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

共 17242 条记录，以下是221-230 订阅

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Optimal Power Flow Based on Area Partitioning Method for Power grids 14

Optimal Power Flow Based on Area Partitioning Method for Pow...

引用

14th international conference on Information science and Technology, ICIST 2024

作者： Ma, Zhiqiang Liang, Fei Yang, Qi Chen, Bing Zhou, Mei Na, Yu Metrology Centre Marketing Service Center State Grid Ningxia Electric Power Co. Yinchuan750010 China

ISBN: (纸本)9798350353334

The power system is gradually orienting to large-scale distributed computing, and the trend of area interconnection is becoming more and more obvious. It is still a classic prob-lem to calculate power flow by using distributed optimization. Compared with traditional centralized power flow calculation, it has obvious advantages with fast computing speed and less information between areas. In this paper, we define the boundary voltage coupling equation with auxiliary variables, to solve the non-convex subproblem in the iterative process of ADMM, and match the optimal area partitioning for ADMM by proposing the optimal spectral clustering (OSC) method. Specifically, the OSC scheme takes the Jacobian matrix, admittance matrix, and voltage pivot vector as the the joint adjacency matrix to measure the similarity of spectral clustering algorithm into consideration, which is obviously better than the traditional spectral clustering method considering admittance matrix only. Combining with ADMM algorithm, ieee-118 bus system is used as a test example to perform the distributed calculation after area partitioning, the experimental results verify the good performance of proposed spectral clustering method in distributed power grid. © 2024 ieee.

关键词： Load flow optimization

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Threat Hunting Architecture for electric Internet of Things: Redundancy, Diversity, Dynamism and Machine Learning 9

Threat Hunting Architecture for Electric Internet of Things:...

引用

9th international conference on Power and Renewable energy

作者： Zhan, Congcong Xie, Shanyi Kang, Yilin Li, Yan Nong, Caiyan Hu, Xianjun Guangdong Power Grid Co Ltd Elect Power Res Inst Guangzhou Peoples R China Guangdong Power Grid Co Ltd Elect Power Res Inst Guangdong Key Lab Elect Power Equipment Reliabil Guangzhou Peoples R China Purple Mt Labs Nanjing Peoples R China

ISBN: (纸本)9798350377477;9798350377460

The electric Internet of Things (e-IoT) system, as a critical information infrastructure, has become a primary target for cyber attackers, resulting in significant consequences upon compromise. Consequently, threat hunting within the e-IoT system plays a crucial role in detecting cyber threats and preventing cyber attacks. In recent decades, machine learning (ML)-based threat hunting methods have proliferated, aiming to achieve better performance and enhance security. These methods focus on analyzing the features of e-IoT equipment and predicting whether they are under attack. However, they often fall short when dealing with attacks that manipulate the output of equipment and compromise other connected devices without altering their configuration information or internal data. This paper first classifies cyber attacks into two categories: the destructive attack and the latent attack, illustrating that traditional ML-based threat hunting methods are primarily effective against the former. Subsequently, we propose the Redundancy Diversity Dynamism Machine Learning (RDD&ML) threat hunting architecture for the e-IoT system and prove that the RDD&ML architecture enhances the system's reliability. Moreover, the proposed architecture exhibits superiority over traditional ML-based methods when confronting unknown threats or attacks, as it does not rely on prior knowledge of the adversary. experimental results on real dataset demonstrate that the RDD&ML architecture enhances the threat hunting performance of the e-IoT system.

关键词： electric Internet of Things threat hunting cyber security machine learning MITRe ATT&CK

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Research on UAV Inspection System Based on edge Intelligent computing AI 6

Research on UAV Inspection System Based on Edge Intelligent ...

引用

2023 ieee 6th international conference on Information Systems and Computer Aided education, ICISCAe 2023

作者： Li, Cong Zhao, Wenyi Zhao, Liuxue Ju, Li Zhang, Hongyu State Grid Beijing Economics Research Institute Beijing100055 China State Grid Beijing Electric Power Company Beijing100031 China

ISBN: (纸本)9798350313444

In view of the unsatisfactory photo quality obtained by UAV during autonomous inspection, this project studies the specific factors that affect the image acquisition quality, and carries out the feasibility study of object tracking and defect intelligent identification based on edge computing. This paper mainly solves the problems of positioning error, environmental interference and defect identification after imaging. At the same time, the intelligent image recognition algorithm is designed and optimized based on the computing power of the airborne end. This paper calculates the mapping relationship between the coordinates of two-dimensional imaging points and their spatial three-dimensional coordinates based on the principle of optical imaging. Then the mathematical model of measuring target orientation is established based on computer vision theory. The R-CNN system algorithm based on deep learning can be used to measure the orientation information of the target's relative vision with high precision. © 2023 ieee.

关键词： AI UAV defect identification edge intelligent computing Inspection photo quality

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Access Control in e Health Care Records employing Mobile Cloud computing Model and Big Data Analytics 1

Access Control in E Health Care Records Employing Mobile Clo...

引用

1st ieee international conference on computing and Data science, ICCDS 2024

作者： Saisree, Yerramaddu Lalitha, Nomula Reddy Felix, A. Yovan Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350365337

Cloud service providers are currently storing large volumes of data on cloud. This requires verification mechanisms often employing cryptography by third party auditors. However, ensuring the security and privacy of e-health systems poses a significant challenge. To overcome this challenge, researchers are focusing on building a robust public auditing system. This privacy preserving protocol focuses on privacy preservation allowing third party auditors to evaluate out sourced data without accessing the content. The key to this approach is implementation of batch auditing that enables simultaneous tasks to be processed by trusted third party auditors. The proposed system provides scalable, flexible and efficient public auditing capabilities enhancing the levels of security of e-healthcare systems. The external auditors promote trust and privacy in cloud-based healthcare systems. The integration of mobile devices and cloud computing provides a vast range of opportunities for healthcare management. This innovation provides a way to meet the evolving changes of cloud-based healthcare data management. © 2024 ieee.

关键词： Mobile cloud computing

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Ontology-Based Optimization Method for Multi-Source Heterogeneous Data Organization in Large Power grid Planning and Operation Platforms 3

Ontology-Based Optimization Method for Multi-Source Heteroge...

引用

3rd international conference on energy and electrical Power Systems (ICeePS)

作者： Tang, Yingqi Zhao, Ligang Su, Yinsheng Zhou, Baorong Xu, Yuan Huang, Guanbiao Hu, Jiaming Li, Kaihang CSG Elect Power Res Inst State Key Lab HVDC Technol Guangzhou Peoples R China CSG Power Dispatching & Control Ctr Guangzhou Peoples R China South China Univ Technol Sch Elect Power Engn Guangzhou Peoples R China

ISBN: (纸本)9798350375145;9798350375138

The construction of a large power grid planning and operation platform requires the integration and organization of multi-source heterogeneous data. However, the various types of power grid business have differing levels of importance and high demands for timely response, which current data organization methods struggle to meet. This paper proposes an ontology-based optimization method for multi-source heterogeneous data organization in large power grid planning and operation platforms. A mathematical optimization model is constructed, taking into account both business retrieval efficiency and data redundancy. Additionally, the genetic algorithm is improved based on the specific characteristics of this optimization problem. The method proposed in this paper is then applied to integrate data from multiple power software applications. experimental results show that this method effectively balances data retrieval efficiency and storage space utilization, achieving automated organization optimization of multi-source heterogeneous data for power grid planning and operation.

关键词： multi-source heterogeneous data organization power grid planning and operation optimization ontology improve genetic algorithm

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A Techno-economic Analysis of an ieee 39 Sustainable grid Bus for DSM on Load Flexibility Options

A Techno-Economic Analysis of an IEEE 39 Sustainable Grid Bu...

引用

2024 international conference on Innovations in science, engineering and Technology, ICISeT 2024

作者： Salam, Syed Munimus Mohammad, Nur Chowdhury, Deepak Kumar Haque, enamul CUET Department of EEE Chattogram Bangladesh Institute of Energy Technology CUET Chattogram Bangladesh

ISBN: (纸本)9798350355499

To estimate the flexibility and benefit of the system integration of demand side management (DSM), this paper evaluates the techno-economic aspects of DSM in a sustainable 39 -bus grid with renewable energy sources (ReS) and load flexibility options (e.g., time flexible, temperature flexible, and light flexible). This 39-bus impedances have been adopted from southern power grid of Bangladesh and ieee 39 bus system. By including environmental considerations, integration of ReS in the system a sustainable grid consideration implemented. The findings demonstrate that load shifting and reduction by DSM may take the place of load shedding and can also balance transient fluctuations. Analysis of DSM's effects on other flexibility choices reveals that, while baseload power plants see an increase in both, peak load plants get a decrease in utilization and contribution margin. DSM causes a countrywide increase in power consumption by reducing imports and exports. © 2024 ieee.

关键词： Demand side management

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Reinforcement Learning edge computing Model for Integrated energy Systems 5

Reinforcement Learning Edge Computing Model for Integrated E...

引用

5th international conference on Clean energy and electric Power engineering, ICCePe 2024

作者： Yang, Yuqiang Li, Lei Zhao, Qiming Lu, Pengfei State Grid Zhejiang Electric Power Company LTD. Marketing Department Hangzhou China

ISBN: (纸本)9798350390315

In the architecture of edge computing, edge servers have a faster data transmission rate and lower energy consumption than terminal devices. In the scenario of the integrated energy system, numerous edge servers and computing tasks will lead to an expansion of the problem-solving scale, greatly increasing the difficulty of workflow scheduling. In addition, due to the fluctuation in the performance of the servers themselves, the traditional method of treating the performance data of the servers as fixed values cannot guarantee the final reliability of the scheduling results. To ensure the reliability of the scheduling algorithm, we propose a server performance model based on probability distribution (PDSPM), which can utilize historical performance data to better characterize the fluctuations in server performance. Benefiting from the excellent performance of deep reinforcement learning in large-scale decision-making problems, this paper proposes a new workflow scheduling algorithm based on Deep-Q-network (DQN) and studies feasible improvement schemes. By combining PDSPM, this algorithm can ensure that the scheduling results with the highest probability of reliability are obtained under the fluctuation of server performance. © 2024 ieee.

关键词： Scheduling algorithms

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Code-Aided Carrier Synchronization with Adjustable Operating Ranges for Satellite Communications 19

Code-Aided Carrier Synchronization with Adjustable Operating...

引用

19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Chen, Taiyi Zhan, Yafeng Xie, Haoran Xiao, Xiaolong Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol BNRis Beijing Peoples R China Tsinghua Univ Dept Elect Engn Beijing Peoples R China State Grid Jiangsu Elect Power Co Ltd Res Inst Nanjing Peoples R China

ISBN: (纸本)9798350333398

Due to limited link resources and increasing demand for data transmission, receivers in satellite communications are required to achieve carrier synchronization, demodulation, and decoding operations at low signal-to-noise ratio (SNR) conditions, thus making full use of the link budget. In this context, code-aided (CA) carrier synchronization is a promising solution, synchronizing low-SNR signals without additional pilot overhead. However, traditional CA carrier synchronization suffers from a narrow operating range and, in practice, performs poorly in tracking dynamic signals with large Doppler frequency offsets. To solve such a problem, we presents a low-complexity algorithm to improve the operating range of CA carrier synchronization. This algorithm tolerates large carrier offsets through coarse correction based on a confidence metric function (CMF). Additionally, a candidate list mechanism is introduced to reduce the computational overhead. The operating range of the algorithm can be adjusted by varying its parameters to sustain carrier recovery under different dynamic scenarios. Simulations verify the effectiveness of the proposed algorithm.

关键词： Code-aided synchronization carrier recovery LDPC codes operating range low SNR

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Research and application of power blockchain data sharing technology based on privacy computing 3

Research and application of power blockchain data sharing te...

引用

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

作者： Shi, Ying Wang, Lixing Ao, Jin Song, Jie Li, Qian Zhang, Xuesen State Grid Jilin Electric Power Company Co. Ltd Jilin China Co. Ltd. Beijing China

ISBN: (纸本)9798350352658

A new type of power system gathers large-scale energy and related data. This paper builds a blockchain power data trusted sharing platform prototype system with independent intellectual property rights to provide a trusted data basis for data sharing, data security, data privacy protection and other functions, explore the potential value of power data, and standardize and standardize the power data market. Based on the key technology of blockchain data management, it realizes the trusted sharing of data side chain support business, ensures the safe interaction of supply chain data, further releases the potential energy of service chain industry, optimizes the industrial environment, and promotes the value-added realization of power data assets. © 2024 ieee.

关键词： Blockchain Data sharing Power service data Privacy computing

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Incremental Multivariate State estimation Technique-Based Fault estimation Method for Motor-driven High-Voltage Circuit Breakers 10

Incremental Multivariate State Estimation Technique-Based Fa...

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10th ieee international conference on Cyber Security and Cloud computing and 9th ieee international conference on edge computing and Scalable Cloud, CSCloud-edgeCom 2023

作者： Li, Wei Fan, Yongwei Xiao, Xi Xie, Fang Zeng, Ping Liu, Zhigang Fu, Yanwei Long, Jing Wang, Xiao Hunan University College of Computer Science and Electronic Engineering Changsha China Tsinghua University Department of Electrical Engineering Beijing China State Grid Jian Power Supply Company Ji'an China Pinggao Group Co. Ltd. Pingdingshan China Hunan Normal University Information Science and Engineering Changsha China

ISBN: (纸本)9798350312461

The fault estimation of motor-driven high-voltage circuit breakers, which is important for improving a system's security, operation, and maintenance, has attracted extensive research interest. Currently, most fault estimations schemes of motor-driven high-voltage circuit breakers worldwide detect a single variable, where the estimation accuracy is significantly affected by parameter selection. Besides, a motor-driven high-voltage circuit breaker's fault may result from multiple parameters. Therefore, this paper develops a comprehensive multiparameter estimation for the motor-driven high-voltage circuit breakers and utilizes the evaluation results to support the optimal operation of the intelligent grid. Specifically, the voltage, current, speed, and position parameters are used to build the fault estimation model of the motor-driven high-voltage circuit breakers to achieve the memory matrix's real-time dynamic update and de-redundancy. The current operating state is then judged for abnormalities by comparing the defined threshold and residual between the estimated model output operation state and the equipment's current actual operation state. Finally, the effectiveness of the proposed method is verified by numerical simulations. © 2023 ieee.

关键词： State estimation

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