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20 October 2023 Resource allocation method for multi-agent 5G communication terminals in power grids considering randomness
Zhigang Wang, Jie Bai, Qing Yang, Yong Zheng, Guangming Guo, Guofeng Zhao
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Proceedings Volume 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023); 128140M (2023) https://doi.org/10.1117/12.3010549
Event: Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 2023, Chongqing, China
Abstract
In order to effectively improve the efficiency and reliability of power grid communication and promote the intelligent development of the power grid, a multi agent 5G communication terminal resource allocation method considering randomness has been proposed for the power grid. Considering the randomness factor, the Monte Carlo method is used to complete the random power flow calculation of the multi-agent 5G communication terminal of the power grid. On this basis, a multi-agent 5G communication terminal resource allocation model for the power grid is constructed, and a hybrid particle swarm optimization algorithm is used to solve the multi-agent 5G communication terminal resource allocation model for the power grid, achieving multi-agent 5G communication terminal resource allocation. The experimental results show that the proposed method has good resource allocation performance for multi-agent 5G communication terminals in the power grid, and can effectively improve resource allocation efficiency.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Zhigang Wang, Jie Bai, Qing Yang, Yong Zheng, Guangming Guo, and Guofeng Zhao "Resource allocation method for multi-agent 5G communication terminals in power grids considering randomness", Proc. SPIE 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 128140M (20 October 2023); https://doi.org/10.1117/12.3010549
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KEYWORDS
Power grids
Particles
Monte Carlo methods
Particle swarm optimization
Computer simulations
Reliability
Data communications
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