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IEEE International Conference on Software engineering and Service Sciences (ICSESS)

作者： Yongxin Chen Shiping E Zhenan Du Kanjun Zhang Gaofeng Zhang State Grid Hubei Electric Power Research Institute Wuhan Hubei China State Key Laboratory of Advanced Electromagnetic Engineering and Technology (HUST) Wuhan Hubei China State Grid Hubei Electric Power Co. Ltd Wuhan Hubei China NR Electric Co. Ltd Nanjing Jiangsu China

ISBN: (数字)9798350389166

ISBN: (纸本)9798350389173

The prediction of transformer oil temperature is a time series prediction task, which is of great significance for the maintenance of substation equipment. In the process of multivariate prediction, not all variables are strongly correlated with the prediction of the transformer oil temperature. This paper proposes a transformer oil temperature prediction method based on Feature Selection and Smooth Residual blocks, named FSSR. A two-stage feature selection method is applied to select the related features. Residual connection is applied to convolutional neural network in smooth residual blocks. Experimental study is performed on the ETTh1 and ETTh2 datasets. With different number of selected features, the best one can reduce the average MSE (mean squared error) by at least 20% than the worst one. Compared to the baseline models, FSSR has the best accuracy. Compared with LSTM (Long Short-Term Memory network), the average MSE of FSSR decreased by 27.62% on the ETTh1 dataset, and 39.34% on the ETTh2 dataset.

关键词： Temperature distribution Substations Oils Time series analysis Oil insulation Predictive models Transformers Feature extraction Convolutional neural networks Long short term memory

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Optimal Coordinated Control of Full-controlled Excitation System with Energy Storage System

Optimal Coordinated Control of Full-controlled Excitation Sy...

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2020 IEEE/IAS Industrial and Commercial Power System Asia, I and CPS Asia 2020

作者： Cheng, Liping Zhang, Tiantian He, Silin Yu, Minghao Mao, Chengxiong Wang, Dan Huazhong University of Science and Technology Key Laboratory of Advanced Electromagnetic Engineering and Technology Hubei Electric Power Security and High Efficiency Key Laboratory School of Electrical and Electronic Engineering Wuhan430074 China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143033

The full-controlled excitation system is a novel excitation system which can regulate the amount of reactive power injected to the power system. In this paper, the full-controlled excitation system with energy storage system (ESS) is proposed. By the combination, the excitation system can provide controllable active and reactive power to the terminal of the generator. The typical structure of this excitation system is proposed and the state-space equation is derived. Then the linear optimal control is used to coordinate three control variables to design the controller. The simulations based on the single machine infinite-bus (SIMB) system show that the full-controlled excitation system with ESS performs better on the suppression of power system oscillation than excitation system without the control of power exchange with the terminal of the generator. It is a prospective substitute to the conventional excitation system and of great value to study. © 2020 IEEE.

关键词： Energy storage

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Large-Scale Fabricating Carbon Coating Chevrel Phase in Molten Salts: Implications for High-Performance Magnesium-Ion Battery Cathode

SSRN

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SSRN 2022年

作者： Zhao, Wenjie Li, Haomiao Zhang, Yujie Wang, Kangli Jiang, Kai State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology No.1037 Luoyu Road Wuhan430074 China State Key Laboratory of Materials Processing and Die & Mould Technology College of Materials Science and Engineering Huazhong University of Science and Technology No.1037 Luoyu Road Wuhan430074 China

Molten salt synthesis is a facile, extensible and effective way to obtain specific electrode materials with in situ carbon coating. Herein, a carbon coating Mo 6 S 8 compounds are synthesized based on molten KCl medium, and the excellent electrochemical Mg-storage performance are demonstrated in rechargeable Mg ion batteries. Benefiting from the in situ carbon coating, the as-synthesized Mo 6 S 8 @C delivers a high reversible capacity of 90 mAh g –1 and a superior rate performance. Further mechanism investigation via kinetics testing, ex situ XRD and XPS demonstrate that the carbon coating layer on the surface of Mo 6 S 8 could accelerate the electron/ion transport and improve the rate performance and stability of the electrodes. This work provides a possible way to large-scale fabricate the carbon coating Mo 6 S 8 and lays a foundation for the practical applications of Mg ion batteries. © 2022, The Authors. All rights reserved.

关键词： Fabrication

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Supply Restoration Method of Flexible Active Distribution Network Using Power Router

SSRN

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SSRN 2023年

作者： Mao, Jilong Yin, Xianggen Yin, Xin Dou, Zhenlan Sun, Pei Lai, Jinmu School of Electrical and Electronic Engineering State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China School of Automation Wuhan University Of Technology Wuhan China State Grid Shanghai Municipal Electric Power Company Shanghai China State Grid Shanghai Electric Power Research Institute Shanghai China School of Electrical and Information Engineering Zhengzhou University Zhengzhou China

Power Router(PR) is an energy exchange device in power systems that is based on fully-controlled power electronic device. It can be flexibly controlled to achieve fault isolation and provide voltage support to the fault area, thus enhancing the power restoration capability of the system. This paper proposes a fault restoration strategy method based on PR. The system power flow model is firstly improved to accommodate systems incorporating PR. Then we present a corresponding fault restoration strategy after system faults and provide an active distribution network power restoration model. This model is essentially a large-scale nonlinear programming model, which is transformed and solved by using second-order cone programming methods. Next, case studies are carried out on a modified IEEE 33 bus system with the PR. The factors affecting the power restoration capability of the PR are analyzed. The results demonstrate that the PR is capable of recovering from system faults and achieving fault restoration. Moreover, compared to methods such as network reconstruction, the PR exhibits a higher restoration ratio. © 2023, The Authors. All rights reserved.

关键词： Second-order cone programming

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Viscous Effects on Nonlinear Double Tearing Mode and Plasmoid Formation in Adjacent Harris Sheets

SSRN

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SSRN 2023年

作者： Zhu, Ping Ahmad, Nisar Shen, Chao Ali, Ahmad Zeng, Shiyong Shenzhen518055 China International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Engineering Physics University of Wisconsin-Madison MadisonWI53706 United States Pakistan Tokamak Plasma Research Institute Islamabad3329 Pakistan Department of Plasma Physics and Fusion Engineering University of Science and Technology of China Hefei230026 China

In this paper, we study the effects of viscosity on the evolution of double tearing mode (DTM) in a pair of adjacent Harris sheets based on the resistive MHD model in the NIMROD code. Similar to the tearing mode in the conventional single Harris sheet, a transition is observed in the generation of both normal and monster plasmoids at Prandtl number Pr = 1. In the Pr 1 regime this flow advection is inhibited. © 2023, The Authors. All rights reserved.

关键词： Prandtl number

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A Novel Resonant Frequency Tracking Control for Linear Compressor Based on MRAS Method

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CES Transactions on Electrical Machines and Systems 2020年第3期4卷 227-236页

作者： Wei Xu Qizhe Wang Xiang Li Yi Liu Jianguo Zhu State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan430074China School of Electrical and Information Engineering University of SydneySydneyNSW 2006Australia

To optimize the efficiency of the linear compressor,its operating frequency must be controlled equal to the system resonant *** traditional resonant frequency tracking control algorithm relies on the steady state characteristics of the system,which suffers from slow convergence speed,low accuracy and slow system *** order to solve these problems,a novel resonant frequency tracking control for linear compressor based on model reference adaptive system(MRAS)is proposed in this paper,and the parameter adaptive rate is derived by the Popov's hyperstability theory,so that the system resonant frequency can be directly calculated through the parameter adaptive ***,the traditional algorithm needs to calculate the piston stroke signal by integrating the back-EMF,which has the problem of integral *** algorithm proposed in this paper only needs the velocity signal,and the accuracy of the velocity calculation can be ensured by utilizing the self-adaptive band-pass filter(SABPF),thereby greatly improving the accuracy of the resonance frequency *** results verify the effectiveness of the proposed algorithm.

关键词： linear compressor linear oscillating motor(LOM) resonant frequency tracking control model reference adaptive system(MRAS)

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Optimal Capacity Planning of a Bundled Wind-Photovoltaic-Thermal Generation System Considering Carbon Emission Trading 14

Optimal Capacity Planning of a Bundled Wind-Photovoltaic-The...

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14th International Conference on Computer and Electrical engineering, ICCEE 2021

作者： Ouyang, Litao Fan, Yue Lou, Suhua Zhang, Yuanxin Bai, Chongtao Yu, Haiyang China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Hubei Wuhan430074 China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Hubei Wuhan430074 China State Grid Qinghai Electric Power Corporation Xining Qinghai810008 China

In view of the situation of the bundled wind-photovoltaic-thermal generation system (BWPTGS) in China's new energy bases and the demand of carbon emissions reduction in generation system, this paper constructs a capacity planning method for wind-photovoltaic-thermal bundling power supply considering the life cycle carbon emissions. Based on the concept of low-carbon economy, this paper introduces carbon emission trading (CET) method into capacity planning of BWPTGS. Then, this paper calculates the carbon emissions cost of the generation system under the carbon emissions trading mechanism. With the objective of minimizing the comprehensive cost of generation system taking into account the cost of CET, the paper constructs an optimal generation system planning model for new energy bases considering carbon emission trading. The optimization model is applied to a BWPTGS for a new energy base in north-western China. Case studies are conducted to demonstrate the effectiveness of this proposed model and method. © Published under licence by IOP Publishing Ltd.

关键词： Emission control

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Interdigitated Terahertz Metamaterial Sensors: Design with the Dielectric Perturbation Theory

arXiv

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arXiv 2023年

作者： Cao, Lei Meng, Fanqi Özdemir, Esra Loth, Yannik Richter, Merle Wigger, Anna Katharina Sosa, Maira Pérez Jumaah, Alaa Jabbar Al-Daffaie, Shihab Bolívar, Peter Haring Roskos, Hartmut G. State Key Laboratory of Advanced Electromagnetic Technology Huazhong University of Science and Technology Wuhan430074 China Physikalisches Institut Johann Wolfgang Goethe-Universität Frankfurt am Main Germany University of Siegen Institute for High Frequency and Quantum Electronics Siegen Germany Department of Electrical Engineering Eindhoven University of Technology Eindhoven5612 AE Netherlands

Designing terahertz sensors with high sensitivity to detect nanoscale thin films and single biomolecule presents a significant challenge, and addressing these obstacles is crucial for unlocking their full potential in scientific research and advanced applications. This work presents a strategy for the design optimization of metamaterial sensors employed in the detection of small amounts of dielectric materials. The sensors usually utilize the shift of the resonance frequency as an indicator of the presence of the analyte. The amount of shifting depends on intrinsic properties (electric field distribution, quality factor, and mode volume) of the bare cavity, as well as the overlap volume of its high-electric-field zone(s) and the analyte. Guided by the simplified dielectric perturbation theory, interdigitated electric split-ring resonators (ID-eSRR) are devised to significantly enhance the detection sensitivity for thin-film analytes compared to eSRRs without interdigitated fingers in the SRR gap region. The fingers of the ID-eSRR metamaterial sensor redistribute the electric field, creating strongly localized field enhancements that substantially boost the interaction with the analyte. Additionally, the periodic change of the orientation of the inherent anti-phase electric field in the interdigitated structure reduces radiation loss, leading to a higher Q-factor. Experiments with e-beam-fabricated ID-eSRR sensors operating at around 300 GHz demonstrate a remarkable frequency shift of 33.5 GHz upon deposition of a SiO2 layer with a thickness of 150 nm as an analyte simulant. The figure of merit (FOM) improves by over 50 times compared to structures without interdigitated fingers. This rational design option opens a promising avenue for highly sensitive detection of thin films and trace biomolecules. Copyright © 2023, The Authors. All rights reserved.

关键词： Metamaterials

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CoFMD-BiLSTM: A Wind and Photovoltaic Power Prediction Method Based on Feature Mode Decomposition and Cooperative Learning Strategy

CoFMD-BiLSTM: A Wind and Photovoltaic Power Prediction Metho...

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Chinese Automation Congress (CAC)

作者： Xinzhi Ding Dayi Li Wei Huang Yiping Chen State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan Yunnan electric power test and Research Institute (Group) Co. Kunming Yunnan Power Grid Co. Ltd. Kunming Novel Electric Power System (Beijing) Research Institute of China Southern Power Grid Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

With the increasing penetration of new energy sources such as wind and solar, accurate source-side power forecasting helps power system dispatchers to obtain new energy pre-output plans and improve the power system's new energy consumption capacity through the coordination of multiple power generation resources. The wind and photovoltaic power data are characterized by large fluctuations, strong nonlinearity, instability, and strong time dependence, etc. Through “Decomposition-Prediction”, the original sequence is decomposed into a number of sub-sequences, which reduces the volatility and randomness of the original sequence, and has been widely used in wind and photovoltaic power prediction. In order to solve the problem that traditional decomposition algorithms have insufficient decomposition capability to extract data features in a targeted and effective way, we propose a wind and photovoltaic power prediction method based on Feature Mode Decomposition and Cooperative Learning Strategy: the CoFMD-BiLSTM model. A novel emerging decomposition algorithm, Feature Mode Decomposition (FMD), originally applied in fault detection, is introduced. By designing a Cooperative Learning Strategy to learn and fit the decomposition sequence information obtained from the FMD decomposition covering different features, which is fed into the BiLSTM model to obtain the wind and light power predictions. The actual operation data of Sotavento Galicia (sg) wind farm in Spain and TuoZhuo photovoltaic farm in Yunnan, China are used. Compared with the two models, VMD-BiLSTM and BiLSTM, the validation results show that the wind and solar power prediction method based on the CoFMD-BiLSTM model can effectively improve the accuracy of wind and solar power prediction.

关键词： Photovoltaic systems Bidirectional long short term memory Predictive models Wind power generation Wind farms Feature extraction Prediction algorithms Data models Wind forecasting Forecasting

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The use of metal–organic frameworks and their derivatives for lithium-ion capacitors

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Carbon 2025年 232卷

作者： Sha-sha Zhao Xiong Zhang Chen Li Ya-bin An Tao Hu Kai Wang Xian-zhong Sun Yan-wei Ma Key Laboratory of High Density Electromagnetic Power and Systems Institute of Electrical Engineering Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Shandong Key Laboratory of Advanced Electromagnetic Conversion Technology Institute of Electrical Engineering and Advanced Electromagnetic Drive Technology Qilu Zhongke Jinan 250013 China

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