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Electrical engineering (CIYCEE), IEEE China International Youth Conference on

作者： Xinze Wang Ping Tan Xinyi Shen Yinjie Lin Songbin Chen Haimin Xiong Zhihong Qian State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

Scan path optimization in proton therapy requires efficient intelligent optimization algorithms. In this study, we discuss the optimization of the genetic algorithm (GA) for scan path optimization from three aspects: generating initial paths using heuristic algorithms, optimizing the genetic parameters of GA, and incorporating an elite preservation strategy. We propose a heuristic elite-genetic algorithm (HE-GA) and compare it with commonly used simulated annealing (SA) and GA, finding that HE-GA demonstrates higher accuracy, better stability, and faster computation. Using HE-GA under discrete scanning, we analyze tumor cases under different scanning dead times and observe that optimizing the total scanning time by reducing the scanning dead time can lead to improvements. This enables repetitive scanning with the same duration as the zigzag scanning pattern, providing better protection for patients' critical organs.

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Distribution Grid Topology Estimation Using 1D-CNN

Distribution Grid Topology Estimation Using 1D-CNN

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International Joint Conference on Energy, Electrical and Power engineering, CoEEPE 2021

作者： Tong, Li Liang, Haiwei Zou, Xudong State Grid Zhejiang Electric Power Research Institute Hangzhou310000 China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430070 China

ISBN: (纸本)9789811919213

In order to improve the safety level and economy of distribution grid, a flexible and reconfigurable grid topology is the basic feature of future smart distribution grid. Many advanced functions of intelligent distribution grid, such as state estimation, power flow calculation and voltage control, require a correct grid topology as a prerequisite. Therefore, it is of great significance to find an accurate topology estimation method for distribution grid. This paper proposes a topology estimation method based on the one-dimensional convolutional neural network (1D-CNN). The proposed method firstly obtains the required voltage amplitude and phase angle data of distribution grid through simulation. The data should be standardized after the first step. Then the processed data is used to train the 1D-CNN model. Finally, the trained 1D-CNN model can be used for topology estimation. Compared to the existing methods, the proposed method does not need much historical data of each node in the distribution grid, and the calculation speed can support the online topology estimation. Meanwhile, this method is suitable for radial and weak loop grid structures. The effectiveness and superiority of the proposed method are validated by IEEE 33-node distribution grid. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electric load flow

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Optimal Real-time Operation Strategy of Microgrid with Power-to-Hydrogen Device: An ADP Approach 5

Optimal Real-time Operation Strategy of Microgrid with Power...

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5th International Conference on Energy, Electrical and Power engineering, CEEPE 2022

作者： Lu, Xun Zhong, Zhiyao Xue, Xizhen Wu, Yunyun Ai, Xiaomeng Fang, Jiakun China Southern Power Grid Company Limited Guangdong Power Grid Corporation Guangzhou China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China

ISBN: (纸本)9781665479059

This paper proposes an Approximate Dynamic Programming (ADP) approach for obtaining the optimal real-time operation strategy of microgrid with power-to-hydrogen (P2H) device. Firstly, the real-time operation model of microgrid with P2H is established, then a piece-wise linear function based approximate dynamic programming is proposed to solve the operation model. With the direction of the slope update and training policies under various training scenarios, the proposed ADP approach can obtain the approximate optimal real-time operation strategies to cope with uncertainties. Case studies verify the superiority of the proposed ADP approach compared with Model Predictive Control approach (MPC). © 2022 IEEE.

关键词： Training Power engineering Uncertainty Simulation Microgrids Linear programming Real-time systems

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Research on Reconstruction Algorithm of Terahertz Signal Based on Compressed Sensing 3

Research on Reconstruction Algorithm of Terahertz Signal Bas...

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3rd IEEE China International Youth Conference on Electrical engineering, CIYCEE 2022

作者： Zeng, Guang Zhang, Chi Zhou, Xingyu Sun, Qitai Xiong, Yongqian Wuhan National High Magnetic Field Center Huazhong University of Science and Technology Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan430074 China

ISBN: (数字)9781665477321

ISBN: (纸本)9781665477321

Numerous features of terahertz make it increasingly prominent in the field of nondestructive testing, but terahertz time domain spectroscopy (THz-TDS) imaging system has the problems of long acquisition time and large amount of data. Compressed sensing theory points out that if the signal meets the sparsity condition in a domain, the original signal can be reconstructed with a number of sampling points far lower than that required by the Nyquist sampling theorem. In this research, the ideal terahertz signal and the measured terahertz signal are reconstructed by using the orthogonal matching pursuit algorithm and the sparsity adaptive matching pursuit algorithm. The results indicate that the ideal terahertz signal can be precisely reconstructed with a sampling rate of only about 15%, and the measured terahertz signal only needs about 25%. This research provides a reliable guarantee for the application of compressed sensing in THz-TDS imaging technology. © 2022 IEEE.

关键词： Compressed sensing

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Optimal Design of Axial Permanent Magnet Hysteresis Damper Based on PSO and Hook-Jeeves Algorithm 3

Optimal Design of Axial Permanent Magnet Hysteresis Damper B...

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3rd IEEE China International Youth Conference on Electrical engineering, CIYCEE 2022

作者： Chen, Jinqiao Wang, Shuang Shang, Huidong Peng, Tao Wuhan National High Magnetic Field Center Huazhong University of Science and Technology Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan430074 China

ISBN: (数字)9781665477321

ISBN: (纸本)9781665477321

In this paper, the operation principles and basic properties of the axial permanent magnet hysteresis damper (APHD) are introduced. First, the double-side APHD (DSAPHD) is taken as an example to analyze the magnetic flux distribution in the stators and the rotor. According to the magnetic flux distribution in the rotor, a finite element (FE) model is established to calculate the minimum and maximum torque of DSAPHD, which has a faster calculation speed. A hybrid method of particle swarm optimization (PSO) and Hook-Jeeves direct search algorithm is used to design and optimize the DSAPHD. This reduces the influence of design experience, resulting in optimal design parameters. The optimized result has a smaller minimum torque while meeting the required maximum torque. Compared with the calculation results of the vector hysteresis model, the simplified FE model has higher calculation accuracy, which can be used in the design of APHD. © 2022 IEEE.

关键词： Hysteresis

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Fault Current Analysis of DFIG Considering Multi-time Scale Protection and Control under Asymmetrical Voltage Dips

Fault Current Analysis of DFIG Considering Multi-time Scale ...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Ziyu Yang Yingbiao Li Jiabing Hu State Key Laboratory of Advanced Electromagnetic and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

The characteristics of asymmetrical short-circuit current of doubly fed induction generators (DFIGs) are different from those of synchronous generators (SGs). With the increase in the quantity and capacity of DFIGs, the analysis and calculation of the asymmetrical short-circuit current of DFIGs are vitally important for the safe and stable operation of modern power systems. Under asymmetrical fault conditions, protection circuits and control strategies of DFIGs have multi-time scale characteristics and the equivalent circuit will change accordingly. Moreover, the negative-sequence internal voltage of DFIG is controllable, which makes the analysis more complex. This paper proposed an analytical calculation method of the asymmetrical short-circuit fault current and the characteristics of fault current are analyzed considering the multi-time scale control and protection. Finally, the proposed expression is validated in MATLAB/Simulink.

关键词： Voltage fluctuations Short-circuit currents Doubly fed induction generators Protective relaying Stators Synchronous generators Power systems

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Inverse Design of electromagnetic Induced Transparency Metamaterials Based on Generative Adversarial Network

Inverse Design of Electromagnetic Induced Transparency Metam...

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Electrical engineering (CIYCEE), IEEE China International Youth Conference on

作者： Xingyu Zhou Peishuai Tian Yanqi Hu Qitai Sun Yongqian Xiong State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

The unique properties of electromagnetic induced transparency (EIT) metamaterials have caused a lot of concern in the field of terahertz wave regulation, but the traditional design methods of metamaterials have the problems of long design cycle and high trial and error cost. Applying deep learning method to the inverse design process of terahertz metamaterials can greatly reduce the design complexity, so that the EIT metamaterial structure can be quickly designed according to the requirements. In this paper, a generative adversarial network (GAN) model for EIT metamaterial structure design is constructed, which realizes the mapping relationship between target spectrum and metamaterial structure parameters. The proposed GAN model can accurately predict structure parameters of the EIT metamaterial according to the target spectrum, and the error between the generated and the real parameters is less than 1μm. Moreover, by introducing the fuzzy processing, the proposed GAN model can accurately generate multiple sets of metamaterial structure according to the same target spectrum, which provides more options for designers. This model offers a novel and efficient design method for EIT metamaterials.

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The Accelerated Life Test Investigation and Lifetime Prediction Method for LED Driver 5

The Accelerated Life Test Investigation and Lifetime Predict...

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5th International Conference on Power and Energy Applications, ICPEA 2022

作者： Gong, Chen Xu, Haiping Yuan, Zengquan Liang, Jinhua Institute of Electrical Engineering Chinese Academy of Sciences Key Laboratory of Power Electronics and Electric Drive Beijing China Institute of Electrical Engineering and Advanced Electromagnetic Drive Technology Qilu Zhongke Jinan China

ISBN: (纸本)9781665487610

Reliability evaluation for products with long lifetime and high reliability is a great challenge in reliability engineering. LED luminaires are one of the most popular lighting solutions of the current society due to their long-lasting and energy-efficient. The system reliability of the LED luminaire is determined by the performance of the driver electronics. This paper analyzes the LED driver failure forms and the possible causes, in order to study the failure mechanism of LED driver and predict the lifetime. The accelerated life model of the driver is also established and the method to get the parameters in the model has been discussed. A high accelerated life testing platform has been built to test the sample's lifetime and get the parameters in the accelerated life model. The lifetime of sample is estimated by the model quickly and correctly. © 2022 IEEE.

关键词： Light emitting diodes

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Hourly-Level Analytical Maintenance Optimization for Large-Scale Offshore Wind Farms: Case Study for Planned Projects in Guangdong

SSRN

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SSRN 2023年

作者： Han, Jingzuo Guo, Xinyang Chen, Xinyu State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

Deployment of offshore wind power is growing from around 6 GW in 2019 towards over 200 GW in 2030 in China. Number of wind turbines in an offshore wind project is increasing from 165 in the largest project worldwide in 2022 towards over 1400 in Guangdong, China in 2030. Maintenance, which accounts for 33% of the life-cycle expenses, is primarily subject to ambient restrictions. With the increased turbine number in large-scale offshore wind farms, their availability will be further reduced. Optimizing the size and mix of maintenance fleets presents a significant opportunity to improve the availability of large-scale offshore wind farms. However, rigorous quantitative analyses of its effectiveness based on real-world project data are lacking. Additionally, suitable models for the maintenance optimization of large-scale offshore wind farms are also scarce, since existing models have overlooked turbine-level deviation and hourly-level variation, which usually leads to inevitable simplification errors. Here, an hourly-level analytical maintenance optimization model targeted at the large number of wind turbines is proposed to optimize maintenance performance. The model optimizes hourly maintenance decisions for each turbine and vessel individually, distinguishing their individual locations and states. The model is applied to evaluate potential benefits from maintenance fleet transformations in Eastern Guangdong, where about 5500 turbines are planned to be in operation by 2030. The effectiveness of enlarged fleet size, accelerated vessel cruise speed, expanded vessel capacity and enhanced vessel wave height resistance is analyzed. Our study reveals that coordinated improvement in vessel wave height resistance and vessel capacity by only 0.5m and 25%, respectively, could elevate large-scale offshore wind farm availability by over 30%. In contrast, enlarging the vessel fleet size by over 133% and increasing the vessel cruise speed by almost 82% could only raise it by around

关键词： Offshore wind farms

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Double Closed-loop Self-regulating Active Gate Driver with High-bandwidth Peak Voltage Sampling Circuit

Double Closed-loop Self-regulating Active Gate Driver with H...

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European Conference on Power Electronics and Applications

作者： Xinbo Chen Han Peng Shijie Song State Key Laboratory of Advanced Electromagnetic Engineering and Technology (AEET) School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

In this article, a double closed-loop self-regulating active gate driver (DCSAGD) for power device is proposed. The high-bandwidth peak detection circuit based on operational trans-conductance amplifier realize the accurate sampling of v DS_peak in the ns-level turn-off process. The closed-loop control strategy is realized at low cost by all analog circuit. The experimental results show that the system can accurately control v DS_peak at 500V/40A working condition under two reference voltage of 700V and 730V.

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