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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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simulation research on primary frequency regulation coordination control strategy of hybrid wind-PV-ES power station based on AGC

Simulation research on primary frequency regulation coordina...

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Annual Meeting of CSEE Study Committee of HVDC and power Electronics (HVDC 2023)

作者： S. Li Y. Hu X. He Y. Zhu T. He C. Luo C. Deng G. Zeng M. Su Yunnan Electric Power Research Institute Kunming People's Republic of China National Energy Power Grid Technology R&D Centre Guangzhou People's Republic of China State Key Laboratory of HVDC Electric Power Research Institute CSG Guangzhou People's Republic of China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou People's Republic of China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou People's Republic of China

With the increase of wind and solar renewable energy penetration in power system, the frequency control ability of power system completely depending on traditional power supply has weakened. This actuality requires that renewable energy stations should be equipped with a certain amount of energy storage to improve the primary frequency control ability. This paper considers the fast response ability and flexible control of energy storage for both charging and discharging, as well as its unique frequency response characteristics. Firstly, the control characteristics of the primary frequency regulation of the hybrid wind-solar-storage power station(Wind-PV-ES) are analyzed. By improving the automatic generation control(AGC) strategy of the hybrid Wind-PV-ES power station, a coordinated control strategy for the primary frequency regulation of the hybrid Wind-PV-ES power station is proposed for different frequency ranges based on the improved AGC control. After the primary frequency regulation action, the energy storage output is given priority control before wind and solar. When the energy storage active margin is insufficient, use the frequency regulation capacity of wind and photovoltaic power system to improve the primary frequency regulation capacity of the hybrid Wind-PV-ES power station. The control strategy proposed in this paper can improve the primary frequency regulation capability of renewable energy station. Finally, the paper verifies the effectiveness of the proposed control strategy through simulation.

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Corrigendum to ‘Optimised configuration of multi-energy systems considering the adjusting capacity of communication base stations and risk of network congestion’ [energy volume 313 (2024) 133873]

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energy 2025年 314卷

作者： Dongfeng Yang Xi Wang Yong Sun Jingying Yang Xiaojun Liu Chao Jiang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin 132012 China State Grid Jilin Electric Power Co. Ltd Changchun 30000 China

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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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Response-Based Synchronization Stability Analysis of Multi-Converter power systems

Response-Based Synchronization Stability Analysis of Multi-C...

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

作者： Yuren Zhou Zihan Wang Gengyin Li Shiwei Xia Le Zheng Linlin Ma Dingyi Cheng Ting Wang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China Shandong Electric Power Dispatching and Control Center State Grid Shandong Electric Power Company Shandong China State Grid Shandong Electric Power Research Institute Power Grid Technology Center Shandong China

With the increasing integration of renewable energy into the power grid, the application of converters in the electrical systems has grown significantly. Due to the nonlinearity, the complexity and the difficult availability of the system models, traditional methods of synchronization stability analysis have revealed limitations and challenges when confronted with modern power systems. Additionally, the prevalence of grid-following converters in the grid leads to a shortage of voltage sources within the system, significantly increasing the risk of grid instability. This paper addresses the issue of synchronization stability analysis of multi-converter power systems, and proposes a response-based method to assess the synchronization stability level of the entire system. Through an analysis of the synchronization stability mechanism of grid-forming converters, a relationship is established between electromotive force, power angle, and node voltages. A quantitative stability evaluation of the system is achieved using the sBTTC index. Case studies show that the proposed response-based method is effective to analyze the synchronization stability of multi-converter power systems, with great practical viability in engineering applications.

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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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Selective Preferred Orientation for High-Performance Antimony Selenide Thin-Film Solar Cells Via Substrate Surface Modulation

SSRN

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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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Research on Transforming Effect and Calculation Method of MMC Converter on AC / DC Harmonics

Research on Transforming Effect and Calculation Method of MM...

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2021 IEEE Sustainable power and energy Conference, iSPEC 2021

作者： Cui, Liu Peng, Guangqiang He, Jingsong Wu, Jiyang Mao, Chizu Jiao, Ning Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc GuangZhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System GuangZhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid GuangZhou China Maintenance Test Center Ehv Power Transmission Company Guangzhou China Csg Key Laboratory for Dc Transmission Equipment State Evaluation and Fault Diagnosis GuangZhou China Sichuan University College of Electrical Engineering and Information Technology Chengdu China

ISBN: (纸本)9781665414395

Modular multilevel converter (MMC) is currently the most concerned voltage source converter topology in the field of flexible direct current transmission (VSC-HVDC). Due to its non-linear characteristics, harmonic components will inevitably be generated in AC and DC systems, which may affect the operation of equipment and system, cause protection equipment to malfunction, and cause interference to neighboring communications. The MMC converter is a non-linear device, which can be considered as an amplifying modulator with voltage and current conversion functions. The AC and DC networks are coupled to each other through the MMC converter to generate dynamic harmonic interaction. In recent years, harmonic instability problems have appeared in many VSC-HVDC projects. Compared with other converter topologies, the transfer relationship of harmonics on the AC and DC sides of MMC converters has not been studied in depth. In this paper, by studying the AC/DC harmonic conversion characteristics of MMC converters, it reveals the conversion law of MMC converters between AC/DC harmonics;through theoretical derivation, the quantitative calculation method of MMC harmonic transmission process is given. PSCAD simulation results prove the correctness of the above results. © 2021 IEEE.

关键词： Transmissions

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Conditional Adversarial Domain Adaption based on Self-attention

Journal of Network Intelligence

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Journal of Network Intelligence 2022年第1期7卷 175-188页

作者： Zhao, Li-Quan Zhang, Yu-Peng Teng, Zi-Ming Jiang, Zi-Cong Cui, Ying Kan, Zhong-Feng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China College of information and communication Jilin University Changchun130012 China Graduate school of Information Science and Electrical Engineering Kyushu University Fukuoka819-0395 Japan Zhuhai Power Supply Bureau Guangdong Electric Power Corporation Zhuhai519000 China Jilin Power Supply Bureau Jilin Electric Power Corporation Jilin132012 China

Transfer learning is a deep learning method. It transforms knowledge in the source domain and feeds it to the target domain to improve the performance of the target domain model. The conditional adversarial domain adaption method is one of a number of transfer learning methods. It uses Resnet as the feature extraction network;however, Resnet can only determine the relationship between local features, and so its feature extraction accuracy is limited. To overcome this problem, a self-attention layer has been designed in order to determine the relationship among all features. This layer is added between the fourth layer and fifth layer of Resnet. Besides, a cross-entropy function is introduced into loss function, and a sigmoid layer is designed and used as the out layer in conditional adversarial domain adaption. These produce gradient disappearance in the deep network, and influence the discriminator training effect. To solve that problem, a least squares function is used as to design the loss function. The new type of loss function does not require the sigmoid function. Using theoretical analysis, we explain how this new loss function can be used to solve the gradient disappearance problem, thus rendering the network structure more stable. We compare our proposed method with other datasets, including Joint Adaptation Networks, adversarial domain adaptation, conditional adversarial domain adaption, Resnet-50, domain-adversarial neural network on imageCLEF-DA, Office-Home, and Office-31. Our simulation results show that the proposed conditional adversarial domain adaption based on self-attention method has the fastest convergence speed and highest accuracy the among different datasets. © 2022, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Computer vision

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Closed-loop simulation Method of Stability control system Based on Virtual Component technology

Closed-loop Simulation Method of Stability Control System Ba...

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

作者： Qinfeng Ma Yihua Zhu Mingshun Liu Dongxu Chang Qingxin Pu Chengxiang Li Power Dispatching Control Center of Guizhou Power Grid Co. Ltd Guizhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China

The stability control system is an important means to ensure the safe and stable operation of the power system. In view of the shortcomings of the existing offline/real-time simulation test methods, a closed-loop simulation scheme based on virtual component technology is proposed. The virtual component technology of the stability control device is researched, and the virtualization method of the external hardware interface of the device is designed. On this basis, a closed-loop simulation framework of the stability control system under the offline/real-time simulation test environment is proposed. The functional logic of each component under the framework are analyzed. The calculation and feedback process of the entire closed-loop simulation system are analyzed in depth, which effectively solves the difficulty of simulation analysis and test verification of large-scale stability control system, providing a new method for the research and verification of stability control system strategy.

关键词： Analytical models Process control system integration power system stability control systems Stability analysis Hardware

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