深度强化学习驱动下的智能电网通信网业务路由分配方法研究
Research on Service Routing Allocation Method of Smart Grid Communication Network Driven by Deep Reinforcement Learning
胡楠 1张维1
作者信息
- 1. 国网汉中供电公司,陕西汉中 723000
- 折叠
摘要
在现代化背景下,为确保电力系统的稳定运行,相关人员需要结合实际情况逐步推进智能电网的构建.智能电网以各项数据的获取、处理、保护为核心,建立了集成通信系统.文章针对深度强化学习驱动下的智能电网通信网业务路由分配方法展开分析,以提高通信资源利用率,提升业务路由方法的稳定性和可靠性.
Abstract
Under the background of modernization,in order to ensure the stable operation of power system,relevant personnel need to gradually promote the construction of smart grid according to the actual situation.Smart grid takes the acquisition,processing and protection of various data as the core,and establishes an integrated communication system.This paper analyzes the service routing method of smart grid communication network driven by deep reinforcement learning,in order to improve the utilization rate of communication resources and improve the stability and reliability of service routing method.
关键词
智能电网/通信网/深度Q网络(DQN)算法/异步优势演员-评论家(A3C)算法/深度学习Key words
smart grid/communication network/Deep Q Network(DQN)algorithm/Asynchronous Advantage Actor-Critic(A3C)algorithm/deep learning引用本文复制引用
出版年
2024
NETL
NSTL
万方数据