电力信息与通信技术2026，Vol.24Issue(4)：15-23,9.DOI:10.16543/j.2095-641x.electric.power.ict.2026.04.03
基于通感一体化技术的数字换流站网络覆盖增强方法
The Network Coverage Enhancement Method for Digital Converter Stations Based on Integrated Sensing and Communication Technology
摘要
Abstract
With the construction of new power systems,digital technology has become the core driving force to improve the quality and efficiency of the grid.In the digital converter station(DCS),the use of drones and robots for inspection often encounters challenges such as roadblocks and abnormal conditions,and the traditional DCS network does not effectively integrate the perception function of the equipment.Therefore,this paper proposes an approach based on integrated sensing and communication(ISAC)and multiple input multiple output(MIMO),which aims to integrate communication and sensing functions in DCS to improve system performance.However,the complex converter station environment and signal fusion process bring about problems such as limited communication coverage and general inductance interference,especially in practical applications,networks need to face special communication requirements such as high bandwidth,low delay and high reliability.In order to solve these challenges,a DCS-MIMO-ISAC network model is designed to optimize the synsense-to-noise ratio of the system,and increase the signal strength through multi-antenna technology and beamforming method,so as to expand the network coverage.Firstly,two strategies of independent design and joint design are proposed in this paper,and the advantages of joint design and MIMO technology are verified by simulation.In addition,considering the actual business scenario of the digital converter station,the simulation results combined with practical application requirements such as load scheduling and equipment monitoring,and further verified the effectiveness of the proposed scheme in the business environment.Further,the deep reinforcement learning algorithm is used to optimize the beamforming strategy to improve the SNR and coverage of the network.The simulation results show that compared with random Angle selection,the proposed scheme significantly improves the total SNR of the system,and has strong practical application potential.关键词
大规模MIMO/通感一体化/波束形成/深度强化学习Key words
massive multiple input multiple output(MIMO)/integrated sensing and communication(ISAC)/beamforming/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
张东磊,陆阳,王默,周雪,从宇..基于通感一体化技术的数字换流站网络覆盖增强方法[J].电力信息与通信技术,2026,24(4):15-23,9.基金项目
国家电网有限公司总部科技项目资助"数字换流站物联感知体系与关键技术研究及应用"(5700-202324620A-3-2-ZN). （5700-202324620A-3-2-ZN）
