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International Conference on Power Electronics and Motion Control (IPEMC)

作者： Siying Chen Min Cheng Yingbiao Li Jiawei Yu Yihua Zhu Mingkang Wu Jiabing Hu Jianan Yan State Key Laboratory of Advanced Electromagnetic Technology and School of Electrical and Electronic Engineering Huazhong University of Science and Technology China Yunnan Power Grid China CSG Key Laboratory for Power System Simulation (Electric Power Research Institute China Southern Power Grid) State Key Laboratory of HVDC (Electric Power Research Institute China Southern Power Grid) National Energy Power Grid Technology R&D Centre Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

DC overvoltage occurs when short circuit fault exists at the receiving-end and is harmful to the safety of the system where wind farms are connected to the grid through high-voltage direct current (HVDC) transmission based on the modular multilevel converter (MMC). To address this issue, this paper first analyzed the mechanism of the DC overvoltage and innovatively proposed a strategy in which grid-forming-controlled wind farms are integrated into the AC grid through MMC-HVDC, whose sending-end applies grid-following control and constant DC voltage control. However, secondary DC overvoltage appears during the fault recovery stage and is mainly caused by the saturation of the PI controller of constant active power control. Simulations are carried out on a test with MATLAB/Simulink, and results verify the efficacy of the proposed methods in suppressing DC overvoltage that appeared during receiving-end faults and their recovery stage.

关键词： PI control Simulation Power control Wind farms Robustness Wind turbines Safety

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A Prediction Model for Time Series of Dissolved Gas Content in Transformer Oil Based on LSTM

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Journal of Physics: Conference Series 2020年第1期1659卷

作者： Chuye Hu Yang Zhong Yiqi Lu Xiaotong Luo Shaorong Wang State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science &Technology Wuhan 430074 Hubei Province China

By combining with dissolved gas analysis, time series prediction of dissolved gas content in oil provides a basis for transformer fault diagnose and early warning. In the view of that, a prediction model based on long short time memory (LSTM) network for time series of dissolved gas content in oil is proposed, which takes advantage of LSTM network's ability to deal with long-sequence prediction problems. Five characteristic gas concentrations are used as input to the model, and the hyper parameters of the model is optimized by Bayesian optimization algorithm to further improve prediction accuracy, then a LSTM prediction model is constructed. By case study, it is verified that the proposed model can precisely predict time series of dissolved gas content. Compared with gray model, BP neural network and support vector machine, the proposed model has higher prediction accuracy and can better track the trend of time series of dissolved gas content in oil.

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Investigation of the population density of excited atomic hydrogen in negative hydrogen ion sources based on a collisional-radiative model

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AIP Conference Proceedings 2021年第1期2373卷

作者： Z. Li D. Li J. Yang P. Chen C. Zuo F. Song D. Chen State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China

Collisional-radiative (CR) models are useful to analyze the dynamic process of excited states and support the interpretation of excited population densities measured for example by optical emission spectroscopy (OES). A CR model of atomic hydrogen is described, in which the population densities of the excited states are coupled to the densities of ground state H, H2 and H2+ . The three coupling channels, namely excitation of H, dissociative excitation of H2 and dissociative recombination of H2+ , usually account for the main contributions to the excited hydrogen atoms in cesium free negative hydrogen ion sources. The population densities of excited hydrogen atom are presented for each channel. They have a similar dependence on electron density for the three channels. Furthermore, the influences of varying electron energy distribution function (EEDF) on the excited state density are discussed. Finally, the described CR model is applied to OES in an ICP hydrogen discharge and the estimated plasma parameters are given.

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Correction to “Wide-Area Backup Protection Algorithm Based on Fault Component Voltage Distribution” [Oct 11 2752-2760]

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IEEE Transactions on Power Delivery 2012年第1期27卷 455-455页

作者： Zhiqin He Zhe Zhang Wei Chen Om P. Malik Xianggen Yin State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China University of Calgary Calgary AB Canada

In the above titled paper (ibid., vol. 26, no. 4, pp. 2752-2760, Oct. 2011), Figs. 1 and 2 appear incorrectly. The correct figures are presented here.

关键词： Algorithm design and analysis Protective relaying Wide area measurements

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Low-loss Fusion Splicing between Antiresonant-HCFs and AR-coated SMFs with Low Return Loss

Low-loss Fusion Splicing between Antiresonant-HCFs and AR-co...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Caoyuan Wang Ruowei Yu Limin Xiao Advanced Fiber Devices and Systems Group Key Laboratory of Micro and Nano Photonic Structures (MoE) Key Laboratory for Information Science of Electromagnetic Waves (MoE) Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing School of Information Science and Technology Fudan University Shanghai China Yiwu Research Institute of Fudan University Yiwu China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen China

We have demonstrated a unique fiber splicing technique for low-loss fusion splicing between antiresonant hollow core fibers and standard single-mode fibers with AR coating, achieving an insertion loss of 0.3 dB per co... 详细信息

关键词： Reflectivity Splicing Asia Insertion loss Bandwidth Optical fiber communication Coatings

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A Novel Protection Scheme for Outgoing Line Fault of AC Transmission Line near the Inverter Station of AC/DC Hybrid Power Grid based on AC Filter Characteristics

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Journal of Physics: Conference Series 2022年第1期2247卷

作者： Lin Yang Minghao Wen Yu Chen Xingzhu Wang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China

Compared with traditional AC power grid, the fault characteristics of the AC/DC hybrid power grid are more complex and variable. Hence there is a problem of incorrect action for the fault detection elements used in traditional AC power grid which comes up when an outgoing line fault occurs on the AC transmission line in the vicinity of the inverter station. To distinguish the fault direction under the aforementioned situation, a directional protection scheme based on the characteristics of the AC filter is proposed in this paper. Considering the information can be measured by AC line relay, a method for estimating the current provided by the AC filter is given during an outgoing line fault. According to the difference of current characteristics between forward and reverse fault, the fault direction can be judged based on waveform similarity among the currents provided by the AC filter and measured by the AC line relay. Finally, a simulation model is built on the PSCAD/EMTDC platform for extensive performance evaluation. The reliability and effectiveness of the protection scheme are verified under different cases.

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electromagnetic fields and antenna impedance analysis of an RF ion source at HUST

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AIP Conference Proceedings 2018年第1期2011卷

作者： Peng Zhao Dezhi Chen Dong Li Chen Zuo 1State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology China

Huazhong University of Science and technology (HUST) is developing an RF based negative ion source. Numerical simulations of the 1 MHz RF driver have been performed using ANSYS HFSS. Differing from conventional inductively coupled plasma (ICP) source simulations, which exclude Faraday screen (FS) for simplifying analysis, our simulation model contains FS and employs a complete 3D model for reproducing the realistic electromagnetic fields in the driver. It is found that the FS suppresses effectively the axial electric field, hence diminishes the capacitive coupling between the antenna and the plasma. The simulations without and with plasma have also been performed by approximating the plasma as a homogeneous electrically conducting medium. It is found that the existence of plasma further enhances the azimuthal electric field in the plasma volume, which enhances the inductive coupling between the antenna and plasma. The equivalent antenna impedance loaded without and with plasma has been analysed. As the plasma conductivity increases, the antenna inductance decreases, while the antenna resistance firstly rises and then declines, which indicates that the RF power transfer gets obstructed at high input power and high plasma density. The measured antenna impedance at no plasma is much closer to the simulation result in the model containing FS rather than excluding FS, which somehow verifies the validity of this model.

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Ultralow-Loss and Polarization-Maintained Fusion Splicing for Asymmetric Antiresonant Hollow-Core Fibers

Ultralow-Loss and Polarization-Maintained Fusion Splicing fo...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Ruowei Yu Jie Zhu Caoyuan Wang Cong Xiong Limin Xiao Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing School of Information Science and Technology Advanced Fiber Devices and Systems Group Key Laboratory of Micro and Nano Photonic Structures (MoE) Key Laboratory for Information Science of Electromagnetic Waves (MoE) Fudan University Shanghai China Yiwu Research Institute Fudan University Yiwu China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen China

We develop an approach to tailoring the mode of a solid-core polarization-maintaining fiber, with both the reverse tapering process and the thermally expanded core technique, enlarging the mode area and reshaping the mode shape to construct a matched interface with an asymmetric antiresonant hollow-core fiber. An ultralow fusion splicing loss of 0.41 dB and a maintained polarization extinction ratio of 28 dB were demonstrated, with no additional intermediate component.

关键词： Optical fiber polarization Optical losses Thermal expansion Shape Splicing Laser modes Optical fiber communication

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Insulator Defect Detection Based on Improved YOLOv5 Model

Insulator Defect Detection Based on Improved YOLOv5 Model

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Software engineering and Artificial Intelligence (SEAI), IEEE International Conference on

作者： Yongxin Chen Zhenan Du Hengxuan Li Kanjun Zhang Pei Wen 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)9798350374346

ISBN: (纸本)9798350374353

In the power system, insulator is a very important type of power equipment. The defects in insulator will directly affect the stability of the system and the safety of workers. In order to quickly and accurately detect the defect of insulators in the high-voltage lines of the power grid, a detection method based on improved YOLOv5 model is proposed. For the convolutional layers in CSPLayer modules which are associated with feature output, self attention mechanism is introduced to improve the feature extraction ability of the model; and deep separable convolution is introduced to improve the detection efficiency. The experimental study is performed by comparing the proposed model with Faster R-CNN, YOLOv3, YOLOv4, and YOLOv5s. The experimental results show that the average detection accuracy of the proposed model is 94.79%, and the detection speed is 63.9FPS, which is superior to other methods under the same conditions.

关键词： YOLO Accuracy Attention mechanisms Convolution Power system stability Insulators Feature extraction

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Air Quality Forecasting with Hybrid LSTM and Extended Stationary Wavelet Transform

Research Square

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Research Square 2021年

作者： Zeng, Yongkang Ma, Xiang Jin, Ning Zhou, Xiaokang Yan, Ke Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province College of Information Engineering China Jiliang University Hangzhou310018 China Faculty of Data Science Shiga University Hikone5228522 Japan RIKEN Center for Advanced Intelligence Project RIKEN Tokyo1030027 Japan National University of Singapore Singapore117566 Singapore

Artificial intelligence (AI) technology-enhanced air quality forecasting is one of the most promising directions in the field of smart environment development. Despite recent advances in this area, two difficulties remain unsolved. First, multiple factors influence forecasting results, such as weather conditions, fuel usage and traffic conditions. These factors are usually unavailable in air quality sensor data. Second, traditional predicting models typically use the most recent training data, which neglects the historical data. In this study, we propose a hybrid deep learning model that embraces the merits of the stationary wavelet transform (SWT) and the nested long short term memory networks (NLSTM) to improve the prediction quality in the problem of hour-ahead air quality forecasting. The proposed method decomposes the original PM2.5 data into several more stationary sub-signals with different resolutions using an extended SWT algorithm. A framework that leverages several NLSTM recurrent neural networks is constructed to output forecasting results for different sub-signals, respectively. The final forecasting result is obtained by combining all sub-signal forecasting results using the inverse wavelet transform. Experiments on real-world data show that, accuracy-wise, our proposed method outperforms most of the existing prediction models in the literature. And the resulting forecasting curves of the proposed method are much closer to the real values without any lags, comparing with existing prediction models. © 2021, CC BY.

关键词： Wavelet transforms

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