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共 17242 条记录，以下是141-150 订阅

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Distribution Transformer Operation Risk Assessment Method Based on early Warning Domain Analysis 6

Distribution Transformer Operation Risk Assessment Method Ba...

引用

6th ieee international conference on Power, Intelligent computing and Systems, ICPICS 2024

作者： Guo, Guowei Zhan, Ximei Chen, Cong Shi, Xuntao Sun, Jian Qiu, Yangxin Xiao, Xiaobing Foshan Shunde Power Supply Bureau Guangdong Power Grid Co. Ltd. China Southern Power Grid Foshan China Electric Power Research Institute Csg China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350374315

Aiming at the problem of the operation condition evaluation of distribution transformers, a practical evaluation method based on the fusion analysis of load rate, three-phase current unbalance rate and voltage difference between the head and end of the distribution zone is proposed. The operating state of the distribution transformer is described as the operating point of the three-dimensional coordinate of load rate, three-phase current unbalance rate and voltage difference between the beginning and the end of the distribution station area. By analyzing the location of the operation point in the operation area, the early warning level is determined. Multi- dimensional operation data is integrated, and the operation risk classification assessment is carried out on the distribution station area through the joint research and judgment of the mild risk early warning line and the severe risk early warning surface, which is conducive to the accurate grasp of the operation conditions of the distribution station area by the operation and maintenance personnel. The results of example analysis show the validity and reliability. © 2024 ieee.

关键词： Distribution transformers

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Time Series Anomaly Detection Based on Normalized Flow and Bayesian Networks 9

Time Series Anomaly Detection Based on Normalized Flow and B...

引用

9th ieee international conference on Data science in Cyberspace, DSC 2024

作者： Yao, Honglei Liu, Donglan Chang, Yingxian Liu, Xin Tang, Chaofan State Grid Shandong Electric Power Research Institute Jinan China State Grid Shandong Electric Power Company Jinan China Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China

ISBN: (纸本)9798350391367

Time series anomaly detection often faces significant challenges due to the high dimensionality, interdependence, and label sparsity of the data. Traditional methods struggle to model the intricate relationships between multiple time series components and often fail to accurately detect anomalies due to insufficient data dependence mining. To address these issues, we introduce GCRNF, a novel Graph-enhanced Standardized Flow Model that incorporates a Bayesian network for causality modeling. This model decomposes joint probabilities into conditional probabilities and utilizes a graph dependency encoder with hybrid CNN-RNN models and Graph Convolutional Networks (GCNs). Our experimental results demonstrate that GCRNF outperforms existing methods in density estimation, anomaly detection, and drift identification within time series distributions. Specifically, GCRNF showed a significant improvement in detection accuracy and robustness compared to traditional methods, providing a more effective solution for identifying anomalies in complex multivariate time series data. © 2024 ieee.

关键词： Markov processes

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elevating Cybersecurity for Smart grid Systems-A Container-Based Approach enhanced by Machine Learning 29

Elevating Cybersecurity for Smart Grid Systems-A Container-B...

引用

29th international conference on Automation and computing (ICAC)

作者： Abukeshek, Mays Barakat, Basel Ajayi, Bamidele Univ Sunderland Sch Comp Sci Sunderland England Univ Huddersfield Huddersfield W Yorkshire England

ISBN: (纸本)9798350360882;9798350360899

This paper presents a comprehensive implementation of a cybersecurity solution for smart grid network containers. The methodology utilises (i) Qualys API-based vulnerability scanning and reporting system for vulnerability identification, (ii) Docker deployment for security and isolation, (iii) advanced load balancing techniques for resource optimisation, and (iv) machine learning-powered anomaly detection for threat identification and vulnerability prioritisation. The implementation was used to create a dataset that continues the details of several simulated attacks, enabling effective training and evaluation of a robust machine-learning model. The paper provides a thorough description of the implemented system architecture, the Qualys API-based vulnerability scanning and reporting system, the data set creation process, simulated attacks in Docker implementation, the load balancing process, and the machine learning model used for vulnerability prioritisation. The experiments showed that the machine learning model performed exceptionally well across all conducted attacks i.e., Denial of Service, Remote-to-Local, User-to-Root, and Probes, achieving high scores in accuracy, precision, recall, and F1 scores.

关键词： Cybersecurity smart grid ML Attacks API Docker

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Table Structure Detection Based on PPLCNet Network 9

Table Structure Detection Based on PPLCNet Network

引用

9th ieee international conference on Progress in Informatics and computing, PIC 2024

作者： Wu, Linfeng Wang, Chenyu Wu, Yu Chen, Shunli Tan, Yiling Wang, Qiang State Grid Chongqing Electric Power Company Marketing Service Center Chongqing China Polytechnic Institute Zhejiang University Hangzhou China Chongqing Guanghui Power Supply Service Co. Ltd. Chongqing China College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798350363203

This paper presents table structure recognition models based on PPLCNet, MobileNetV3, and ResNet, evaluated on the PubTabNet dataset. By incorporating residual structures and the CBAM attention mechanism into PPLCNet, we achieve an accuracy of 73.53% and a TeDS of 94.57%. Ablation and comparative experiments validate the effectiveness of these enhancements. © 2024 ieee.

关键词： machine learning neural nets table recognition table structure detection

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Research on Power Line Loss Degree Prediction Model Based on Artificial Neural Network 3

Research on Power Line Loss Degree Prediction Model Based on...

引用

3rd ieee international conference on Distributed computing and electrical Circuits and electronics, ICDCeCe 2024

作者： Liu, Shengchun Zhang, Jie Zhang, Shikun Zhu, Junze Qinghai Dehong Electric Power Technology Qinghai Xining China State Grid Qinghai Electric Power Research Institute Qinghai Xining China State Grid Qinghai Electric Power Company Qinghai Xining China School Of Mathematical And Physical Science North China Electric Power University Beijing Changping China Hydropower Development Sichuan Xiangcheng China

ISBN: (纸本)9798350318609

In order to improve the prediction accuracy of power line loss degree, this paper analyzes the structure of the artificial neural network model and proposes the quality checking method of line loss data, which lays the foundation for the model to predict the line loss degree. Secondly, we use the equivalent resistance method to calculate the historical grid line loss rate, normalize the data in the input layer of the neural network, so as to improve the accuracy of line loss prediction, and complete the design of the prediction mode of the degree of power line loss based on artificial neural network. The results show that the accuracy, misjudgement rate and omission rate of the line loss prediction model in this paper are 99.32%, 0.45% and 0.23%, respectively, which are better than the other two line loss prediction models, and have strong application advantages. © 2024 ieee.

关键词： Forecasting

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energy Modeling Method for Containerized Applications on Physical Hosts 8

Energy Modeling Method for Containerized Applications on Phy...

引用

8th international conference on Cloud computing and Big Data Analytics (ICCCBDA)

作者： Ma, Zhoujun Lü, Mengjie Ma, Di Shi, Wenlong State Grid Jiangsu Elect Power Co Ltd Nanjing Power Supply Branch Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781665455336

The energy consumption problem in data centers is becoming increasingly severe, and energy consumption models can reveal the relationship between data center energy consumption and its corresponding factors, which is crucial for reducing energy consumption. Containerization is the current mainstream trend in data centers. Therefore, this paper proposes energy consumption models for physical hosts, containers, and containerized applications. First, we constructe a physical host energy consumption model based on polynomial regression with lasso. Then, by analyzing the resource utilization, we propose a simple and accurate method for modeling the container energy consumption. Finally, based on the container energy consumption model, we propose a method for constructing a parameter-based energy consumption models for containerized applications. The experimental results show that our modeling methods are valid. The advantages of our modeling method are that it can analyze data center energy consumption from different levels, such as physical hosts, containers, and applications, and it has the advantages of simplicity, high accuracy, ease of implementation.

关键词： power consumption modeling containerized applications cloud computing data center

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Optimal Voltage Regulation and energy efficiency in Photovoltaic grid system 1

Optimal Voltage Regulation and Energy Efficiency in Photovol...

引用

1st ieee international conference on Advances in Signal Processing, Power, Communication, and computing, ASPCC 2024

作者： Mishra, Debarchita Karan, D. Rahul, C Sanjay Abhsha, J. Benito Micheal Abuoi, Arok Biror Mandal, Sharmistha Vels Institute of Science Technology and Advanced Studies Department of Electrical and Electronics Engineering Chennai India Aliah University Electrical Engineering Department Kolkata India

ISBN: (纸本)9798350355093

Photovoltaic (PV) energy is the most vital renewable energy sources, and it has appeared as a feasible solution to the world's energy issue. This paper proposes a sophisticated PV integrated architecture including a coupled inductor based second order buck-boost converter, synergized with a particle swarm optimized proportional integral (PSO-PI) controller. With its ability to handle a broad range of input voltages, the converter's topology is designed to reduce energy losses and improve overall system efficiency. The objective is to guarantee excellent power quality and improve system reliability. To further improve performance, the system also includes a PI controller that is supported by PSO. The output is delivered to the grid via a single-phase voltage source inverter and grid synchronization is attained by the PI controller. The developed research is validated in MATLAB/Simulink and comparison with traditional approaches is conducted. The observed results show better converter efficiency of 92% with higher performance in terms of power quality enhancement. © 2024 ieee.

关键词： Buck converter

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evaluation of Complementary Characteristics of Multiple Types of Resources Based on AHP-entropy Weighting Approach 6

Evaluation of Complementary Characteristics of Multiple Type...

引用

6th ieee international conference on Power, Intelligent computing and Systems, ICPICS 2024

作者： Liu, Yifeng Sun, Yunchao Yan, Bing Wang, Wenhong Li, Yipu Zhang, Xin Ningxia Electric Power Dispatching Control Center State Grid Ningxia Electric Power Co. Ltd Yinchuan China Tsinghua University Beijing China

ISBN: (纸本)9798350374315

Aiming at the new working conditions of various new types of energy and high proportion of new energy sources connected to the grid, as well as the operation of guaranteed energy co-generation with thermal power as the main source, a system of evaluation indexes for the complementary evaluation of multiple types of resources is proposed as to how to judge the operation level of such multiple types of resources in multiple time scales. The article firstly analyzes the evaluation indexes of natural constrained energy sources and conventional controllable power sources, and puts forward the sub-system complementary evaluation indexes;then it analyzes the complementary relationship between the two types of energy sources from the system perspective, and puts forward the joint system complementary evaluation indexes. Finally, the proposed indexes are compared and analyzed through examples, and the complementary effects of the combined power system under different typical days are comprehensively judged through the AHP-entropy weight method, so as to realize the universalization analysis of the complementary characteristics of multiple types of resources. © 2024 ieee.

关键词： Windmill

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Abnormal Analysis System and Analysis of Residential electricity Consumption Based on electricity Data

Abnormal Analysis System and Analysis of Residential Electri...

引用

2024 international conference on Optimization computing and Wireless Communication, ICOCWC 2024

作者： Zhuang, Wende Zhang, Wei Yuan, Hao China Southern Power Grid Digital Power Grid Research Institute Co. Ltd Guangdong Guangzhou China

ISBN: (纸本)9798350383348

With the development of society and the progress of science and technology, electricity has become an indispensable resource in our daily life. However, in the process of power use, abnormal power consumption behavior often leads to energy waste and potential safety hazards. Therefore, anomaly analysis of residential electricity consumption data is of great significance for improving energy utilization efficiency, ensuring electricity safety and promoting energy conservation and emission reduction. This paper will discuss the data analysis of residents' abnormal electricity consumption. © 2024 ieee.

关键词： Analysis of abnormal electricity consumption Anomaly localization current overload theory electricity data calculation electricity for residents smart grids

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Leveraging the Compute Power of Two HPC Systems for Higher-Dimensional grid-Based Simulations with the Widely-Distributed Sparse grid Combination Technique 23

Leveraging the Compute Power of Two HPC Systems for Higher-D...

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2023 international conference for High Performance computing, Networking, Storage and Analysis, SC 2023

作者： Pollinger, Theresa Van Craen, Alexander Niethammer, Christoph Breyer, Marcel Pflüger, Dirk Institute for Parallel and Distributed Systems Universität Stuttgart Stuttgart Germany High Performance Computing Center Universität Stuttgart Stuttgart Germany

ISBN: (纸本)9798400701092

grid-based simulations of hot fusion plasmas are often severely limited by computational and memory resources;the grids live in four- to six-dimensional space and thus suffer the curse of dimensionality. However, high resolutions are required to fully capture the physics of interest. The sparse grid combination technique is a multi-scale method in which many anisotropically coarse resolved grids are used to approximate a fine-scale solution - -and it alleviates the curse of *** paper presents the core concepts of the widely-distributed combination technique, which allows us to use the compute power and memory of more than one HPC system for the same simulation. We apply the sparse grid combination technique to a six-dimensional advection problem serving as a proxy for plasma simulations. The full-grid solution approximated by the combination technique would contain ≈ 5 ZB if computed with conventional grid-based methods. even the combination technique simulation operates on ≈ 1 × 1011 double-precision degrees of freedom, or 988 GB, plus the supporting sparse grid data structures. We propose a new approach to divide the compute load between the two HPC systems, requiring only 76 GB to be exchanged. Based on this, we have realized the first synchronous combination technique simulation using two HPC systems, in our case the two German Tier-0 supercomputers HAWK and SuperMUC-NG. On two systems, the simulation can be computed at an average overhead of ≈ 35 % (108 s per combination step) for file I/O and transfer. The presented concepts apply to any pair of HPC systems if high-speed data transfer is possible. © 2023 ACM.

关键词： Supercomputers

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