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Research on the Deployment of MEC Edge computing Platform Based on 5G Network in Power System 7

Research on the Deployment of MEC Edge Computing Platform Ba...

引用

7th international conference on Computer and Information Processing Technology, ISCIPT 2022

作者： Wang, Long Dong, Wu Zhang, Guoyi Wang, Tao Liu, Xu China Southern Power Grid Digital Power Grid Research Institute Co. Ltd 510670 China Guizhou Power Grid Power Dispatching and Control Center 550002 China CSG Power Dispatching and Control Center 510670 China

With the rapid development of cloud computing, Internet of Things, AI and other technologies, edge computing technology has also developed rapidly. To be on the safe side, especially those mid-sized, larger utilities are more inclined to use edge computing. To this end, this paper conducts an in-depth discussion on the application of the MEC edge computing platform on 5G networks. A distributed power architecture based on distributed computing is proposed, and the distributed application of MEC is studied from two aspects: distributed application model and distributed service carrier. Experiments on the effect of deploying the live network pilot show that: the power system delay of the platform in the comparison case, the power system delay of the local forwarding platform is shortened by 50%, the deployment effect is faster, the delay is shorter, and the efficiency is higher. © 2022 Copyright for this paper by its authors.

关键词： 5G mobile communication systems

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Trust Evaluation Model in New Power System Edge computing

Trust Evaluation Model in New Power System Edge Computing

引用

2023 international conference on Optoelectronic Information and Functional Materials, OIFM 2023

作者： Lu, Junfeng Wang, Chan Li, Jing Li, Xiaomeng Zhao, Jinmeng Wang, Xiaolong State Grid Information and Telecommunication Branch Company Beijing100761 China Hebei Baoding071000 China

ISBN: (纸本)9781510668119

The existing sensor network trust evaluation model cannot be directly applied to the new power system distributed home photovoltaic collection scenario, which is difficult to meet the requirements of strong computing power and high defense power of the new power system. Therefore, a distributed dynamic trust evaluation model based on multi-index detection is proposed. Firstly, the communication trust evaluation based on Bayes is carried out according to the historical interaction of terminal acquisition nodes. Then, the current collected data is evaluated by perceptual trust based on its historical data support degree and regional trust based on probability density. Finally, the entropy weight method is used to dynamically decentralize the values of each trust module. The node activeness and double reward and punishment mechanism are introduced to calculate the comprehensive trust value and realize the dynamic update. The experimental results show that the four levels of trust evaluation model suitable for the new power system environment and can be used to detect the distributed in a short period of time household photovoltaic power generation collection in view of the signal in the scene, such as equipment aging and malicious tampering with cases of abnormal nodes, dynamic, accuracy of node trust evaluation, and according to the specific details provide a reference for analysis of exception type. © 2023 SPIE.

关键词： Sensor networks

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Dynamic Data Replication for Short Time-to-Completion in a Data grid 23rd

Dynamic Data Replication for Short Time-to-Completion in a D...

引用

23rd international conference on Computational Science, ICCS 2023

作者： Vamosi, Ralf Schikuta, Erich Faculty of Computer Science University of Vienna Vienna Austria

ISBN: (纸本)9783031360237

Science collaborations use computer grids to run expensive computational tasks on large data sets. Tasks as jobs across the network demand data and thereby workload management and data allocation to maintain the computational workflow. Data allocation includes data placement with different replication factors (multiplicity) of data. The proposed data replication & allocation model can place multi tudes of subsets of a data population in a distributed system, such as a computer cluster or computer grid. A stochastic simulation with a data and computing example from the ATLAS Physics Collaboration shows its potential usability in one of the largest computing grids. This paper showcases data allocation with different replica factors and various numbers of subsets to improve the overall situation in a computer network. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Data centers

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Hardware-in-the-Loop Evaluation of grid-Edge DER Chip Integration Into Next-Generation Smart Meters 14

Hardware-in-the-Loop Evaluation of Grid-Edge DER Chip Integr...

引用

14th IEEE international conference on Communications, Control, and computing Technologies for Smart grids, SmartgridComm 2023

作者： Comden, Joshua Wang, Jing Ganguly, Subhankar Forsyth, Steven Gomez, Reynaldo Bernstein, Andrey National Renewable Energy Laboratory GoldenCO United States Nvidia Corporation Santa ClaraCA United States

ISBN: (纸本)9781665455541

To facilitate the implementation of distributed energy resource management systems (DERMS), we propose to insert a grid-edge distributed energy resource (DER) chip hosting a DERMS algorithm into the next generation of smart meters. This will create a pathway for the wide adoption of DERMS technology because many utilities plan to invest in advanced metering infrastructure in the near future. This will also bridge the gap between an electrical power utility and DERs behind the meter. The DER chip is designed to follow power direction signals from the DERMS coordinator while balancing its local objectives. We tested the chip using a controller- and power-hardware-in-the-loop evaluation under three scenarios that a DERMS could face in the real world. The DER chip was capable of and effective at directing four heterogeneous DERs to respond to a DERMS coordinator for grid services (e.g., voltage regulation and a virtual power plant). © 2023 IEEE.

关键词： Energy resources

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Research on Characteristics of Electricity Theft Behavior and Risk Early Warning Technology Based on Big Data Information of the Internet of Things

Research on Characteristics of Electricity Theft Behavior an...

引用

IEEE international conference on Electrical Engineering, Big Data and Algorithms (EEBDA)

作者： Huang, Rongguo Lu, Chunguang Hu, Shuhong Tang, Di Pan, Boliang State Grid Zhejiang Elect Power Co Ltd Mkt Serv Ctr Hangzhou Peoples R China Zhejiang Huayun Informat Technol Co Ltd Hangzhou Peoples R China

ISBN: (纸本)9781665416061

Based on the results of online loss calculations, we comprehensively utilize the existing massive data of power grid companies, and conduct in-depth mining of abnormal line loss rate lines or stations by using big data technologies such as Hadoop offline distributed computing and Spark memory computing to identify possible occurrences. Electricity stealing, providing electricity theft warning and data support services for power supply companies' anti-electricity theft inspections. The data collected on the spot proves the effectiveness of the structured anti-theft model, and provides an effective method for solving the problem of monitoring the behavior of electricity theft under the condition of big data.

关键词： electricity consumption information collection system big data anti-stealing structured model

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A Data Security Protection Method for Deep Neural Network Model Based on Mobility and Sharing 18th

A Data Security Protection Method for Deep Neural Network Mo...

引用

18th international conference on Green, Pervasive, and Cloud computing, GPC 2023

作者： Zhao, Xinjian Li, Qianmu Wang, Qi Chen, Shi Li, Tengfei Li, Nianzhe State Grid Jiangsu Information and Telecommunication Company Jiangsu Nanjing210024 China School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing210094 China State Grid Smart Grid Research Institute Co. Ltd. Jiangsu Nanjing210003 China State Grid Key Laboratory of Information and Network Security Jiangsu Nanjing210003 China

ISBN: (纸本)9789819998920

With the rapid development of digital economy, numerous business scenarios, such as smart grid, energy network, intelligent transportation, etc., require the design and distribution of deep neural network (DNN) models, which typically use large amounts of data and computing resources for training. As a result, DNN models are now considered important assets, but at great risk of being stolen and distributed illegally. In response to the new risks and challenges brought by frequent data flow and sharing, watermarks have been introduced to protect the ownership of DNN models. Watermarks can be extracted in a relatively simple manner to declare ownership of a model. However, watermarks are vulnerable to attacks. In this work, we propose a novel label-based black-box watermark model protection algorithm. Inspired by new labels, we design a method to embed watermarks by adding new labels in the model, and to prevent watermarks from being forged, we use encryption algorithms to generate key samples. We conduct experiments on the VGG19 model using the CIFAR-10 dataset. Experimental results show that the method is robust to fine-tuning attacks, pruning attacks. Furthermore, our method does not affect the performance of deep neural network models. This method helps to solve scenarios such as "internal data circulation, external data sharing and multi-party data collaboration". © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Neural network models

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Research on Commercial Operation System of Power Supply Enterprises Based on Shareable Basic Resources 2

Research on Commercial Operation System of Power Supply Ente...

引用

2nd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Peng, Zhirong Cheng, Yang Chen, Jinhong China Southern Power Grid Co. Ltd. Jiangmen Branch Jiangmen529000 China

ISBN: (纸本)9798350347456

Enterprises want to obtain core competitiveness in the increasingly fierce market competition, to obtain greater benefits, improve the level of enterprise information will be one of the important means. At present, enterprises have built a large number of application systems, which play an important role in their own business areas, but they often cannot work well with each other, independent of each other, thus forming many information islands in the enterprise. In order to solve the problems of "difficult reuse"and "difficult integration"in the informatization of electric power enterprises, this paper suggests that the Service Oriented Architecture (SOA) should be applied to the operation support system of electric power enterprises to realize function reuse and data sharing. This paper presents a model of power supply enterprise operation support system based on SOA architecture, which includes an information integration platform, an enterprise portal and a series of business application systems. The information integration platform is used to realize enterprise application integration. The platform uses the enterprise service Bus to act as the intermediary between service requester and service provider, avoiding point-to-point integration. The business functions provided by the business application system are realized through the best implementation technology of SOA - Web services, and these Web services will be published on the information integration platform to achieve functional reuse. Data and services on the information integration platform can be displayed through the enterprise portal. Unlike traditional tightly coupled enterprise portals, soA-BASED enterprise portals are loosely coupled, and the functionality of their user interfaces can be reused, combined, and tailored. The new data scheduling algorithm in smart grid proposed in this paper can ensure that the data scheduling priority sensitive to time delay is superior to the data insensitive to time

关键词： Web services

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A Data Privacy Protection Scheme Integrating Federal Learning and Secret Sharing 5

A Data Privacy Protection Scheme Integrating Federal Learnin...

引用

5th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2023

作者： Wang, Hao Zhang, Yiying Cheng, Yang Li, Qiang Zhao, Jia Li, Wenjing Tianjin University of Science and Technology Tianjin China State Grid Jiangsu Electric Power Company Taizhou Power Supply Company Taizhou China State Grid Information and Telecommunication Group Co. Ltd Beijing China Nanchang Institute of Technology Nanchang China

ISBN: (纸本)9798350333442

The explosive growth of power data in the process of new power system business operation has high utilization value, how to maximize the value of data mining at the same time, to ensure its privacy in the collection, transmission, aggregation and analysis is a critical issue that needs to be addressed. This paper proposes a data privacy protection scheme (FL-SS) based on federal learning and secret sharing. Firstly, based on the federal learning framework, the information of gateway local training model parameters is distributed and reconfigured to ensure the security of the model updating process while preventing the betrayal of internal gateways;meanwhile, a lightweight communication key negotiation mechanism is designed to protect the transmission process of model parameters and data. The comparison experiments show that FL-SS has better performance in terms of accuracy and energy consumption compared with other similar schemes. © 2023 IEEE.

关键词： Data mining

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Research on Abnormal Work Order Closed-Loop Management System for Power Acquisition Operation and Maintenance 2

Research on Abnormal Work Order Closed-Loop Management Syste...

引用

2nd international conference on Data Analytics, computing and Artificial Intelligence, ICDACAI 2023

作者： Xiaoqin, Ma Xiaohe, Guo Hongjiao, Luo Yufeng, Xue Haiying, Ma State Grid Qinghai Information Telecommunication Company Xining China State Grid Qinghai Electric Economic Research Institute Xining China

ISBN: (纸本)9798350339765

This paper introduces geographic information system display technology, distributed big data processing architecture, measuring equipment anomaly self-learning analysis technology and other advanced technologies to achieve the graphical panoramic operation and maintenance control and metering equipment online monitoring and intelligent diagnosis. At the same time, this paper constructs the corresponding software application system. Then, an anomaly diagnosis and processing method based on power acquisition operation and maintenance system is proposed. The method firstly obtains the diagnosis rules through association mining, and then converts the monitored data into event elements and performs rule matching to obtain the diagnosis results. Finally, confirm and feedback the diagnosis result through on-site troubleshooting. The practical application results show that the above system can effectively reduce the burden of operation and maintenance personnel, shorten the time of fault handling and enrich the means of marketing audit. The system can improve the efficiency of collection operation and maintenance and the service level of power marketing and reduce the economic loss of enterprises. © 2023 IEEE.

关键词： Data acquisition

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2023 IEEE international conference on Power Electronics, Smart grid, and Renewable Energy: Power Electronics, Smart grid, and Renewable Energy for Sustainable Development, PESGRE 2023

2023 IEEE International Conference on Power Electronics, Sma...

引用

2023 IEEE international conference on Power Electronics, Smart grid, and Renewable Energy, PESGRE 2023

ISBN: (纸本)9798350310573

The proceedings contain 245 papers. The topics discussed include: demand response supported energy management framework for residential users;torque ripple analysis of five-phase induction motor drive with pentacle connected stator windings;an innovative islanding detection scheme in a distributed generation using phase angle between negative sequence superimposed components of voltage and current;SPARK technology for condition monitoring of solar power plants;power quality improvement with hybrid shunt active power filter;LLC resonant converter based led driver fed by single phase high power factor boost converter;residential demand response using Q-learning with pursuit algorithm for action selection;communication independent islanding detection technique utilizing wavelet packet transform;effective power management and stability analysis of MIMO EV charging station;and force and motion analysis of blade-less wind energy harvesters.

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