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检索条件"任意字段=7th IEEE/ACM International Conference on Grid Computing"

共 9693 条记录，以下是31-40 订阅

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Multi-objective Dynamic Economic Dispatch 8th

Multi-objective Dynamic Economic Dispatch

引用

8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Yang, Wenqiang Zhu, Xinxin School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang 453003 Henan China

ISBN: (纸本)9789819602247

Power system's efficient operations and management heavily rely on dynamic economic dispatch (DED), which, due to its integration with spatial and temporal factors, poses a elaborate and intricate challenge in optimizing decision-making processes. the introduction of vehicle-to-grid (V2G) technology, which allows for the integration of plug-in electric vehicles (PEVs) to connect to the grid, serves as a viable solution to mitigate grid fluctuations and capitalize on the advantages of load leveling during peak times and utilizing off-peak electricity consumption. the paper introduces a model that incorporates current date, hourly dispatch of power systems as well as the influence exerted by Plug-in Electric Vehicles (PEVs). To resolve the model, an Osprey optimization algorithm (OOA) is introduced. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Vehicle-to-grid

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Edge computing-Driven Optimization of Electricity Consumption Information Collection 24

Edge Computing-Driven Optimization of Electricity Consumptio...

引用

Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Jingting Lei Lijun Wang Min Zhang Marketing Department of State Grid Shaanxi Electric Power Co. Ltd. Xian Shaanxi China State Grid Shaanxi Electric Power Co. Ltd. Weinan Power Supply Company Weinan Shaanxi China State Grid Xian Power Supply Company Electricity Metering Center Xian Shaanxi China

ISBN: (纸本)9798400707087

As the scale of the power system enlarges, the current system of collecting power consumption information has the disadvantages of delays in transmitting information, excessive bandwidth pressure, and the lack of real-time information processing capability. In order to alleviate the aforementioned issues, this paper provides an edge computing method to enhance the system of collecting power consumption information. the edge computing concept is to execute the preprocessing, analysis, and decision-making functions of the data near the source end at the edge nodes to decrease the center server load and enhance the real-time nature and reliability of the system. this paper initiates the explanation of the use cases of edge computing to collect power consumption information and verifies the optimization strategies of edge computing through specific examples. In practical use cases, edge nodes execute functions such as anomaly detection of power consumption and fault alarms through real-time monitoring and analysis of the information, significantly decreasing the amount of transmitted information and the system's response time. the results prove that the edge computing optimization strategy has superior performance in the efficiency of transmitting information, the ability to process real-time information, and system stability, providing a new technical means to the intelligence and efficiency of the system of collecting power consumption information.

关键词： Anomaly Detection

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Research on Intelligent Scheduling and Optimization Algorithm of Mobile Nursing 24

Research on Intelligent Scheduling and Optimization Algorith...

引用

Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Hong Chang Hong Tian Shenbo Xuan Jindi Wang Ying Feng State Grid Beijing Electric Power Hospital Information Center Beijing China State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijing China

ISBN: (纸本)9798400707087

this study conducted an in-depth discussion on the intelligent scheduling and optimization algorithm of mobile nursing. By constructing an optimization model for cost minimization and resource maximization utilization, combined with heuristic algorithms, the scheduling efficiency and resource utilization were significantly improved. Specifically, through strategies such as parameter tuning, heuristic improvement, and parallel computing, the optimized algorithm performs well in key indicators such as cost control, resource consumption, and task completion time. Experimental results show that the optimized algorithm can maintain good performance under different task loads, especially under high load conditions. through real data set testing, the robustness and broad applicability of the algorithm are verified. this research not only improves the efficiency of the mobile nursing system and provides solid technical support for practical applications, but also provides valuable theoretical foundation and practical experience for the further optimization and application of intelligent scheduling algorithms.

关键词： Intelligent Scheduling

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Research on Adaptive Segmentation and Collaborative computing of Edge Intelligence Model in Power Edge Gateway 24

Research on Adaptive Segmentation and Collaborative Computin...

引用

Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Wei Zhang Peng Wang Zenghai Wang Jie Yang Feng Jiao Liguo Liu State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijng China

ISBN: (纸本)9798400707087

this paper proposes an edge intelligence model adaptive segmentation and collaborative computing method for power edge gateways to improve computing efficiency and resource utilization. First, an adaptive segmentation algorithm is studied and designed to effectively optimize the computational overhead and delay by adjusting the segmentation strategy of the model in real time. Next, the design of the collaborative computing framework realizes efficient data interaction between edge nodes, and uses advanced data exchange protocols to improve the reliability and speed of communication between nodes. through empirical analysis, it has been verified that the model has significant performance improvements in application scenarios such as real-time fault detection, load forecasting, and smart meter reading analysis. Compared with traditional methods, the performance improvement rate reaches more than 20%. Experimental results show that the model proposed in this paper has high computational efficiency, resource utilization and task response capabilities, and can adapt to diverse power system application requirements. In summary, this article provides theoretical and practical support for the application of edge intelligence in power gateways and verifies its effectiveness in practical application scenarios.

关键词： Adaptive Segmentation

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Research on Distribution Network Load Classification and Identification Technology Based on Edge computing 24

Research on Distribution Network Load Classification and Ide...

引用

Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Yuankun Jiang Wei Zhang Yuan Liu Liguo Liu Xuehua Li Chenjie Yang State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijng China SGIT-UNI (QINGDAO) CLOUD DATA TECHNOLOGY CO. LTD. Beijng China

ISBN: (纸本)9798400707087

In response to the needs of distribution network load classification and identification, this study proposes an efficient classification method based on edge computing, aiming to solve the problem of high real-time and accuracy requirements in the power system. through in-depth analysis of the application potential of edge computing in power systems, a lightweight neural network model was designed and optimized through the momentum gradient descent method, which significantly improved the model's convergence speed and computational efficiency. In the experimental verification, through field testing in multiple scenarios, the results showed that the method performed well in terms of classification accuracy, latency and resource utilization, especially in the classification of residential, commercial and industrial loads, showing high accuracy and Lower processing latency. In addition, through in-depth analysis of actual application cases, this study further proves the wide applicability and application value of edge computing in power load classification. the results of this research provide a new technical path for the optimization and management of power systems, and lay a theoretical and practical foundation for the development of future smart grids.

关键词： Distribution Network

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Genetic Algorithm-Based Optimal EV Charging Station and V2G Allocation with Power Factor Control

Genetic Algorithm-Based Optimal EV Charging Station and V2G ...

引用

international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Ismail A. Soliman Vladimir Tulsky Hossam A. Abd El-Ghany Electrical Power Systems Department National Research University “MPEI” Moscow Russian Federation Electrical Power and Machines Engineering Department Faculty of Engineering Tanta University Tanta Egypt

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

the worldwide shift toward electric vehicles (EVs) aims to mitigate climate change and reduce pollution. Advancements in battery technology have significantly boosted the EV industry, accelerating the transition from hybrid to fully electric vehicles. To sustain this growth, the widespread availability of EV charging stations (EVCS) is essential. However, integrating EVCS into the distribution network introduces challenges, including potential power system constraints and quality standards violations. this study proposes an optimal approach for integrating EVCS into distribution systems while adhering to power quality constraints, such as minimizing energy losses, enhancing voltage stability, and improving the system power factor. A Genetic Algorithm is employed to define the optimal locations for EVCS, Vehicle-to-grid (V2G) allocation, and V2G power factor. Simulations are conducted using the radial system ieee-33 bus, along with load curves and EV charging/discharging profiles, demonstrating the proposed approach's effectiveness in improving voltage stability and reducing energy losses.

关键词： Vehicle-to-grid Reactive power Energy loss Pollution Stability criteria Power quality Power system stability Electric vehicle charging Resource management Genetic algorithms

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Study on Key Technologies of Edge Intelligence for Long-Distance, Large-Scale, and Complex Environment Power Inspection 24

Study on Key Technologies of Edge Intelligence for Long-Dist...

引用

Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Luyun Zhang Ying Zou Yefeng Zhang Jie Liu Zifeng Zhang Wenfeng Xue State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijing China

ISBN: (纸本)9798400707087

this paper studies the application and key technologies of edge intelligence technology in long-distance, large-scale, and complex environment power inspection. Traditional power inspection relies on cloud computing, but when faced with real-time and low-latency requirements, the cloud computing model has limitations and is difficult to adapt to the inspection needs of complex environments. this study first analyzes the current status and technical challenges of power inspection, and proposes a solution based on edge intelligence. through a multi-layer architecture design, the collaborative work of data collection, real-time processing, and global analysis is realized between the perception layer, edge computing layer, and cloud layer. On this basis, the key technologies of multi-source data fusion, fault diagnosis algorithm, and system optimization are studied, especially for the specific application of long-distance transmission line and substation equipment inspection scenarios, and performance evaluation is carried out. the results show that the edge intelligence system has significant advantages in reducing data transmission delay, improving fault identification accuracy, and enhancing system responsiveness. this study shows that edge intelligence technology provides a more real-time, stable, and reliable solution for power inspection, and has broad application prospects.

关键词： edge intelligence

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Design of a peer-to-peer information system using the GT4 Index Service 06

Design of a peer-to-peer information system using the GT4 In...

引用

7th ieee/acm international conference on grid computing

作者： Bharathi, Shishir Chervenak, Ann Univ So Calif Inst Informat Sci Marina Del Rey CA 90292 USA

No abstract available.

ISBN: (纸本)9781424403431

No abstract available.

关键词： Peer to peer computing Information systems Query processing Aggregates Organizing Monitoring Engines Testing Catalogs Scheduling

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GriCoL: A language for grid computing 06

GriCoL: A language for Grid computing

引用

7th ieee/acm international conference on grid computing

作者： Currle-Linde, Natalia Resch, Michael Univ Stuttgart High Performance Comp Ctr HLRS Nobelstr 19 D-70550 Stuttgart Germany

ISBN: (纸本)9781424403431

the development of the grid has opened new possibilities for scientists and engineers to execute large-scale modeling experiments. this has stimulated the generation and development of tools for the creation and management of complex computing experiments in the grid. Among these, tools for the automation of the programming of experiments play a significant role. In this paper we present GriCoL, which we propose as a simple and efficient language for the description of complex grid experiments.

关键词： grid computing Logic Large-scale systems Control systems Flow graphs Parallel processing Application software Wrapping Libraries Parallel programming

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A set coverage-based mapping heuristic for scheduling distributed data-intensive applications on global grids 06

A set coverage-based mapping heuristic for scheduling distri...

引用

7th ieee/acm international conference on grid computing

作者： Venugopal, Srikumar Buyya, Rajkumar Univ Melbourne Dept Comp Sci & Software Engn GRIDS Lab Parkville Vic 3052 Australia

ISBN: (纸本)9781424403431

Data-intensive grid applications need access to large datasets that may each be replicated on different resources. Minimizing the overhead of transferring these datasets to the resources where the applications are executed requires that appropriate computational and data resources be selected. In this paper, we introduce a heuristic for the selection of resources based on a solution to the Set Covering Problem (SCP). We then pair this mapping heuristic with the well-known MinMin scheduling algorithm and conduct performance evaluation through extensive simulations.

关键词： Processor scheduling grid computing Computer networks Testing Application software Pervasive computing Astronomy Laboratories Computer science Software engineering

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