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12th international conference on Cyber-Enabled distributed computing and Knowledge Discovery (CyberC)

作者： Ding, Junfeng Zong, Haonan Zhou, Jian Wu, Deyong Chen, Xuan Wang, Lei State Grid Jiangsu Elect Power Co Ltd Nanjing 211102 Peoples R China Nanjing Univ Posts & Telecommun Sch Comp Sci Nanjing 210023 Peoples R China State Grid Jiangsu Elect Power Co Ltd Extra High Voltage Branch Co Nanjing 211102 Peoples R China

ISBN: (纸本)9798350331547

Reverse modeling is a kind of technology that transforms natural scenes into three-dimensional models. The models are generated manually by referring to the point cloud obtained by a laser scanner, which is time-consuming, laborious, and complicated. To address this problem, we propose an automatic modeling method for the point cloud data of substations. First, an algorithm is designed to automatically generate a component model library by referring to the standard structure of the substation equipment. Then, we improve the Euclidean clustering to segment disconnected point cloud data. Finally, corresponding points are found according to the SHOT feature descriptor, and each component is identified with Hough voting. After the location information for each element in the scene is obtained, the models can be transferred to the scene to replace the corresponding part in the point cloud, thus completing the process of automatic modeling. The experiment compares the results of improved Euclidean clustering and traditional Euclidean clustering. The clustering method in this paper has a significant improvement in execution efficiency. In addition, we also give the final modeling result of the method in this paper. Compared with the Delaunay triangulation and Poisson surface reconstruction methods, the model built by this method is more complete.

关键词： automatic modeling Euclidean clustering SHOT Hough voting

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distributed fault recovery strategy and example analysis of large power grid based on 5G technology 4

Distributed fault recovery strategy and example analysis of ...

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4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

作者： Zhongbin, Li Zhengkun, Mo Jiaming, Liu Xi, Han Wenqin, Chen Digital Grid Research Institute China Southern Power Grid Guangdong Province Guangzhou City510700 China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

a distributed fault recovery method for large-scale power grid with multiple power sources and multiple connections is proposed. This method fully considers the characteristics of 5G communication, the recovery process is simple, the number of information transmission is less, and the power supply of important load nodes can be restored first. For the proposed scheme, numerical examples are analyzed in different complex power grid scenarios, the urban power grid system simulation model is built to verify the feasibility of the recovery strategy, and the expected results are analyzed. According to the proposed distributed fault recovery method based on 5G communication, combined with the specific urban power grid system, the modular software design of the distributed fault recovery scheme is carried out. © 2022 IEEE.

关键词： Software design

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Grouped federated learning for time-sensitive tasks in industrial IoTs

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2024年第2期17卷 819-833页

作者： Hao, Jiangshan Zhang, Linghao Zhao, Yanchao Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Jiangjun Ave Nanjing 211106 Jiangsu Peoples R China State Grid Sichuan Elect Power Res Inst Power Internet Things Key Lab Jinhui West Second St Chengdu 610094 Sichuan Peoples R China

The Industrial Internet of Things (IoT) is a crucial part of Industry 4.0 and constantly calls for intelligence to improve productivity. Meanwhile, the federated learning scheme has recently been proposed to provide both distributed learning ability and inherent privacy protection functions. Despite its original advantages, the unique features of industrial IoT posed several challenges to federated learning regarding efficiency and scalability. Due to the heterogeneity of data under IoT and the large difference in computing efficiency of each device, the training time of federated learning will be affected by stragglers. To this end, an effective device selection mechanism is urgently needed to improve the training efficiency of global model. Additionally, the communication coordination problem among various devices should be considered to accelerate global convergence. To solve the abovementioned problems, we proposed an Upper Confidence Bound (UCB)-based grouping federated learning (UGFL) where a data scheduling method effectively reduces the stragglers. We combined Lyapunov optimization with the UCB (Garivier and Moulines in international conference on Algorithmic Learning Theory, pp. 178-188, 2011) algorithm to design an efficient device selection method to choose the best device to participate in each global epoch. In addition, we theoretically analyzed the upper bound of convergence of our proposed method. Experimental results show that our method has higher accuracy and faster convergence speed than the existing methods.

关键词： Internet of things Federated learning Device selection Data scheduling

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Analysis and Improvement of the Power Quality in grid Integrated to distributed Generation (Solar PV System) Using UPQC

Analysis and Improvement of the Power Quality in Grid Integr...

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2023 international conference on Advanced and Global Engineering Challenges, AGEC 2023

作者： Mangalapuri, Sravani Sobhan, Polamraju. V. S. Vignan's Foundation for ScienceTechnology and Research Department of Eee Guntur India

ISBN: (纸本)9798350340969

Increased power-electronic-based non-linear loads will affect the distribution network's ability to produce and use high-quality power under the current circumstances. Now a day's identification of problems is more crucial in the electricity system. The main factors like voltage sag and voltage swell are affecting the quality of power for connecting a non-linear load to the system. The proposed system aims to assess the grid's power quality issues caused by distributed photovoltaic generation while also computing the Total harmonic Distortion (THD). In the proposed system, the Unified Power Quality Conditioner (UPQC) based Artificial Neural Network (ANN) controller is used to alleviate power quality issues and lower THD levels. When Compare to all conventional controllers the proposed method will gives better results. Using the MATLAB/SIMULINK software, the UPQC will be designed with the Vector Template Generation (VTG) and park transformation theory with MPPT technique in the shunt part for generating the signals. © 2023 IEEE.

关键词： Power quality

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Analyze the Impact of distributed Generation Units on Distribution System Performances

Analyze the Impact of Distributed Generation Units on Distri...

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

作者： Patel, Hemant Saw, Bikash Kumar Bohre, Aashish Kumar Yadav, Omkar Nit Durgapur Dept. of Electrical Engineering Durgapur India

ISBN: (纸本)9798350310573

This paper introduces a methodology for the optimal allocation and sizing of distributed Generation (DG) through the utilization of the Particle Swarm Optimization Technique (PSO). An objective optimization function (OOF) is used to improve voltage profiles and enhance overall system reliability concurrently with short circuit analysis. Additionally, the OOF effectively reduces both active and reactive power losses. The optimization process entails load flow computations within the distribution system, and simulations are executed using DigSILENT software to assess the outcomes. The research is centered on the IEEE 69 bus distribution system, which integrates DG solutions based on renewable energy resources. Two scenarios are considered in the analysis without DG and with DG. By comparing the results obtained from these scenarios, it becomes evident that the proposed methodology yields superior outcomes, underscoring its effectiveness in enhancing the performance of the distribution system. © 2023 IEEE.

关键词： distributed Generation (DG) Particle Swarm Optimization (PSO) Radial Distribution Network (RDN) Reliability Short circuit

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Scenario based intelligent desensitization and dynamic access control technology for power distribution and distributed new energy data resources 6

Scenario based intelligent desensitization and dynamic acces...

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6th international conference on Intelligent computing, Communication, and Devices, ICCD 2023

作者： Min, Xu Aihua, Zhou Yiqing, Wang Xiaofeng, Shen Lin, Peng Nige, Li Gang, Wang He, Wang State Grid Smart Grid Research Institute Co. LTD. Jiangsu Nanjing210003 China State Grid Key Laboratory of Information and Network Security Nanjing210003 China State Grid Jiangsu Electric Power Co. Ltd Jiangsu Nanjing210024 China State Grid Shanghai Electric Power Company Shanghai200122 China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

The new power system has a new operation mode of "the source follows the load, the load follows the network, and the source loads interact". With the continuous excavation of flexible regulation resources, new third-party entities such as virtual power plants or load integrators need to consider implementing differentiated network security protection requirements to ensure their fair access to business. At the same time, with the clarity of the regulation level of the new power system and the continuous participation of various entities in the construction, the company's network security protection boundary will no longer be "horizontal and vertical", but will become more uneven, with more types of interfaces and interfaces. It is necessary to refine the boundary protection measures according to different interaction needs. The new regulatory subject on the demand side of the new power system involves the privacy information of a large number of users. Data flow and sharing, cross access and collaborative analysis among the subjects have security problems such as unauthorized access and privacy leakage. This paper focuses on the scenario based intelligent desensitization and dynamic access control technology for power distribution and distributed new energy data resources, and combs various factors involved in the data access process, On the basis of obtaining the data access authority, the dynamic correlation analysis of the three elements of user role and access authority, sensitive data level, power allocation and distributed new energy business scenario is integrated, and finally the appropriate desensitization method is selected from the desensitization algorithm library, and finally the appropriate desensitization method is selected from the desensitization algorithm library to ensure the security protection capability of the new distribution network under the flexible, open and interactive energy scenario, Effectively respond to new major network security ris

关键词： Network security

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Time-Aware Edge computing Method for High-Frequency Acquisition of Low-Voltage Distribution Substation Area 3

Time-Aware Edge Computing Method for High-Frequency Acquisit...

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3rd international conference on Electrical Engineering and Control Science, IC2ECS 2023

作者： Song, Peng Zhang, Yongwang Lu, Tao Chen, Peng Yang, Zhicong Li, Qian Zhao, Binghui Guangdong Power Grid Co. Ltd. Metrology Center Guangdong China

ISBN: (纸本)9798350382426

With the digital transformation of the new power system, massive information collection devices are deployed in low-voltage substation area, leading to a proliferation of power business data. Edge computing can sink computing and storage resources to realize distributed processing of data and relieve network transmission pressure. However, due to the limited computing resources of edge servers, massive data access will lead to competition for computing resources as well as communication resources, making it difficult to realize real-time processing of high-frequency collection data in the low-voltage distribution substation area. To solve the above problems, we propose an edge computing framework for the high-frequency collection of information in low-voltage distribution substation area based on delay awareness. Then, we formulate the optimization problem of minimizing the data transmission delay and edge server processing delay. An edge computing method based on mutual benefit game is proposed to solve the optimization problem. Simulation results show that the proposed algorithm has excellent performance in delay. © 2023 IEEE.

关键词： delay-awareness edge computing high-frequency information acquisition Low-voltage distribution

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Hex-Cell Clustering Based distributed Service Discovery Algorithm for MANETs 15

Hex-Cell Clustering Based Distributed Service Discovery Algo...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Prabu, B. Jagatheeshkumar, G. Department of Computer Science Karuppann Mariappan College Tamilnadu Muthur India

ISBN: (纸本)9798350370249

Mobile Ad-Hoc Network (MANET) is a type of wireless network consisting of mobile devices (such as laptops, smartphones, tablets, etc.) that communicate with each other without the need for a centralized infrastructure like base stations or access points. MANETs are highly dynamic and adaptable, making them suitable for scenarios where traditional infrastructure-based networks are impractical or unavailable. Service discovery remains a formidable challenge in MANETs, with the primary concern being the efficient assignment of optimal services to service requesters. This study proposes a novel Hex-cell Clustering based distributed Service Discovery Algorithm (HC-DSDA) tailored specifically for MANETs. Utilizing a hexagonal grid structure for clustering, the algorithm appoints a Mobile Cluster Head (MCH) within each cell, tasked with coordinating with other MCHs in their respective cells. The Mscore (Mobile Score) concept were introduced to select MCH in an efficient manner which is calculated through the trust parameters of each mobile node. Extensive simulations validate the efficacy of the proposed algorithm, showcasing enhancements in precision, recall, F-measure, and time consumption. These results underscore the algorithm's potential in improving service discovery within MANETs, thereby addressing critical challenges in dynamic network environments. ©2024 IEEE.

关键词： Mobile ad hoc networks

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Simulation of Performance Evaluation Model of Cloud computing Platform Based on Deep Learning

Simulation of Performance Evaluation Model of Cloud Computin...

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2023 international conference on Internet of Things, Robotics and distributed computing, ICIRDC 2023

作者： Ma, Xin Gu, Liang Duan, Xiaorong Wang, Liguo Liu, Zeyu Information and Communication Branch State Grid Shanxi Electric Power Company Shanxi Taiyuan030021 China

ISBN: (纸本)9798350375275

With the wide application of cloud computing platform, more and more enterprises and individuals migrate their data to cloud computing platform. However, how to accurately evaluate and measure its performance and ensure the quality of service of users while making full use of resources is still an important problem to be solved urgently in the development of cloud computing platform. In this paper, a performance evaluation model of cloud computing platform based on deep learning is proposed. Based on BPNN (BP neural network) model, the complex nonlinear relationship between system input characteristics and service efficiency is simulated, and the efficiency model based on BPNN is established. The structure of the model mainly includes input module, data hiding module and output module. In this paper, a three-layer BPNN model is adopted, and based on the overall architecture of the intelligent service framework, the key input features affecting the overall service efficiency are extracted from each layer of the framework, and the overall service efficiency is predicted by using the BPNN model. The simulation results show that the prediction value of service efficiency based on BPNN optimization model is closer to the measured value than the traditional model without optimization algorithm. The experimental results show that the optimization model based on BPNN proposed in this paper has good computational efficiency and accuracy as a prediction model. It is proved that it can accurately evaluate the performance of cloud computing platform in practical application. © 2023 IEEE.

关键词： Cloud computing

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Ordered Scheduling in Control-Flow distributed Transactional Memory 19th

Ordered Scheduling in Control-Flow Distributed Transactional...

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19th international conference on distributed computing and Intelligent Technology (ICDCIT)

作者： Poudel, Pavan Rai, Shishir Guragain, Swapnil Sharma, Gokarna ATGWORK Norcross GA USA Kent State Univ Kent OH 44242 USA

ISBN: (纸本)9783031248474;9783031248481

Consider the control-flow model of transaction execution in a distributed system modeled as a communication graph where shared objects positioned at nodes of the graph are immobile but the transactions accessing the objects send requests to the nodes where objects are located to read/write those objects. The control-flow model offers benefits to applications in which the movement of shared objects is costly due to their sizes and security purposes. In this paper, we study the ordered scheduling problem of committing dependent transactions according to their predefined priorities in this model. The considered problem naturally arises in areas, such as loop parallelization and state-machine-based computing, where producing executions equivalent to a priority order is needed to satisfy certain properties. Specifically, we study ordered scheduling considering two performance metrics fundamental to any distributed system: (i) execution time - total time to commit all the transactions and (ii) communication cost - the total distance traversed in accessing required shared objects. We design scheduling algorithms that are individually or simultaneously efficient for both the metrics and rigorously evaluate them through several benchmarks on random and grid graphs, validating their efficiency. To our best knowledge, this is the first study of ordered scheduling in the control-flow model of transaction execution.

关键词： Scheduling algorithms

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