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检索条件"任意字段=3rd IEEE International Conference on e-Science and Grid Computing"

共 7528 条记录，以下是231-240 订阅

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Improved DataX Data Synchronization Technique for Distribution grid Data Middleware Implementation 3

Improved DataX Data Synchronization Technique for Distributi...

引用

3rd ieee international conference on electrical engineering, Big Data and Algorithms, eeBDA 2024

作者： Yi, Zhang Hongkai, Zhao Yongyu, Wei Yulian, Xia Xiaoyan, Zhang State Grid Qinghai Information & Telecommunication Company Qinghai Xining810000 China State Grid Info-Telecom Great Power Science and Technology Co. Ltd. Fujian Fuzhou350003 China

ISBN: (纸本)9798350380989

Nowadays, the data processing efficiency of the distribution network is very low, which is not conducive to further monitoring of power grid data. It is necessary to adopt improved DataX data synchronization technology to further enhance the management ability and work efficiency of the distribution network data center. This article was based on technologies such as big data and cloud platforms to establish a unified data sharing mode, and utilized workflow technology and file online collaboration technology to establish an engineering management process model. In terms of data source collection, this article was based on the data center and utilized improved DataX data synchronization technology to ensure data security. Apart from key query data, big data is no longer stored locally. The data storage capacity of the distribution network data center was 80TB;the data storage capacity of Google BigQuery platform was 43TB, and the data storage capacity of Microsoft Azure platform was 32TB. This article helped to improve the value of electricity data usage. © 2024 ieee.

关键词： Data Center Data Storage Capacity Distribution Network Improved DataX Data Synchronization Technology Power grid engineering

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Single Phase grid Connected Nine Level Quadruple Boost Inverter with Current Control and Active Damping Capability 3

Single Phase Grid Connected Nine Level Quadruple Boost Inver...

引用

3rd Odisha international conference on electrical Power engineering, Communication and computing Technology, ODICON 2024

作者： Sarada, S. Challa, Ganesh Hemakesavulu, O. Damodar Reddy, M. Ravisankara Reddy, N. Yamuna, Pagidela Annamacharya University Department of EEE Rajampet India S. V. University Department of EEE Tirupati India Gprec Department of EEE Kurnool India Jntuace Department of EEE Pulivendula India

ISBN: (纸本)9798350354379

This study describes a 9-Level Switched-Capacitor Quadruple Boost Inverter (9LSCQBI) for the 1-Φgrid-tied system through L-C-L filter. This inverter can generate a quadruple voltage gain from a single dc source. Compared to prior switched-capacitor inverters, the absence of an H-bridge decreases voltage stress on switches. The recommended inverter can handle inductive loads and accomplish capacitor voltage balancing itself without the use of auxiliary circuits. The L-C-L filter is frequently employed in grid-tied inverters to decrease switching frequency harmonics. Yet, the filter's resonance produces stability concerns, necessitating effective damping. To avoid resonance, one approach is to connect a resistor to the filtering capacitor in series. However, this affects the inverter's efficiency. The proposed method employs current control and an Active Damping (AD) scheme entails incorporating a proportional regulation loop to monitor filter capacitor's current. In which, the grid current is controlled by a Proportional Resonant (PR) controller, whereas AD eliminates L-C-L resonance and preserves stability. Simulation outcomes demonstrate the proposed scheme's efficacy and robustness. © 2024 ieee.

关键词： Damping

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enhancing Stroke Risk Prediction with Stochastic Boosting and Adaptive grid-based Modeling 3

Enhancing Stroke Risk Prediction with Stochastic Boosting an...

引用

3rd international conference on electronics and Renewable Systems, ICeARS 2025

作者： Rohini, Talekar Praveen, P. Shaik, Mohammad Ali Ace Engineering College Dept of Cse Hyderabad India Sr University School of Cs&ai Warangal India

ISBN: (纸本)9798331509675

Stroke has emerged as a predominant cause of mortality and enduring impairment globally, with no effective therapy available. Deep learning methodologies can surpass current stroke risk prediction models;nevertheless, they depend on extensive, accurately labeled datasets. The study presents a new hybrid framework called Stochastic Boosting Filters with Adaptive grid-Based Projections (SBF-AGBP) to figure out the risk of having a stroke. The new method takes the best parts of stochastic boosting and adaptive grid-based projections. Stochastic boosting makes models more general by training them over and over on bootstrapped subsets. Adaptive grid-based projections divide the feature space into changing grids that make data representation efficient and simple to understand. SBF-AGBP utilizes domain-specific heuristics to priorities essential stroke risk indicators, including blood pressure, cholesterol levels, age, and lifestyle behaviors. The adaptive grid-based projections effectively capture non-linear correlations among features while preserving computing efficiency. The stochastic boosting filters also slowly make weak predictors better and lessen the impact of data imbalance, which happens a lot in medical datasets. The framework was assessed using ieee stroke dataset and shown enhanced accuracy, precision, and recall performance relative to conventional machine learning methods such as Random Forest, XGBoost, and Support Vector Machines. In addition, the proposed paradigm gives us understandable clues about the importance of several risk factors, which makes it more useful for making clinical decisions. SBF-AGBP provides a viable option for the early prediction of stroke risk, facilitating prompt treatments and alleviating global healthcare challenges. © 2025 ieee.

关键词： Support vector machines

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Image Compression Algorithms - Comparative Analysis 3

Image Compression Algorithms - Comparative Analysis

引用

3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Niharika Reddy, G. Namrutha, M. Akshaya, Namratha Bhaskaran, Sreebha Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508456

Due to the abundance of the new digital media data, the issue of image quality and volume of data requiring compression has become a significant factor of concern, especially in media storage and transmitting. This work affords a comparative analysis of different image compression techniques with focus on the compression ratio, quality preservation, and complexity. A new hybrid model of Predictive Coding, Run Length Coding and Quantum entropy Coding (QeC) is proposed and shown to exhibit negligible quality loss with substantial space saving. The experimental outcomes show that the proposed method reduces space 80 percent and works better than previous methods for areas requiring high speed and relative accuracy. These insights are timely, as practical computing-communication trade-offs are paramount in the new generation of social networks, medicine, and multimedia streaming. © 2025 ieee.

关键词： Image compression

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A non-invasive dynamic load identification algorithm for charging stations based on cloud edge collaboration 3

A non-invasive dynamic load identification algorithm for cha...

引用

3rd international conference on energy, Power and electrical Technology, ICePeT 2024

作者： Liu, Zhanxiong Guo, Tian Liu, Kaojiang Liu, Feng Zhao, Qihui State Grid Wu'an Power Supply Company Hebei Handan056300 China

ISBN: (纸本)9798350352658

In order to improve the accuracy of load dynamic identification, a cloud edge collaborative non-invasive charging station load dynamic identification algorithm is proposed. Based on the edge perception layer of the cloud computing platform, analyze and operate the data, decompose the original load signal, and obtain the load signal components. Using the minimum sum of component signal bandwidth as the constraint, calculate the partial load fluctuation coefficient and extract component load characteristics, Build a load dynamic identification model using genetic optimization algorithm to achieve dynamic identification of charging station loads. The experimental results show that applying the proposed method to identify the load of the charging station has a higher recognition accuracy and better recognition effect. © 2024 ieee.

关键词： charging station cloud edge collaboration load dynamic identification non invasive

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Capacitor health condition evaluation based on matrix condition number 3

Capacitor health condition evaluation based on matrix condit...

引用

3rd international conference on energy, Power and electrical Technology, ICePeT 2024

作者： Zhang, Zhenyu Cai, Zhiping Luo, Xiang Wang, Jueying Gao, Yuan Lin, Jianli State Grid Fujian Electrical Power Research Institution Fuzhou350007 China Electric Power Distribution Technology Fujian Provincial Enterprise Key Laboratory of High Reliable Fuzhou350007 China

ISBN: (纸本)9798350352658

Due to the reliability and low cost, power capacitors are widely used in power grid to ensure the stability of the power system and improve the power quality. In order to realize the online evaluation of capacitor health condition, this paper proposes a capacitor health evaluation algorithm based on matrix condition number. Based on the location and number of breakdown elements, the matrix describing capacitor breakdown condition is constructed. Then, the relationship between condition number and capacitor health condition is analyzed to build the algorithm to rank the threat degree of different element breakdown conditions, based on which the capacitor health condition is scored. The results of the theoretical analysis and simulation verify the effectiveness of the proposed algorithm. © 2024 ieee.

关键词： Capacitor bank

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Research on intelligent identification method of lightning arrester deterioration state based on GASF-CNN 3

Research on intelligent identification method of lightning a...

引用

3rd international conference on Smart grids and energy Systems, SGeS 2024

作者： He, Yong Guo, Sheng Tan, Haiao Yuan, Hanjie Lu, Lin Liao, Gaofeng Xie, Congzhen Zhaoqing Power Supply Bureau of Guangdong Power Grid Co Zhaoqing China Guangdong Power Grid Co Guangzhou China School of Electric Power South China University of Technology Guangzhou China

ISBN: (纸本)9798331539634

In recent years, monitoring and identifying the deterioration state of surge arresters has become essential for enhancing the reliability of electrical power systems. This paper introduces a novel method for recognizing the deterioration state of surge arresters, employing Gramian Angular Summation Fields (GASF) and Convolutional Neural Networks (CNN). Initially, GASF technology is utilized to transform the historical operational data of surge arresters into image format, capturing the texture and structural features that characterize the deterioration state. Subsequently, a specially designed CNN model processes these images to extract features and perform classification, thus identifying the deterioration states accurately. The results of this research offer a new approach for the online recognition of deterioration states in critical protective devices on transmission lines, providing significant insights for the safe and reliable operation of power systems. © 2024 ieee.

关键词： Convolutional neural networks

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Intelligent Operation and Inspection Software Based on edge computing Concept and Artificial Intelligence Technology 3

Intelligent Operation and Inspection Software Based on Edge ...

引用

3rd international conference on energy engineering and Power Systems, eePS 2023

作者： Ren, Jiaxuan Wang, Shaorong Yang, Youhang Zhang, Yanyan Wei, Zheng Zheng, Chao Li, Jingsong Chen, Yunan Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China Dongguan Power Supply Bureau of Guangdong Power Grid Co. Ltd Dongguan China Wuhan Qiyi Electric Co. Ltd Wuhan China Yunnan Power Dispatch Control Center Kunming China

ISBN: (纸本)9798350313857

A new intelligent operation and inspection software based on the concept of edge computing and artificial intelligence technology is proposed for the physical and operational architecture of substation electrical equipment intelligent inspection, and a human-computer interaction interface is designed for the convenience of operation and maintenance personnel, which effectively avoids the problems of poor real-time and monitoring blind areas of off-line inspection and conventional energized inspection, and solves the defects of cloud computing and manual inspection. The key technologies included in the realization of intelligent operation and inspection software functions are: the design of physical and operational architecture, and the analysis of structured and unstructured charged inspection data. The intelligent operation and inspection software is stable and reliable, which can greatly improve the efficiency of inspection and the intelligence level of the substation. © 2023 ieee.

关键词： edge computing

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Carbon emission Management of Industrial Parks Based on Carbon Price and electricity Consumption Prediction 3

Carbon Emission Management of Industrial Parks Based on Carb...

引用

3rd international conference on Smart grids and energy Systems, SGeS 2024

作者： Li, Zhonghao Fang, Lei Yang, Zijie Zhang, Chenggong Wang, Jinjian He, Bin Guo, Bingtao State Grid Corporation of China State Grid Shanghai Urban Electric Power Supply Company Shanghai China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798331539634

Driven by carbon neutrality ambitions, effective carbon emission management has become paramount for industrial park sustainability. This study proposes an industrial park carbon emission management model incorporating carbon price and electricity consumption predictions. By leveraging historical data and machine learning algorithms, separate prediction models for carbon price and electricity consumption are developed. These predictions, combined with park-specific carbon emission intensity data, enable forecasting future carbon emissions. The model further incorporates government carbon policies and park emission reduction targets to formulate data-driven management strategies. Results demonstrate the model's effectiveness in predicting carbon emission trends and providing scientific emission reduction recommendations, facilitating the achievement of carbon neutrality goals within industrial parks. © 2024 ieee.

关键词： Carbon capture and utilization

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An Unknown Risk Analysis and evaluation Method for Distribution edge computing Networks 3

An Unknown Risk Analysis and Evaluation Method for Distribut...

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3rd international conference on Robotics, Automation and Intelligent Control, ICRAIC 2023

作者： Ni, Hua Lin, Yifu Chen, Xue Shanghai Academy of Artificial Intelligence Industrial Technology Shanghai China State Grid Fujian Electric Power Co. Ltd. Fuzhou China State Grid Fujian Economic Research Institute Fuzhou China

ISBN: (纸本)9798350360813

Distribution edge computing networks require robust risk analysis and evaluation, especially for unknown attacks. This work addresses unknown risk analysis using the Bayesian hazard graph, proposing an algorithm tailored to the context of edge computing networks. The algorithm calculates unknown risks using a noise model and incorporates the CVSS scoring standard to create a conditional probability table. It continuously updates probability distributions with known information and real-time feedback, making it well-suited for distribution edge computing networks. © 2023 ieee.

关键词： Risk analysis

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