Satellite Imagery-Assisted Link-Budget Analysis Algorithm for Smart Grid Wireless Backhaul Network Planning

被引:0
作者
Vieira, Marina L. S. C. [1 ]
de lara, Marina [1 ]
Pellenz, Marcelo Eduardo [1 ]
Mochinski, Marcos Alberto [1 ]
Biczkowski, Mauricio [2 ]
Enembreck, Fabricio [1 ]
Jamhour, Edgard [3 ]
Zambenedetti, Voldi Costa [3 ]
机构
[1] Pontificia Univ Catolica Parana, Grad Program Comp Sci PPGIa, Curitiba, Parana, Brazil
[2] COPEL Distribuicao, SSG Superintendencia Smart Grid & Projetos Especi, Curitiba, Parana, Brazil
[3] Pontificia Univ Catolica Parana PUCPR, Smart Grid Res Ctr, Ctr P&I Sistemas Eletr Inteligentes CISEI, Curitiba, Parana, Brazil
来源
39TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, SAC 2024 | 2024年
关键词
Smart Cities; Smart Grids; AMI Network; Wireless Network Planning; Backhaul Network; Satellite Imagery; Link-budget Analysis;
D O I
10.1145/3605098.3635987
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Electricity companies are accelerating the process of implementing smart grids. Two main components of the smart grid architecture are the communication networks for Distribution Automation (DA) and Advanced Metering Infrastructure (AMI), responsible for communicating with the smart meters installed at the user's premises. This work focuses on planning the wireless backhaul network that supports communication networks for DA and AMI. Backhaul networking involves deploying wireless communication devices to establish wireless links for interconnecting routers, gateways, and automation equipment. Planning these wireless links can be quite challenging due to the geographical diversity of deployment environments, inaccuracies in propagation models in heterogeneous areas (rural, suburban, and urban), and the necessity for detailed databases of soil relief and coverage, which are generally paid and high cost. This paper introduces a satellite imagery-assisted algorithm designed to facilitate efficient link budget analysis for wireless links in smart grid backhaul network planning. The satellite-assisted method classifies the terrain and makes it possible to aggregate loss information from various types of obstructions, such as trees, buildings, and the elevation of the terrain itself. The method uses information from open terrain databases for predictions. The algorithm's performance was validated using real link measurements from a smart grid wireless backhaul network.
引用
收藏
页码:151 / 158
页数:8
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