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Partitioning Calculation Method of Short-Circuit Current for High Proportion DG Access to Distribution Network

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Energy Engineering 2024年第9期121卷 2569-2584页

作者： Wei Wang Qingzhu Shao Shaoliang Wang Yiwei Zhao Yuanbo Ye Duanchao Li Mengyu Wu Anhui Electric Power Dispatch and Control center State Grid Anhui Electric Power Co.Ltd.Hefei230000China School of Electrical Engineering Beijing Jiaotong UniversityBeijing100000China

Aiming at the problemthat the traditional short-circuit current calculationmethod is not applicable to Distributed Generation(DG)accessing the distribution network,the paper proposes a short-circuit current partitioning calculation method considering the degree of voltage drop at the grid-connected point of ***,the output characteristics of DG in the process of low voltage ride through are analyzed,and the equivalent output model of DG in the fault state is ***,by studying the network voltage distribution law after fault in distribution networks under different DG penetration rates,the degree of voltage drop at the grid-connected point of DG is used as a partition index to partition the distribution ***,iterative computation is performed within each partition,and data are transferred between partitions through split nodes to realize the fast partition calculation of short-circuit current for high proportion DG access to distribution network,which solves the problems of long iteration time and large calculation error of traditional short-circuit ***,a 62-node real distribution network model containing a high proportion of DG access is constructed onMATLAB/Simulink,and the simulation verifies the effectiveness of the short-circuit current partitioning calculation method proposed in the paper,and its calculation speed is improved by 48.35%compared with the global iteration method.

关键词： High proportion DG short-circuit calculation low voltage ride through partition iteration

Intelligent Predetermination of Generator Tripping Scheme: Knowledge Fusion-based Deep Reinforcement Learning Framework

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 66-75页

作者： Lingkang Zeng Wei Yao Ze Hu Hang Shuai Zhouping Li Jinyu Wen Shijie Cheng state Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronics EngineeringHuazhong University of Science and TechnologyWuhan 430074China Dispatching and Control center Central China Branch of State Grid Corporation of ChinaWuhan 430077China. Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN 37996USA

Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power *** improve efficiency of predetermination,this paper proposes a framework of knowledge fusion-based deep reinforcement learning(KF-DRL)for intelligent predetermination of ***,the Markov Decision Process(MDP)for GTS problem is formulated based on transient instability ***,linear action space is developed to reduce dimensionality of action space for multiple controllable ***,KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making *** can enhance the efficiency and learning ***,the graph convolutional network(GCN)is introduced to the policy network for enhanced learning *** simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.

关键词： Deep reinforcement learning generator tripping scheme graph convolutional network invalid action masking knowledgefusion

The influences of canopy temperature measuring on the derived crop water stress index

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中国生态农业学报（中英文） 2024年第9期32卷 1503-1519页

作者： WANG Hongxi LI Fei SHEN Hongtao LI Mengyu YIN Gongchao FANG Qin SHAO Liwei marketing service center of the state grid Hebei Electric Power Co. Ltd.Shijiazhuang 050035China Nanpi Agriculture and Rural Affairs Bureau Nanpi 061500China College of Agronomy Hebei Agricultural UniversityBaoding 071000China center for Agri-cultural Resources Research Institute of Genetics and Developmental BiologyChinese Academy of SciencesShijiazhuang 050022China

Crop water stress index(CWSI)is widely used for efficient irrigation *** canopy temperature(T_(c))measurement is necessary to derive a reliable *** objective of this research was to investigate the influences of atmospheric conditions,settled height,view angle of infrared thermography,and investigating time of temperature measuring on the performance of the *** irrigation treatments were used to create different soil water conditions during the 2020-2021 and 2021-2022 winter wheat-growing *** CWSI was calculated using the CWSI-E(an empirical approach)and CWSI-T(a theoretical approach)based on the T_(c).Weather conditions were recorded continuously throughout the experimental *** results showed that atmospheric conditions influenced the estimation of the CWSI;when the vapor pressure deficit(VPD)was>2000 Pa,the estimated CWSI was related to soil water *** height of the installed infrared thermograph influenced the T_(c)values,and the differences among the T_(c)values measured at height of 3,5,and 10 m was smaller in the afternoon than in the ***,the lens of the thermometer facing south recorded a higher T_(c)than those facing east or north,especially at a low height,indicating that the direction of the thermometer had a significant influence on T_(c).There was a large variation in CWSI derived at different times of the day,and the midday measurements(12:00-15:00)were the most reliable for estimating *** linear relationships were found between the transpiration rate and CWSI-E(R^(2)of 0.3646-0.5725)and CWSI-T(R^(2)of 0.5407-0.7213).The relations between fraction of available soil water(FASW)with CWSI-T was higher than that with CWSI-E,indicating CWSI-T was more accurate for predicting crop water *** addition,The R^(2)between CWSI-T and FASW at 14:00 was higher than that at other times,indicating that 14:00 was the optimal time for using the CWSI for crop water status *** hi

关键词： Canopy temperature Measuring time Measuring height and direction Crop water stress index

Deep Reinforcement Learning Based Resource Allocation for Fault Detection with Cloud Edge Collaboration in Smart grid

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1220-1230页

作者： Qiyue Li Yadong Zhu Jinjin Ding Weitao Li Wei Sun Lijian Ding Hefei University of Technology Engineering Technology Research center of Industrial Automation Hefei 230009China Electric Power Research Institute of state grid Anhui Electric Power Co. Ltd.Hefei 230000China Hefei University of Technology Hefei 230009China IEEE CSEE

Real-time fault detection is important for operation of smart *** has become a trend of future development to design an anomaly detection system based on deep learning by using the powerful computing power of the ***,delay of Internet transmission is large,which may make the delay time of detection and transmission go beyond the ***,the edge-based scheme may not be able to undertake all data detection tasks due to limited computing resources of edge ***,we propose a cloud-edge collaborative smart grid fault detection system,next to which edge devices are placed,and equipped with a lightweight neural network with different precision for fault *** addition,a sub-optimal and realtime communication and computing resource allocation method is proposed based on deep reinforcement *** method greatly speeds up solution time,which can meet the requirements of data transmission delay,maximize the system throughput,and improve communication *** results show the scheme is superior in transmission delay and improves real-time performance of the smart grid detection system.

关键词： Cloud-edge collaboration communication delay deep reinforcement learning fault detection smart grid

A Cloud-Fog Enabled and Privacy-Preserving IoT Data Market Platform Based on Blockchain

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2237-2260页

作者： Yurong Luo Wei You Chao Shang Xiongpeng Ren Jin Cao Hui Li School of Cyber Engineering State Key Laboratory of Integrated Service NetworkXidian UniversityXi’an710126China

The dynamic landscape of the Internet of Things(IoT)is set to revolutionize the pace of interaction among entities,ushering in a proliferation of applications characterized by heightened quality and *** the pivotal applications within the realm of IoT,as a significant example,the Smart grid(SG)evolves into intricate networks of energy deployment marked by data *** evolution concurrently entails data interchange with other IoT ***,there are also several challenges including data-sharing overheads and the intricate establishment of trusted centers in the IoT *** this paper,we introduce a hierarchical secure data-sharing platform empowered by cloud-fog ***,we propose a novel non-interactive zero-knowledge proof-based group authentication and key agreement protocol that supports one-to-many sharing sets of IoT data,especially SG *** security formal verification tool shows that the proposed scheme can achieve mutual authentication and secure data sharing while protecting the privacy of data *** with previous IoT data sharing schemes,the proposed scheme has advantages in both computational and transmission efficiency,and has more superiority with the increasing volume of shared data or increasing number of participants.

关键词： IoT data sharing zero-knowledge proof authentication privacy preserving blockchain

Optimal Planning of Hybrid AC/DC Low-voltage Distribution Networks Considering DC Conversion of Three-phase Four-wire Low-voltage AC Systems

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 141-153页

作者： Bo Zhang Lu Zhang Wei Tang Gen Li Chen Wang the College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China the Electric Energy Group Department of Engineering TechnologyTechnical University of Denmark(DTU)2750 BallerupDenmark the Power Distribution Technology center State Grid Beijing Electric Power Research InstituteBeijing 100075China

The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple pow er quality problems by the flexible power regulation capability of voltage source *** paper proposes schemes to es tablish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC op *** characteristics and DC conversion constraints of typical LVDNs are *** addition,converter configura tions for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC ***,an optimal planning method of hybrid AC/DC LVDNs is proposed,which is modeled as a bi-level programming model considering the annual investments and three-phase *** are conducted to verify the effectiveness of the proposed optimal planning *** ulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reduc ing issues related to voltage violation and unbalance.

关键词： Optimal planning low-voltage distribution net work three-phase unbalance DC conversion

Modeling of Large-Scale Hydrogen Storage System Considering Capacity Attenuation and Analysis of Its Efficiency Characteristics

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Energy Engineering 2024年第2期121卷 291-313页

作者： Junhui Li Haotian Zhang Cuiping Li Xingxu Zhu Ruitong Liu Fangwei Duan Yongming Peng Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Ministry of Science and Technology Electric Power Research Institute of State Grid Liaoning Electric Power Co.Ltd.Shenyang110006China Northeast Electric Power Dispatching Control center Northeast Branch of State Grid Corporation of ChinaShenyang110180China

In the existing power system with a large-scale hydrogen storage system,there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage *** order to improve the hydrogen utilization rate of hydrogen storage system in the process of participating in the power grid operation,and speed up the process of electric-hydrogen-electricity *** article provides a detailed introduction to the mathematical and electrical models of various components of the hydrogen storage unit,and also establishes a charging and discharging efficiency model that considers the temperature and internal gas partial pressure of the hydrogen storage *** models are of great significance for studying and optimizing gas storage *** these models,the performance of gas storage units can be better understood and *** studies are very helpful for improving energy storage efficiency and sustainable *** factors affecting the charge-discharge efficiency of hydrogen storage units are *** integrating the models of each unit and considering the capacity degradation of the hydrogen storage system,we can construct an efficiency model for a large hydrogen storage system and power conversion *** addition,the simulation models of the hydrogen production system and hydrogen consumption system were established in MATLAB/*** accuracy and effectiveness of the simulation model were proved by comparing the output voltage variation curve of the simulation with the polarization curve of the typical hydrogen production system and hydrogen consumption *** results show that the charge-discharge efficiency of the hydrogen storage unit increases with the increase of operating temperature,and H2 and O2 partial voltage have little influence on the charge-discharge *** the process of power conversion system converter rectification operation,its efficiency decreases wi

关键词： Hydrogen storage system simulation modeling electrolyzer fuel cell capacity loss

Reinforcement Learning-Based MAS Interception in Antagonistic Environments

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 270-272页

作者： Siqing Sun Defu Cai Hai-Tao Zhang Ning Xing the School of Artificial Intelligence and Automation the MOE Engineering Research Center of Autonomous Intelligent Unmanned Systemsthe Guangdong Engineering Technology Research Center of Fully Autonomous Unmanned Surface VehiclesHuazhong University of Science and TechnologyWuhan 430074China the state grid Hubei Electric Power Research Institute Wuhan 430074China IEEE

Dear Editor, As a promising multi-agent systems(MASs) operation, autonomous interception has attracted more and more attentions in these years, where defenders prevent intruders from reaching *** far, most of the relevant methods are applied in ideal environments without agent damages. As a remedy, this letter proposes a more realistic interception method for MASs suffered by damages.

关键词： agent MAS destination

Very Short-Term Forecasting of Distributed PV Power Using GSTANN

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1491-1501页

作者： Tiechui Yao Jue Wang Yangang Wang Pei Zhang Haizhou Cao Xuebin Chi Min Shi Computer Network Information center of the Chinese Academy of Sciences Beijing 100190China University of Chinese Academy of Sciences Beijing 100190China School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China state grid Hebei Electric Power Co. Ltd.Shijiazhuang 050000China

Photovoltaic(PV)power forecasting is essential for secure operation of a power *** prediction of PV power can improve new energy consumption capacity,help power system planning,promote development of smart grids,and ultimately support construction of smart energy ***,different from centralized PV power forecasts,three critical challenges are encountered in distributed PV power forecasting:1)lack of on-site meteorological observation,2)leveraging extraneous data to enhance forecasting performance,3)spatial-temporal modelling methods of meteorological information around the distributed PV *** address these issues,we propose a Graph Spatial-Temporal Attention Neural Network(GSTANN)to predict the very short-term power of distributed ***,we use satellite remote sensing data covering a specific geographical area to supplement meteorological information for all PV ***,we apply the graph convolution block to model the non-Euclidean local and global spatial dependence and design an attention mechanism to simultaneously derive temporal and spatial ***,we propose a data fusion module to solve the time misalignment between satellite remote sensing data and surrounding measured on-site data and design a power approximation block to map the conversion from solar irradiance to PV *** conducted with real-world case study datasets demonstrate that the prediction performance of GSTANN outperforms five state-of-the-art baselines.

关键词： Distributed photovoltaic power forecasting graph convolutional networks satellite images spatial-temporal attention