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SSRN 2022年

作者： Zhou, Jing Zhu, Jiawei He, Weilan Cao, Yu Pang, Jinbo Ni, Jian Zhang, Jianjun School of Chemical Engineering Northeast Electric Power University Jilin132012 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education School of Electrical Engineering Northeast Electric Power University Jilin132012 China University of Jinan Jinan250022 China College of Electronic Information and Optical Engineering Nankai University Tianjin300350 China

Antimony selenide (Sb2Se3) has rapidly emerged in the field of photovoltaics using one-dimensional crystal structure. However, the power conversion efficiency (PCE) of Sb2Se3 solar cells is influenced by the orientation of the Sb2Se3 photoactive layers. In this study, we investigate the influence of substrate properties on the preferred orientation and microstructure of Sb2Se3 films systematically. With the rise of substrate surface temperature and the decline of substrate surface bonding energy, the preferred orientation of the Sb2Se3 films altered from (hk0) to (hk1) and finally to (002). After summarizing the performance of different preferentially oriented Sb2Se3 solar cells, the results showed that the (hk0)-preferentially oriented devices exhibited a poor performance of less than 1.1%. As the preferred orientation of Sb2Se3 absorbers changed from (hk0) to (hk1), the carrier transport changed from inter-ribbon charge hopping to transportation along the (Sb4Se6)n ribbons. This enhanced the carrier transport efficiency, thereby leading to the enhancement of the PCE to 2%–3%. Furthermore, when the (002) texture coefficient (TC) of the Sb2Se3 films was between 1.8 and 3.6, the PCE of the devices was further enhanced to above 3.5%. A maximum PCE of 4.79% can be obtained when the (002) TC was 3.24. This study reveals the relationship between the Sb2Se3 film preferred orientation and device performance, and demonstrates an effective way to precisely control the Sb2Se3 film microstructure to obtain a high PCE. © 2022, The Authors. All rights reserved.

关键词： Selenium compounds

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Fault Detection Method for Insulators Using Improved YOLOv4

Journal of Network Intelligence

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Journal of Network Intelligence 2022年第4期7卷 818-834页

作者： Zhao, Li-Quan Jiang, Zi-Cong Teng, Zi-Ming Jia, Yan-Fei Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University 168 Changchun Road Jilin132012 China Graduate school of Information Science and Electrical Engineering Kyushu University Fukuoka819-0395 Japan College of information and communication Jilin University Changchun130012 China School of Electrical and Information Engineering Beihua University Jilin132013 China

A defective insulator detection method based on improved You Only Look Once version 4 (YOLOv4) is proposed to improve the precision of defective insulator detection. This method designs a dual-branch attention block by simulating the attention process of the human eye, and introduces it into the backbone of YOLOv4 to extract richer information on defective insulator features. To make the output feature map of shallow layer network fuse more different scale features, a path aggregation network has been designed. To improve detection accuracy, the spatial pyramid pooling has been replaced by atrous spatial pyramid pooling. A dynamic non-maximum suppression method is proposed to improve defective insulator detection accuracy. It employs an adaptive threshold control strategy and weighted operation to full use of the predicted box. We compare our method with defective insulator detection methods based on YOLO and R-CNN. Our simulation results show that the proposed method is more accurate than defective insulator detection methods based on YOLO, and has a faster detection speed than methods based on R-CNN. Compared with the defective insulator detection method based on R-CNN that has the highest mean average precision, the mean average precision of the proposed method is lower, but its detection speed is faster. Compared with YOLOv4, its detection speed is slower, but the mean average precision is higher. The proposed method strikes a satisfactory tradeoff between detection speed and mean average precision. © 2022, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Object detection

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Day-ahead Intra-day Economic Dispatch Methodology Accounting for the Participation of Electrolytic Aluminum Loads and energy Storage in power system Peaking

Day-ahead Intra-day Economic Dispatch Methodology Accounting...

引用

power Science and technology (ICPST), IEEE International Conference on

作者： Wei Zheng Peng Yu Zhaoyang Xu Tianzhen Fan Hengyu Liu Meng Yu Jiong Zhang Junhui Li State Grid Liaoning Electric Power Supply Co. Ltd State Grid Fushun Electric Power Supply Company Liao Ning China State Grid Liaoning Electric Power Co. Ltd State Grid Liaoning Electric Power Company Limited Power Dispatch And Control Center Liao Ning China State Grid Electric Power Research Institute Co. Ltd State Grid Electric Power Research Institute Wuhan Efficiency Evaluation Co. Ltd Hu Bei China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology (Northeast Electric Power University) Ji Lin China State Grid Liaoning Electric Power Co. Ltd State Grid Liaoning Electric Power Company Limited Electric Power Research Institute Liao Ning China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

Under the background of dual-carbon target and large-scale new energy access, most of the existing power system scheduling modes focus on the power source side, ignoring the potential of load-side interaction with the grid for peak shifting. In order to promote two-way coordination and interaction on both sides of the source and load sides, and to guarantee the balance of power supply and demand on different time scales and the high level of new energy consumption, it is proposed to incorporate the representative electrolysis aluminum loads on the load side into the main body of the scheduling, and to optimize the dispatching of power supply and demand through the configuration of It is proposed that the representative electrolytic aluminum load on the load side should be included in the main body of dispatch, and by configuring battery energy storage devices on the load side, joint optimal dispatch with thermal power units containing carbon capture devices should be carried out. With the optimization objective of minimizing the operating cost of the power system, a joint day-ahead-intraday economic dispatch method is developed. Finally, simulation calculations are carried out with an example to show that the proposed peaking model can effectively guide the demand response of the aluminum loads, increase the rate of new energy consumption, and reduce the operating cost of the system at the same time.

关键词： energy consumption Costs power supplies Aluminum Optimal scheduling Wind power generation Regulation

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Wind power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach

arXiv

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arXiv 2022年

作者： Li, Yang Wang, Ruinong Li, Yuanzheng Zhang, Meng Long, Chao The Key Laboratory of Modern Power System Simulation Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The State Grid Jilin Electric Power Co. Ltd Jilin Power Supply Company Chuanying District Jilin132001 China The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of National Key Laboratory of Science and Technology Vessel Integrated Power System Naval University of Engineering Wuhan430033 China The School of Water Energy and Environment Cranfield University United Kingdom

In a modern power system with an increasing proportion of renewable energy, wind power prediction is crucial to the arrangement of power grid dispatching plans due to the volatility of wind power. However, traditional centralized forecasting methods raise concerns regarding data privacy-preserving and data islands problem. To handle the data privacy and openness, we propose a forecasting scheme that combines federated learning and deep reinforcement learning (DRL) for ultra-short-term wind power forecasting, called federated deep reinforcement learning (FedDRL). Firstly, this paper uses the deep deterministic policy gradient (DDPG) algorithm as the basic forecasting model to improve prediction accuracy. Secondly, we integrate the DDPG forecasting model into the framework of federated learning. The designed FedDRL can obtain an accurate prediction model in a decentralized way by sharing model parameters instead of sharing private data which can avoid sensitive privacy issues. The simulation results show that the proposed FedDRL outperforms the traditional prediction methods in terms of forecasting accuracy. More importantly, while ensuring the forecasting performance, FedDRL can effectively protect the data privacy and relieve the communication pressure compared with the traditional centralized forecasting method. In addition, a simulation with different federated learning parameters is conducted to confirm the robustness of the proposed scheme. Copyright © 2022, The Authors. All rights reserved.

关键词： Electric load dispatching

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Seismic Interpolation Transformer for Consecutively Missing Data: A Case Study in DAS-VSP Data

arXiv

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arXiv 2024年

作者： Cheng, Ming Lin, Jun Dong, Xintong Lu, Shaoping Zhong, Tie College of Instrumentation and Electrical Engineering Jilin University Jilin Changchun130026 China School of Earth Sciences and Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China Guangdong Zhuhai519000 China Guangdong Provincial Key Lab of Geodynamics and Geohazards Sun Yat-sen University Guangdong Guangzhou510275 China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Jilin132012 China Department of Communication Engineering College of Electric Engineering Northeast Electric Power University Jilin132012 China

Distributed optical fiber acoustic sensing (DAS) is a rapidly-developed seismic acquisition technology with advantages of low cost, high resolution, high sensitivity, and small interval, etc. Nonetheless, consecutively missing cases often appear in real seismic data acquired by DAS system due to some factors, including optical fiber damage and inferior coupling between cable and well. Recently, some deep-learning seismic interpolation methods based on convolutional neural network (CNN) have shown impressive performance in regular and random missing cases but still remain the consecutively missing case as a challenging task. The main reason is that the weight sharing makes it difficult for CNN to capture enough comprehensive features. In this paper, we propose a transformer-based interpolation method, called seismic interpolation transformer (SIT), to deal with the consecutively missing case. This proposed SIT is an encoder-decoder structure connected by some U-shaped swin-transformer blocks. In encoder and decoder part, the multi-head self-attention (MSA) mechanism is used to capture global features which is essential for the reconstruction of consecutively missing traces. The U-shaped swin-transformer blocks are utilized to perform feature extraction operations on feature maps with different resolutions. Moreover, we combine the loss based on structural similarity index (SSIM) and L1 norm to propose a novel loss function for SIT. In experiments, this proposed SIT outperforms U-Net and swin-transformer. Moreover, ablation studies also demonstrate the advantages of new network architecture and loss function. Copyright © 2024, The Authors. All rights reserved.

关键词： Optical fibers

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Capacity and power Allocation Strategy of energy Storage Participating in Grid Peak Shaving

Capacity and Power Allocation Strategy of Energy Storage Par...

引用

IEEE Conference on energy Internet and energy system Integration (EI2)

作者： Tengyun Qi Qiren Wu Jianping Liu Fei Xu Yajing Li He Li Yiming Wang Cuiping Li Junhui Li China Three Gorges Corporation Beijing China China Three Gorges Renewables(Group) Co. Ltd Beijing China State Key Laboratory of Power System and Power Generation Equipment Control and Simulation (Tsinghua University) Beijing China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China

ISBN: (纸本)9781665434263

High penetration wind power grid with energy storage system can effectively improve peak load regulation pressure and increase wind power capacity. In this paper, a capacity allocation method of energy storage system under peak load regulation scenario is proposed. The upper model combines the investment cost, operation cost, arbitrage income, environmental income, and wind power grid benefits during the entire life cycle of the energy storage system, with the goal of maximizing the net income during the energy storage life cycle; the lower model optimizes the charging and discharging power of the energy storage system according to each energy storage configuration scheme in the upper modeling, and its objective is to minimize the standard deviation of system net load and waste wind power. Finally, under the conditions of local grid load and wind power data, verified the effectiveness of capacity allocation strategy.

关键词： Costs system integration Production Wind power generation Lithium batteries Regulation Resource management

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MAE-GAN: A Novel Strategy for Simultaneous Super-resolution Reconstruction and Denoising of Post-stack Seismic Profile

arXiv

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arXiv 2024年

作者： Yu, Wenshuo Dong, Shiqi Lu, Shaoping Dong, Xintong The College of Instrumentation and Electrical Engineering Jilin University Jilin Changchun130026 China The Key Laboratory of Modern Power System Simulation and the Control and Renewable Energy Technology Ministry of Education Jilin Jilin City132012 China Department of Communication Engineering College of Electric Engineering Northeast Electric Power University Jilin Jilin City132012 China School of Earth Sciences and Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China Guangdong Zhuhai519000 China Guangdong Provincial Key Lab of Geodynamics and Geohazards Sun Yat-Sen University Guangdong Guangzhou510275 China

Post-stack seismic profiles are images reflecting containing geological structures which provides a critical foundation for understanding the distribution of oil and gas resources. However, due to the limitations of seismic acquisition equipment and data collecting geometry, the post-stack profiles suffer from low resolution and strong noise issues, which severely affects subsequent seismic interpretation. To better enhance the spatial resolution and signal-to-noise ratio of post-seismic profiles, a multi-scale attention encoder-decoder network based on generative adversarial network (MAE-GAN) is proposed. This method improves the resolution of post-stack profiles, and effectively suppresses noises and recovers weak signals as well. A multi-scale residual module is proposed to extract geological features under different receptive fields. At the same time, an attention module is designed to further guide the network to focus on important feature information. Additionally, to better recover the global and local information of post-stack profiles, an adversarial network based on a Markov discriminator is proposed. Finally, by introducing an edge information preservation loss function, the conventional loss function of the Generative Adversarial Network is improved, which enables better recovery of the edge information of the original post-stack profiles. Experimental results on simulated and field post-stack profiles demonstrate that the proposed MAE-GAN method outperforms two advanced convolutional neural network-based methods in noise suppression and weak signal recovery. Furthermore, the profiles reconstructed by the MAE-GAN method preserve more geological structures. Copyright © 2024, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Applications of MXenes in human-like sensors and actuators

引用

Nano Research 2023年第4期16卷 5767-5795页

作者： Jinbo Pang Songang Peng Chongyang Hou Xiao Wang Ting Wang Yu Cao Weijia Zhou Ding Sun Kai Wang Mark H.Rümmeli Gianaurelio Cuniberti Hong Liu Institute for Advanced Interdisciplinary Research(iAIR) Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of ShandongUniversity of JinanJinan 250022China Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics Dresden Technische Universität DresdenDresden 01069Germany Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China State Key Laboratory of Biobased Material and Green Papermaking Qilu University of TechnologyShandong Academy of SciencesJinan 250353China School of Bioengineering Qilu University of TechnologyShandong Academy of ScienceJinan 250353China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Ministry of Education) Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Weihai Innovation Research InstituteQingdao UniversityQingdao 266000China School of Electrical and Computer Engineering Jilin Jianzhu UniversityChangchun 130118China Institute for Complex Materials Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz StrasseDresden 01069Germany College of Energy Soochow Institute for Energy and Materials Innovations Soochow UniversitySuzhou 215006China Key L

Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.

关键词： MXenes sensors actuators gas sensors biosensors tactile sensors sound sensors artificial retina

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Super-Resolution Reconstruction of Electric power Inspection Images Based on Very Deep Network Super Resolution 6th

Super-Resolution Reconstruction of Electric Power Inspection...

引用

6th International Conference on Artificial Intelligence and Security, ICAIS 2020

作者： Shi, Bowen Gao, Jilong He, Zhentao Zhang, Tian Zhong, Tie Chen, Haipeng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin CityJilin132012 China College of Electrical Engineering Northeast Electric Power University Jilin CityJilin132012 China School of Physics Northeast Normal University Changchun130024 China

ISBN: (纸本)9783030578831

Aiming at the problem of getting low resolution image and blurred image during unmanned aerial vehicle (UAV) inspection, a super-resolution reconstruction algorithm based on very deep network super resolution (VDSR) is proposed. The algorithm model is composed of deep convolution neural network and residual structure, which is improved on the basis of super resolution convolutional neural network (SRCNN). By deepening the network to 20 layers, the receptive field can be expanded, and the residual structure can be combined to obtain better reconstruction effect. The experimental results show that the proposed super-resolution method based on VDSR has richer texture and more realistic visual effect, with 2.95 dB and 0.037 improvement in PSNR and SSIM compared with the super-resolution methods based on Bicubic Interpolation, Sparse Coding and SRCNN. The proposed algorithm further promotes the theoretical research of inspection image super-resolution, and can be effectively applied to the practical application of power inspection. © 2020, Springer Nature Switzerland AG.

关键词： Textures

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Single-stage Grid-connected Photovoltaic Generation Takes Part in Grid Frequency Regulation for Electromechanical Transient Analysis

Single-stage Grid-connected Photovoltaic Generation Takes Pa...

引用

2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Yan, Gangui Hu, Wenbo Jia, Qi Zhang, Shanfeng Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9781728135205

In order to solve the problem of insufficient frequency regulation capacity caused by the large-scale grid-connected photovoltaic (PV) generation, the active power-frequency droop control strategy and virtual inertia control strategy are proposed for single-stage grid-connected PV generation for electromechanical transient analysis. By modifying the control structure of the inverter, PV generation actively got involved in frequency regulation. The simulation results indicate that: the inverter can control the PV array to increase or decrease the active power generated according to the set droop control and virtual inertia control, so as to suppress the drop or rise of the grid frequency;in the dynamic process of frequency, the incremental power of PV generation induced by the dynamic action of the voltage vector of grid connection point is dependent on its virtual inertia control. © 2019 IEEE.

关键词： Transient analysis

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