy

关键词： non-Hermitian system wireless power transfer anti-PT-symmetric circuits synthetic dimension metamaterials

Bearing Fault Diagnosis Based on Deep Discriminative Adversarial Domain Adaptation Neural Networks

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2619-2640页

作者： Jinxi Guo Kai Chen Jiehui Liu Yuhao Ma Jie Wu Yaochun Wu Xiaofeng Xue Jianshen Li school of mechanical and Equipment engineering Hebei University of EngineeringHandan056000China College of mechanical engineering Anyang Institute of TechnologyAnyang455000China Department of mechanical and electrical engineering Yuncheng UniversityYuncheng044000China

Intelligent diagnosis driven by big data for mechanical fault is an important means to ensure the safe operation ofequipment. In these methods, deep learning-based machinery fault diagnosis approaches have received increasingattention and achieved some results. It might lead to insufficient performance for using transfer learning alone andcause misclassification of target samples for domain bias when building deep models to learn domain-invariantfeatures. To address the above problems, a deep discriminative adversarial domain adaptation neural networkfor the bearing fault diagnosis model is proposed (DDADAN). In this method, the raw vibration data are firstlyconverted into frequency domain data by Fast Fourier Transform, and an improved deep convolutional neuralnetwork with wide first-layer kernels is used as a feature extractor to extract deep fault features. Then, domaininvariant features are learned from the fault data with correlation alignment-based domain adversarial training.Furthermore, to enhance the discriminative property of features, discriminative feature learning is embeddedinto this network to make the features compact, as well as separable between classes within the class. Finally, theperformance and anti-noise capability of the proposedmethod are evaluated using two sets of bearing fault datasets.The results demonstrate that the proposed method is capable of handling domain offset caused by differentworkingconditions and maintaining more than 97.53% accuracy on various transfer tasks. Furthermore, the proposedmethod can achieve high diagnostic accuracy under varying noise levels.

关键词： Fault diagnosis transfer learning domain adaptation discriminative feature learning correlation alignment