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Research and Application of Electronic Data Retrieval in Material Supply Chain Enhanced by Large Language Models and Knowledge Graph

Research and Application of Electronic Data Retrieval in Mat...

引用

Information technology, Communication Ecosystem and Management (ITCEM), International Conference on

作者： Xing Ge Yafei Liu Pei Yang Xin Sun Junfeng Qiao Luyao Qu Jingyi Qiu State Grid Jiangsu Electric Power CO. LTD. Material Branch Nanjing China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology & China Electric Power Research Institute Beijing China

ISBN: (数字)9798331542696

ISBN: (纸本)9798331542702

In response to the new goals of building green and modern smart supply chains, the electric power equipment supply chain is experiencing a shift toward digital intelligence and low-carbon, environmentally friendly development [1]. However, traditional search platforms based on relational databases face challenges in handling vast amounts of multimodal electronic data. These platforms often suffer from low search accuracy, limited cross-dimensional correlation analysis capabilities, and inefficiencies, making them inadequate for constructing comprehensive big data platforms that integrate and share information across the entire green, modern, smart supply chain. This paper introduces an innovative electronic data retrieval method designed to meet the data retrieval needs of material supply chains. By integrating large language models with knowledge graph technology, it proposes an electronic data retrieval system that leverages vector database technology for text embedding of multimodal data. Additionally, artificial intelligence is used to enable knowledge retrieval and augmented generation, significantly enhancing data retrieval capabilities within the specialized domain of material supply chains.

关键词： Green buildings Large language models Supply chains Knowledge graphs Relational databases Data retrieval Vectors power systems Information technology Faces

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Research and Application of Distribution Network Planning Based on Digital Twinning technology

Research and Application of Distribution Network Planning Ba...

引用

Decision Science & Management (ICDSM), International Conference on

作者： Junfeng Qiao Lin Peng Aihua Zhou Zhujian Ou Xiaoyi Xu Fuyun Zhu State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co. LTD Nanjing China Nantong Power Supply Company State Grid Jiangsu Electric Power Co. LTD Nanjing China

To satisfy the requirement of electric distribution grid planning brought by the forward annual electricity consumption growth and power grid expand, to determine where, when, and which type of substations, lines or distributed electric power generation device will be built. The future distribution network planning must adopt electric power flow, dynamic change of load and new distributed power generation in various directions, and build an electric distribution grid with grid structure. The results of distribution network planning has a huge impact on the operation efficiency of the power grid, the safety of electricity use, and the allocation of asset investment. This paper uses digital twinning, advanced computing and other technologies to divide and evaluate the scope of power supply, load characteristics, and user demand, and the scale of power facilities. With the power supply reliability demand as the core, it plans and builds a target network framework with high voltage quality, reasonable structure, flexible operation, and unified grid division standards, effectively giving play to the key role of planning in the construction and operation of distribution networks.

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Research and Implementation of Multi Fusion Data Model Construction technology for Distribution Network Digital Twins

Research and Implementation of Multi Fusion Data Model Const...

引用

Decision Science & Management (ICDSM), International Conference on

作者： Junfeng Qiao Lin Peng Aihua Zhou Zhujian Ou Yanfang Mao Sen Pan State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co. LTD Nanjing China Nantong Power Supply Company State Grid Jiangsu Electric Power Co. LTD Nanjing China

The core of digital twin is the digital reconstruction of physical space, that is the physical space perception and processed data are applied to the virtual space to achieve real-time mapping of physical space through full integration of data. With the rapid development of digital twin technology in the power field, in order to achieve the purpose of real-time data fusion of physical space and virtual space in the digital twin of distribution network, the virtual and real data fusion processing technology for digital twin has become the focus of research in the power field. In this paper, firstly, the characteristics and ontology technology of power digital twin virtual and real data are studied, and an ontology based virtual and real data fusion architecture is proposed. Then, a semantic feature extraction method is proposed for the structured and unstructured virtual and real data of power digital twin, and the extracted semantic features are formatted, described and stored. Then the overall architecture of the distribution network digital twin virtual real data fusion system is designed, the technical route of the system is analyzed and discussed, and the virtual real data fusion processing is completed using the similarity algorithm and fusion rules based on the elements between ontology. Finally, the functional modules of the distribution network digital twin virtual real data fusion system are divided and introduced, and the digital twin virtual real data fusion of the fan hub casting process is verified as an example.

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Microservice Anomaly monitoring Method based on Multi-dimensional Spatiotemporal Feature Reconstruction

Microservice Anomaly Monitoring Method based on Multi-dimens...

引用

Artificial Intelligence and Intelligent Manufacturing (AIIM), International Symposium on

作者： Jing Zeng Ji Lai Shuo Li Xian Li Ruxia Yang Information Communication Branch State Grid Jibei Electric Power Co. Ltd. Beijing China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology China Electric Power Research Institute Nanjing China

ISBN: (数字)9798331541729

ISBN: (纸本)9798331541736

In a modern microservice architecture, the largescale distribution of services and high concurrency access make anomaly monitoring particularly complex. Traditional monitoring methods usually rely on a single data dimension, such as request delay or resource utilization, making capturing complex abnormal patterns challenging. Therefore, this paper proposes a microservice anomaly monitoring method based on multidimensional spatiotemporal feature reconstruction, aiming to reconstruct the complete feature space by integrating different data sources to improve the accuracy and robustness of anomaly detection. This paper’s method first extracts adequate data, such as service response time and service call chain from the tracking dataset, with time and space as the core and constructs it into a multi-dimensional feature matrix, fully considering the spatial and temporal correlation between microservices. Second, this paper introduces a deep learning model combining convolutional neural networks and gated recurrent cells to capture dynamic dependence and feature interactions in spatiotemporal dimensions. The convolutional neural network module extracts the spatial dependence through the convolution operation, while the gating cycle unit module captures the changing trend of the time series. By paralleling two modules and introducing the attention mechanism, the model is optimized with the reconstruction error, and finally, the network abnormality is judged by setting the threshold.

关键词： Adaptation models Attention mechanisms Microservice architectures Computer architecture Feature extraction Robustness Spatiotemporal phenomena Convolutional neural networks monitoring Anomaly detection

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Device Identification based on Network Traffic Fingerprint

Device Identification based on Network Traffic Fingerprint

引用

Artificial Intelligence and Intelligent Information Processing (AIIIP), International Conference on

作者： Tianqi Wu Xiaoming Zhou Hongbin Wu Daojuan Zhang Yingjie Zhang Xiao Han State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute co. Ltd Beijing China Operations Safety and Technology Department State Grid Liaoning Electric Power Supply Co. Ltd. Liaoning China

The devices connected to the LAN have the security risk of being counterfeited and remotely controlled. To identify and understand the devices in the network in advance, the administrator can monitor and handle the abnormal devices in advance. At present, the device recognition method based on deep learning has some limitations. In this paper, the fingerprint information related to the device type is extracted from the network traffic, and the deep learning algorithm based on graph neural network is used to deeply mine the traffic feature hiding relationship between devices, and effectively identify various device types and device models. The effect of the model in this paper on the task of device identification of public data sets has been greatly improved.

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Research and Implementation of Spatial Layout Algorithm and Optimization technology for Digital Twin Objects of Distribution Network Facilities

Research and Implementation of Spatial Layout Algorithm and ...

引用

International Conference on Applied Machine Learning (ICAML)

作者： Junfeng Qiao Lin Peng Aihua Zhou Zhujian Ou Xiaoyi Xu Jianguang Yao State Grid Laboratory of Power cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co. LTD Nanjing Jiangsu China Nantong Power Supply Company State Grid Jiangsu Electric Power Co. LTD Nanjing Jiangsu China

The equipment and facilities in the distribution network include not only primary equipment such as transformers, circuit breakers, lightning arr-esters, capacitors, but also secondary equipment such as transfer switches, buttons, indicator lights, current and voltage meters. The total number of equipment types exceeds 200, and the average number of equipment in provincial areas exceeds 100 million. Equipment management is very arduous. The equipment management system in the power industry records the basic archive information of all these equipment, including equipment nameplate, equipment type, equipment operation mode, and geographic information. With the rapid development of power applications, the two-dimensional information description in device management systems cannot meet the needs of more complex power applications. The spatial description and layout of device objects is the foundation for the next step of power business applications. To address this issue, this paper proposes a layout and optimization algorithm for the digital twin object space of distribution network facilities, which visualizes distribution network equipment and facilities, and describes the three-dimensional features of the equipment using point cloud description methods, providing a spatial layout and optimization method for the equipment. The method proposed in this paper has been applied and verified in actual power production and maintenance business, improving the efficiency of power operation and maintenance work.

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Design of a Data Provenance Scheme with Virtual Tuple-Based Database Watermarking

Design of a Data Provenance Scheme with Virtual Tuple-Based ...

引用

Chinese Automation Congress (CAC)

作者： Qi Wang Aihua Zhou Yiqing Wang Zhen Zheng Jing Jiang Ruxia Yang State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute co. LTD Nanjing China State Grid XuZhou Power Supply Company Xuzhou China Qingpu Power Supply Company State Grid Shanghai Municipal Electric Power Company Shanghai China

The security of power grid is closely related to national security and social stability. With the development of smart grid and big data, grid data security has ushered in new challenges. The data provenance is one of the key issues. Considering the complexity of grid data storage types, this paper designs a virtual tuple-based data provenance scheme. This scheme firstly embedding the watermark with user identity through virtual tuple injection. Then, the data with watermark is distributed in the form of table splitting, which makes it possible to quickly locate the suspect user when a data leakage event occurs. Finally, the leaker is identified through watermark extraction and comparison. The simulation experiments show that our scheme has good robustness against insertion, replacement and deletion attacks.

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A comprehensive assessment method for the power structured data classification and grading based on hierarchical analysis

A comprehensive assessment method for the power structured d...

引用

International Conference on Communications, Information System and Computer Engineering (CISCE)

作者： Yujia Zhai Xiuli Huang Congcong Shi Shenglong Liu Hao Zhang State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. LTD Nanjing China Big Data Center of State Grid Corporation of China Beijing China State Grid Shandong Electric Power Company Jinan China

With the transformation of the digital development of power grids, the classification and grading of structured data for electricity is an important basis for data security protection. Existing methods for assessing data classification and grading results are mostly always based on individual indicators of the model's operational results. However, such methods can only evaluate a single performance indicator of that result, and cannot provide a comprehensive evaluation of all performance indicators. This paper proposes a comprehensive assessment method for the power structured data classification and grading based on hierarchical analysis, which allows various quality elements of the model to be extracted according to different needs, establishes a hierarchical indicator system, and determines the weights of each indicator in the system by means of hierarchical analysis, and finally calculates a comprehensive quality score for the classification and grading results. Finally, the method is systematically validated using different classification and grading models.

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Attack-Aware Capability Assessment Method Based on Specific Semantic Search

Attack-Aware Capability Assessment Method Based on Specific ...

引用

International Conference on Electronic Engineering and Informatics (EEI)

作者： Daojuan Zhang Qi Zhao Yuman Wang Shu Li Zheng Tian Yizhen Sun State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute co. Ltd Beijing China Hunan Provincial Key Laboratory of Internet of Things in Electricity State Grid information & Communication Company of Hunan Electric Power Corporation Changsha China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

In this paper, we propose an attack perception capability assessment method based on the specific semantic search for the problem of attack perception capability assessment of security protection equipment for power monitoring systems. The method aims to improve the recognition and localization accuracy of common attacks by accurately correlating the output products of security equipment with the execution of attack test cases. The research employs an attack-specific semantic generation technique that combines attack attribute values with timestamps to form specific semantics for subsequent matching. Pattern matching algorithm, specifically the BM (Boyer-Moore) algorithm, is further utilized to match the specific semantics with the output products of the security device Snort to achieve attack localization. Experimental results demonstrate that Snort exhibits high accuracy in perceiving the majority of attack types and exhibits an enhanced perception rate compared to certain baseline methods. In summary, the method proposed in this paper effectively improves the sensing ability of security equipment to attacks on the power monitoring system and provides a new idea for the performance evaluation of security protection equipment.

关键词： Location awareness Performance evaluation Accuracy Semantic search Sensors security protection Informatics monitoring Pattern matching

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Research on Secure Data Circulation and Sharing protection technology Framework for power monitoring System

Research on Secure Data Circulation and Sharing Protection T...

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International Conference on Networking and Network Applications (NaNA)

作者： Weicong Huang Jieying Zhou Minghui Jin Zheng Han Sijia Wei State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. LTD. Nanjing China National Power Dispatching and Control Center State Grid Corporation of China Beijing China State Grid Shanghai Municipal Electric Power Company Shanghai China

With the increasing frequency of data circulation and sharing in power monitoring systems, traditional network-centric protection strategies are insufficient to resist the growing risk of data leakage. This article analyzes the security risks in existing typical data circulation and sharing scenarios based on the demand for data security sharing in power monitoring systems. A data security protection technology framework covering the source layer, interaction layer, and terminal layer has been proposed from the perspectives of basic protection capabilities and key protection technologies, as well as an evaluation method for the protection technology capabilities of data circulation and sharing. This provides a reference idea for effectively enhancing the data circulation and sharing protection capabilities of power monitoring systems.

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