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Evolution and Challenges of the New-Type power System: Transformation under the Carbon Neutrality Goal

Evolution and Challenges of the New-Type Power System: Trans...

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2024 International Conference on Advanced Control Systems and Automation Technologies, ACSAT 2024

作者： Wang, Tengyan Li, Nige Chen, Lu Chen, Mu State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing Branch of China Electric Power Research Institute Co. Ltd. Nanjing China

ISBN: (纸本)9798331541668

Amid the severe backdrop of global climate change, achieving carbon peaking and neutrality has emerged as a universal consensus and the cornerstone of energy policies worldwide. As the largest energy consumer and carbon emitter, China's profound transformation of its power system holds paramount significance for global climate governance. This paper delves into the backdrop, characteristics, current development status, multifaceted challenges, and future trends of China's newtype power system. It aims to provide theoretical underpinnings and practical guidance for accelerating the realization of the 'dual carbon' (carbon peaking and neutrality) goals. Additionally, this research explores the application of advanced control and automation technologies in the power system transformation. For example, the intelligent grid technologies, such as the Internet of Things and big data analytics, play a crucial role in enhancing the grid's sensing and control capabilities, which are essential aspects of advanced control systems. Moreover, the research on energy storage technology and its integration into the power system involves innovative control strategies and optimization algorithms, directly contributing to the field of automation technologies in the power sector. © 2024 IEEE.

关键词： Carbon sequestration

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Research on a digital twin dynamic polymerization technology 7

Research on a digital twin dynamic polymerization technology

引用

7th International Conference on Mechatronics and Intelligent Robotics, ICMIR 2023

作者： He, Zhimin Peng, Lin Yu, Hai Wang, He State Grid Smart Grid Research Institute Co. LTD Nanjing Jiangsu210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing Jiangsu210003 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

In this paper, a kind of digital twin dynamic polymerization technology based on clustering and intelligent analysis is studied. In the first step, the goal and business requirements of device-level digital twin polymerization are studied, and the principle of hierarchical and distributed dynamic polymerization of device-level digital twin is proposed. The second step analyzes the dynamic characteristics of the county energy Internet source network charge and storage, and studies the spatio-Temporal dynamic aggregation modeling technology of the device-level digital twin based on the dynamic characteristics of the source network charge and storage. The third step is to study the hierarchical polymerization framework and polymerization method of the virtual power plant at the source, load and storage side facing the distributed multi-level interaction framework of the county energy Internet, the hierarchical polymerization framework and polymerization method of the county energy Internet side, and the hierarchical polymerization framework and polymerization method of the virtual power plant at the source, load and storage side facing the county network side. © 2023 SPIE. All rights reserved.

关键词： Polymerization

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Research on Virtual and Real Spatial Data Interconnection Mapping technology for Digital Twin 4th

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4th International Conference on 3D Imaging Technologies- Multidimensional Signal Processing and Deep Learning, 3D IT-MSP and DL 2022

作者： He, Zhimin Peng, Lin Yu, Hai Wang, He State Grid Smart Grid Research Institute Co. LTD Jiangsu Nanjing210003 China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology NanjingJiangsu210003 China

ISBN: (纸本)9789819912292

In recent years, distributed photovoltaics, decentralized wind power, new loads, electric vehicles, etc. have been connected to the power grid in a wide range, and the distribution network has become more active, with strong fluctuations, and large peak-to-valley differences. The management and coordination of distributed resources interaction put forward higher requirements. This paper conducts research on the data interconnection and mapping technology of virtual and real space for digital twins. The first step is to study the modeling and driving technology of data interconnection, fusion mechanism model, and information model based on the real twin of the power grid. Coordinate data and monitoring data of main and auxiliary equipment and the data interconnection mechanism of the power grid real scene twin, build a dual-mode driving method that integrates the mechanism model and data model;the second step is to study the power grid "virtual-real" space multi-service continuous mapping mechanism and real-time data. The panoramic mapping method realizes the continuous and real-time mapping of point data and surface data to the digital twin and realizes multi-block, multi-level, and multi-type mapping according to the steps of feature extraction, feature matching, model parameter estimation, transformation, and interpolation. The digital twin data is accurately matched;the third step is to study the efficient transmission and update integration technology of twin data in the power grid environment, research methods to improve the real-time and concurrency of data transmission, and research multi-source heterogeneous data dynamic update and integration technology. The fourth step is to study the two-way intelligent cooperation and integration technology of station equipment, realize real-time data interaction and state interaction between the virtual digital model and the real physical model, and realize the interconnection and mapping between the station panoramic m

关键词： Mapping

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Multi-source System Log Behavior Pattern Mining Method Based on FP-Growth

Multi-source System Log Behavior Pattern Mining Method Based...

引用

2023 International Conference on Communication Network and Machine Learning, CNML 2023

作者： Zhang, Daojuan Wu, Tianqi Zhou, Xiaoming Hu, Bo Zhang, Wenjie State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd Beijing China State Grid Liaoning Electric Power Supply Co. Ltd. Shenyang China

ISBN: (纸本)9798400716683

By analyzing and mining system logs, it is possible to effectively discover behavioral characteristics and anomalies of network users or systems. Through association analysis, patterns and correlations between different log sources can be identified, thereby enabling the detection of various intrusion behaviors in computer networks. To address the challenge of handling massive and complex log data, this paper proposes a multi-source system log behavior pattern mining method based on FP-Growth. This method efficiently extracts frequent patterns and abnormal behaviors from large-scale system logs. Firstly, to ensure data quality and facilitate subsequent data mining processes, we perform necessary structuring and cleansing of raw logs and transform them into a format suitable for data analysis. Subsequently, given the variations in structure and content across different types of logs, we conduct distinct feature extraction for each type of log to retain essential information and generate transaction items. The data is then organized into datasets based on temporal partitions, forming a transaction database as input for the association rule mining algorithm. Finally, utilizing the FP-Growth association rule mining algorithm, this paper explores the relationships between entries from various types of single and multi-source logs. Based on metrics such as support, appropriate association rules are selected for behavior pattern mining. Experimental results demonstrate that the proposed method effectively uncovers typical behavior patterns. © 2023 ACM.

关键词： Association rules

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An instruction level attack detection method for new power load system based on LSTM

An instruction level attack detection method for new power l...

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2024 International Conference on Smart grid and Artificial Intelligence, SGAI 2024

作者： Yao, Qigui Zhang, Xiaojian Fei, Jiaxuan Yao, Minglu Li, Ye State Grid Smart Grid Research Institute Co. Ltd. Nanjing210003 China State Grid Laboratory of Power Cyber-security Protection and Monitoring Technology China State Grid Tianjin Electric Power Company Tianjin300384 China

To realize the efficient instruction level attack detection of the new power load resource management system under the load resource coordination and control interactive service scenario, this article proposes a novel LSTM adaptive sequence classification detection method combining MTM feature modeling and GAN countermeasure sample generation. In this method, the system operation instruction model based on MTM is established, and the generalized instruction features are expressed in detail. Simultaneously, large quantities of confrontation samples are generated by the GAN Network, which is similar to the real samples, and the problem of data imbalance in model training is solved. Finally, this paper proposes an adaptive coefficient-based LSTM for system instruction feature learning and testing and realizes the detection and recognition of hidden instruction level attacks in the new power load resource management system, which is more accurate and efficient than other methods. © Published under licence by IOP Publishing Ltd.

关键词： Long short-term memory

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Microservice Anomaly monitoring Method based on Multi-dimensional Spatiotemporal Feature Reconstruction 4

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

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Zeng, Jing Lai, Ji Li, Shuo Li, Xian Yang, Ruxia 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: (纸本)9798331541729

In a modern microservice architecture, the large-scale 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. © 2024 IEEE.

关键词： Convolutional neural networks

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NFA Regular Expression Matching based Electriuec power Sensitive Data Recognition Algorithm Design and Simulation

NFA Regular Expression Matching based Electriuec Power Sensi...

引用

2023 International Conference on Communication Network and Machine Learning, CNML 2023

作者： Yao, Qigui Zhang, Xiaojian Fei, Jiaxuan Ji, Wen Guo, Caiwei State Grid Smart Research Institute CO.LTD Nanjing China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing China State Grid Fujian Electric Power CO.LTD Fujian China

ISBN: (纸本)9798400716683

In the era of big data, electric power sensitive data recognition and network intrusion detection are concerned. Accurate pattern matching based sensitive data recognition software has low matching efficiency, poor flexibility and high resource consumption. However, regular expression matching is widely used because of its strong semantic expression ability and high flexibility. Aiming at the problems such as the small number and simple form of regular expressions supported by traditional NFA algorithm, this paper proposes an improved NFA regular expression matching algorithm for sensitive data recognition based on the iterative combination of metacharacter preprocessing, completes the regular expression matching algorithm and FPGA hardware logic circuits design. The simulation results based on Vivado platform show this algorithm can achieve efficient and fast matching of regular expressions with strong flexibility and less resource consumption. © 2023 ACM.

关键词： Field programmable gate arrays (FPGA)

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Research and implementation of topology data quality improvement system in electric distribution network 7

Research and implementation of topology data quality improve...

引用

7th International Conference on Mechatronics and Intelligent Robotics, ICMIR 2023

作者： Qiao, Junfeng Zhou, Aihua Peng, Lin Shen, Xiaofeng Pan, Sen Yang, Pei Huang, Chenhong State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co.LTD Nanjing Jiangsu210003 China Qingpu Power Supply Company State Grid Shanghai Electric Power Company Shanghai201799 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

The demand for lean management of distribution network is growing. However, the current identification of distribution network data quality lacks a unified standard and can not achieve automatic data verification and processing, which restricts the improvement of distribution network application level. In the actual distribution network application, more experts rely on their experience to solve the quality and availability problems of local distribution network topology data as needed, lacking a global data quality evaluation and *** the development of smart grid, the demand for lean management of distribution network is growing. However, the current identification of distribution network data quality lacks a unified standard and can not achieve automatic data verification and processing, which restricts the improvement of distribution network application level. In actual distribution network applications, more experts rely on their experience to solve the quality and availability problems of local distribution network topology data as needed, Lack of overall data quality evaluation and solutions. This paper first combs the status quo and quality problems of distribution network topology data, collates and summarizes the current status quo of distribution network topology data, summarizes the problems existing in the application of distribution network topology data, and researches and classifies the problems, laying a foundation for the development of distribution network topology data quality evaluation system and distribution network topology data verification rules. © 2023 SPIE. All rights reserved.

关键词： Topology

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Detecting Anomalous Behaviours Based on System Logs: A Dynamic Graph Perspective 8

Detecting Anomalous Behaviours Based on System Logs: A Dynam...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Wang, Ming Wang, Yuman Wu, Tianqi Chen, Cen Qian, Kexiang State Grid Corporation of China Co. Ltd Beijing China State Grid Smart Grid Research Institute Co. Ltd China Sgri Power Grid Digitizing Technology Department State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology China State Grid Henan Electric Power Company China State Grid Henan Electric Power Research Institute China State Grid Laboratory of Power Monitoring System Cyber Security Technical Standard Verification China School of Information and Communication Engineering Beijing University of Posts and Telecommunications China

ISBN: (纸本)9798350302455

System logs provide rich information about the current system's state. To make use of system logs, various existing work extracts a causal graph from the log events, and then applies graph-based machine learning algorithms to detect the anomalous behaviors. One limitation of these work is that they treat the graph in a static way, neglecting the dynamic nature of anomalous behaviors. In this paper, we propose to detect anomalous behaviors based on system logs using dynamic graph modeling. Our method consists of several key steps, including negative sampling which helps to balance the dataset, edge encoding which encodes the spatial information for each behavior, and sequence modeling which further models the temporal information. Experimental evaluations on real datasets demonstrate the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Graphic methods

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Research and implementation of automatic generation of electrical topology based on topology optimization technology 7

Research and implementation of automatic generation of elect...

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7th International Conference on Mechatronics and Intelligent Robotics, ICMIR 2023

作者： Qiao, Junfeng Zhou, Aihua Peng, Lin Yang, Pei Pan, Sen Huang, Xingde Shen, Xiaofeng State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co.LTD Nanjing Jiangsu210003 China Qingpu Power Supply Company State Grid Shanghai Electric Power Company Shanghai201799 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

Under the development and reform of the new power grid, the technology of drawing single line diagrams also needs to be developed and reformed urgently. In the past, single line diagrams were drawn mostly by manpower. On the premise of given data and topology structure, the drafters first sorted out the topological relationship between the components, and then placed the components on the canvas with the principle of minimizing line crossings, and the canvas size needs to be reduced as much as possible, And draw the graph W in a way that is easy to understand with the aid of CAD and other tools. This paper adopts a new decomposition model to solve the problem of power system single line mapping. First, the steps of electrical topology automatic mapping are decomposed into H steps. Using the knowledge of graph theory in mathematics instead of the form of polynomials, multiple processing objectives are processed separately, and H different methods are used to process them step by step. Then, the improved mapping algorithm is used to generate the plane embedding of electrical graph topology, which is used to achieve the goal of minimizing the intersection of lines. Then, the improved least cost flow graph method is used to process the graphic dexterity with the least cross. On the one hand, the graphic elements are evenly distributed, on the other hand, the horizontal and vertical orthogonal graphs are generated and the bending of the lines is minimized. © 2023 SPIE. All rights reserved.

关键词： Flow graphs

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