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检索条件"机构=State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology"

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Research and Application of Digital Modeling technology Based on Multi-source Data of power grid

Research and Application of Digital Modeling Technology Base...

引用

作者： Qiao, Junfeng Yu, Hai He, Zhimin Shen, Lianteng Du, Xiaodong State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd. Nanjing China China Electric Power Research Institute Co. Ltd. Beijing China State Grid Hebei Electric Power Co. Ltd. Shijiazhuang China

During the production and operation process, power enterprises generate rich power data, which is distributed and stored in multiple power application information systems. Due to past management reasons, there are significant differences in the description rules of data among different power application information systems, and due to the different data structures of various business processes, their storage structures and media also vary greatly. For example, for the operation and maintenance data generated during the operation and maintenance work, mainly photo and video data, this data must be stored in a large file storage server. The power consumption information sales data, which is composed of discrete numerical data, is stored in the relational database. In response to the above issues, this article proposes a method for constructing a power multi-source data model, which unifies the modeling of heterogeneous power data from multiple sources to meet the digital construction and service needs of power business. For file system data, build a file retrieval directory, store it in a relational data table, and establish an association model with relational data to achieve data connectivity of business meaning. This model can provide data services for power application scenarios, and power business application managers can directly call the model interface to meet the needs of power applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Information systems

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grid Engineering Point Cloud Device Clustering Segmentation and Three-Dimensional Shape Retrieval technology for grid Digital Handover Method 5th

Grid Engineering Point Cloud Device Clustering Segmentation ...

引用

5th International Conference on 3D Imaging Technologies—Multidimensional Signal Processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Wang, Gang Wang, He Wang, Fei Yu, Hai Fan, Zikai State Grid Smart Grid Research Institute CO. LTD Nanjing210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing210003 China State Grid Jiangsu Electric Power Co. Ltd. Economic and Technological Research Institute Nanjing210009 China

ISBN: (纸本)9789819751808

The power grid infrastructure design model requires the transfer of digital design data to the power grid operation and maintenance, but the current digital transfer lacks intelligent components such as serial transfer data and automatic feedback correction for specific application scenarios. There are problems in the clustering and segmentation of single devices in the power grid engineering point cloud, as well as the three-dimensional shape description and retrieval of power grid devices. This paper studies the technology of point cloud target extraction and verification. Based on the characteristics of the 3D handover model, point cloud data is preprocessed using a direct pass filter. Point cloud filtering methods based on terrain filtering and 3D model filtering are used to achieve point cloud ground processing. An improved region growth method based on the boundary eigenvalue of the 3D handover model is used to segment the point cloud model, and a deep neural network is introduced, research on 3D key point extraction methods and feature descriptors for point clouds suitable for complex power equipment to improve the accuracy of apparent 3D shape matching and retrieval of power grid equipment. Through the research methods in this article, it is easier to segment and extract individual points from point clouds and achieve automatic association mapping of main equipment extraction and equipment point clouds with corresponding models in the model library. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： power grids

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Risk Assessment of Distributed PV Microgrids Under cyber Attacks based on CNN-AE 8

Risk Assessment of Distributed PV Microgrids Under Cyber Att...

引用

8th International Conference on Smart grid and Smart Cities, ICSGSC 2024

作者： Qiu, Shenjian Guo, Shiang Shao, Zhipeng Fei, Jiaxuan Liu, Quan Pan, Kaikai State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. LTD. Nanjing China Zhejiang University School of Electrical Engineering Hangzhou China State Grid Jiangsu Electric Power Co. Ltd. Yangzhou Power Supply Branch Yangzhou China

ISBN: (纸本)9798350377408

The widespread application of smart grid technology and numerous Internet of Things (IoT) devices expose microgrid vulnerability to various cyber attacks. Moreover, the complex interactions and implicit risk propagation within the system pose challenges in accessing the risk from cyber attacks. To this end, we propose a risk assessment method for distributed PV microgrids under cyber attacks. This program employs an autoencoder (AE) architecture where convolutional neural networks (CNN) serve as the intermediate layer to extract the local features of data exchange from adjacent nodes. The AE conducts unsupervised learning using power data under normal operating conditions, thus performing risk assessment by evaluating the reconstruction errors. To validate the proposed method, we conducted training on the algorithm using historical data and the topology of a real scenario of a distributed photovoltaic microgrid and tested the risk assessment with various fake data injection attacks (FDIA) and Denial of Service (DoS) attacks. © 2024 IEEE.

关键词： cyber attacks

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A Web Attack Detection Method Based on DistilBERT and Feature Fusion for power Micro-Application Server 2

A Web Attack Detection Method Based on DistilBERT and Featur...

引用

2nd International Conference on Advanced Electronics, Electrical and Green Energy, AEEGE 2023

作者： Nige, Li Lu, Chen Lei, Zhao Zhenning, Teng Zhiqiang, Wang Yiyang, Shao Xiaolin, Gui State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co.Ltd. Nanjing China Xi'an Jiaotong University Faculty of Electronic and Information Engineering Shaanxi Province Key Laboratory of Computer Network Xi'an China

ISBN: (纸本)9798350322866

The widespread use of power micro-applications has significantly expanded the attack surface of their server side, thus increasing the risk of vulnerability attacks such as SQL injection, XSS, and CRLF injection. To ensure the security of power systems, these attacks must be detected precisely and timely. Therefore, this paper proposes a server-side web attack detection method based on DistilBERT and feature fusion for HTTP and HTTPS requests. The method treats HTTP and HTTPS requests as text data, specifically, extracts deep semantic features using DistilBERT, and fuses them with well-designed empirical features to comprehensively characterize and classify the request. Consequently, anomalous requests can be detected. The experimental results show that the accuracy, precision, recall, and F1 score of the method on HTTP CSIC 2010 and FWAF datasets are close to or higher than 99%. Compared with other methods as far as we known, this method has better performance and efficiency. © 2023 IEEE.

关键词： cybersecurity

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Three-Dimensional Model Resume Transfer technology for the Entire Lifecycle of power grid Equipment 5th

Three-Dimensional Model Resume Transfer Technology for the E...

引用

5th International Conference on 3D Imaging Technologies-Multidimensional Signal Processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Wang, Gang Wang, Fei Yu, Hai Fan, Zikai Wang, He State Grid Smart Grid Research Institute Co. Ltd. Nanjing210003 China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology Nanjing210003 China State Grid Jiangsu Electric Power Co. Ltd. Economic and Technological Research Institute Nanjing210009 China

ISBN: (纸本)9789819751839

This article analyzes the differences in device naming and archiving between data files in the infrastructure and operation stages of the power grid, and studies the method of device naming association based on relative layout reasoning. The steps involved are as follows: Establish connection edges between nodes in the topology map of the power grid scene layout, use the layout adjacency relationship between known structural elements to infer adjacent unknown device entities, and obtain their naming semantic elements to achieve the association of different naming methods for equipment in the infrastructure and operation inspection stages. Build an association network for on-demand matching of key business processes in the power grid for equipment resume data retrieval requirements, generate an index for resume data retrieval requirements, obtain spatiotemporal mapping associations of cross link and multi-stage equipment resumes, and achieve equipment resume archiving and updating. Build an association network for on-demand matching of key business processes in the power grid for equipment resume data retrieval requirements, generate an index for resume data retrieval requirements, obtain spatiotemporal mapping associations of cross link and multi-stage equipment resumes, and achieve equipment resume archiving and updating. Develop a 3D model data correction component for construction and transportation transfer, establish a record based construction and transportation transfer mechanism for the entire lifecycle of equipment level, and enhance the support of digital transfer results for transportation and inspection business. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Office equipment

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Research on digital transfer and correction technology for 3D model of power grid

Research on digital transfer and correction technology for 3...

引用

2024 International Conference on Electronics, Electrical and Information Engineering, ICEEIE 2024

作者： Wang, Gang Wang, He Yu, Hai Wang, Fei Fan, Zikai Dai, Jiao State Grid Smart Grid Research Institute CO. Ltd. Nanjing210003 China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology Nanjing210003 China State Grid Jiangsu Electric Power Co. Ltd. Economic and Technological Research Institute Nanjing210009 China

ISBN: (数字)9781510686809

ISBN: (纸本)9781510686793

The design drawings in power grid engineering construction usually need to be transferred to the equipment operation and maintenance stage. However, due to the differences between the actual construction process and the design drawings, manual adjustment has the problems of large workload and low efficiency. This article proposes the intelligent registration and reconstruction of power grid engineering data twins, which solves the problem of the lack of grid based 3D point cloud data for modifying and adjusting the design drawings of substations in related technologies, and improves the accuracy of operation and maintenance control after transferring the 3D design drawings to the operation and maintenance stage. This article studies the application of transfer model data in unmanned aerial vehicle inspection business for power transmission and transformation, improving the safety of unmanned aerial vehicle autonomous inspection and enhancing the reusability of transfer models by operation and inspection departments. © 2024 SPIE.

关键词： Reusability

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Design of an Automated security protection System for power System 4

Design of an Automated Security Protection System for Power ...

引用

2023 4th International Conference on Computer Engineering and Intelligent Control, ICCEIC 2023

作者： Xia, Jun Li, Jun Jiang, Xinfan Zhou, Bo Xi, Zesheng State Grid Hunan Electric Power Co. Ltd Changsha China State Grid Hunan Electric Power Co. Ltd. Hunan Energy Big Data Intelligence Ltd Changsha China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd Nanjing China

ISBN: (纸本)9798350308877

In situations involving power system applications, a design plan for a new kind of automated security protection system has been put out. The self-repair vulnerability module, attack detection module, security policy configuration automation module, and front-end monitoring interface have all been designed for this article. This prototype system can secure device privacy and system stability while generating security policies automatically, responding to attacks quickly, and operating and maintaining expenses. This mostly entails the creation of self-repair and mining techniques for terminal vulnerabilities as well as detection techniques for malicious terminal-based assaults. In order to automatically create security protection device linkage methods, the automation module is configured to accept vulnerability and attack alert information. Each module opens its own database or offers interface forms for interactive operation and administration, while the front-end monitoring interface is created concurrently. © 2023 IEEE.

关键词： Automation

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Design of an energy management system based on digital twins

Design of an energy management system based on digital twins

引用

2024 International Conference on Optics, Electronics, and Communication Engineering, OECE 2024

作者： He, Zhimin Peng, Lin Yu, Hai Wang, He Zhou, Jianqi Feng, Zhenyuan State Grid Smart Grid Research Institute Co. Ltd. Jiangsu Nanjing210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Jiangsu Nanjing210003 China State Grid Zhejiang Electric Power Co. Ltd. Jiaxing Power Supply Company Zhejiang Jiaxing314000 China

ISBN: (纸本)9781510685437

In the construction of clean and low-carbon community energy management systems, the challenges of the new era of low-carbon community development lie in monitoring and utilizing the massive panoramic information obtained from physical equipment within the community, constructing digital twin models of intelligent clean energy systems, and achieving multi-energy complementarity and energy conservation and emission reduction. Based on the optimization and complementarity of multi-energy interconnected systems and the coordinated operation control technology of "source-grid-load-storage," this paper designs a digital twin-based green and low-carbon community energy system operation management platform that integrates the needs of multiple business scenarios. By integrating modeling, simulation, artificial intelligence, and hierarchical control across multiple temporal and spatial scales through digital twin technology, this platform offers functions such as energy planning, operation and control, demand response, distributed energy trading, and carbon neutrality services. It addresses the issues of information barriers hindering the development of clean energy systems such as "source-grid-load-storage integration" in energy systems, effectively supporting key aspects of integrated energy systems, including planning and design, optimized operation, online safety analysis, and equipment health management. © 2024 SPIE.

关键词： Zero-carbon

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Research and Implementation of Building a Digital Twin Model for Electric grid Based on Deep Learning

Research and Implementation of Building a Digital Twin Model...

引用

International Conference on Artificial Intelligence and Communication Technologies, ICAICT 2023

作者： Qiao, Junfeng He, Zhimin Yu, Hai Shen, LianTeng Du, Xiaodong State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co. LTD Jiangsu Nanjing210003 China China Electric Power Research Institute Co.Ltd Beijing100192 China State Grid Hebei Electric Power Co. LTD Hebei Shijiazhuang050021 China

ISBN: (纸本)9789819969555

In the production of the power industry, digital twin technology is mainly used for the dispatch and distribution of electricity. Through real-time monitoring and analysis of key indicators in the dispatch center of the power company, the operation level and power supply service quality of the power company are improved. At present, the digital twin applications in the power industry are mainly used for indicator monitoring and process analysis, with the main goal of monitoring being existing collected data, lacking real-time analysis of higher-order data. With the continuous expansion of electricity consumption scale, the electricity demand of electricity customers is also becoming increasingly rich, which correspondingly drives the data generated in various business processes of power enterprises to develop towards a trend of high-dimensional and high-order. Traditional data processing and mining technologies are no longer able to quickly characterize and describe such high-order and high-dimensional data. Only by utilizing more efficient data analysis methods can we meet the current demand for power digital twin services. This article proposes a method for constructing a power grid digital twin model based on deep learning methods, which conducts deep learning on high-dimensional and high-order data in the power grid, identifies its features, and constructs a data category classifier to promote the construction of a power grid digital twin model that is more needed for load power business analysis, and improve the usability and applicability of the power grid digital twin model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electric power utilization

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Deep Learning-Based Control Model for Electronic Evidence Access Rights 4

Deep Learning-Based Control Model for Electronic Evidence Ac...

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4th International Conference on Information Science, Parallel and Distributed Systems, ISPDS 2023

作者： Chen, Peng Li, Yongliang Gao, Xianzhou State Grid Ningxia Electric Power Co.Ltd. Ningxia750001 China State Grid Ningxia Electric Power Co.Ltd. Electric Power Research Institute Ningxia750002 China State Grid Smart Grid Research Institute Co. Ltd. Nanjing210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing210003 China

ISBN: (纸本)9798350337181

With the rapid development of digitalization and intelligence in smart grids, how to identify untrusted users in the electric power system and implement user access control based on electronic evidence has become an important research topic. A credible assessment needs to be made on the subject users accessing electronic evidence. In this paper, we propose a deep learning-based user multi-dimensional attribute feature extraction access control model, which considers multi-dimensional attribute features such as user identity, behaviour, and device information, and determines whether the user is a legitimate access user by using CNN-Transformer deep learning framework to extract user features and determine their trust value. Through simulation experiments, it is proved that the access permission control model proposed in this paper has high accuracy and reliability and can meet the access requirements of different electronic evidence users. © 2023 IEEE.

关键词： Smart power grids

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