云计算
计算机科学
边缘计算
虚拟化
智能电网
延迟(音频)
GSM演进的增强数据速率
网格
虚拟机
分布式计算
信息物理系统
嵌入式系统
实时计算
操作系统
工程类
电信
几何学
电气工程
数学
作者
Nikolaos Tzanis,Eleftherios Mylonas,Panagiotis Papaioannou,Michael Birbas,Alexios Birbas,Christos Tranoris,Spyros Denazis,A. Papalexopoulos
出处
期刊:IEEE Transactions on Cloud Computing
[Institute of Electrical and Electronics Engineers]
日期:2023-04-01
卷期号:11 (2): 1230-1241
被引量:1
标识
DOI:10.1109/tcc.2023.3241698
摘要
Edge Cloud is providing unprecedented opportunities for IoT and WAMS (Wide Area Monitoring Systems) in electrical grid operation. It is an orchestrated environment able to address low latency events through appropriate edge-cloud computing configurations. Transient State Estimation (TSE) is a key monitoring tool for capturing a reliable knowledge of the Smart Grid status in real-time, given the impediments introduced by the increasing penetration of Distributed Energy Resources in the energy mix. Frequency response anomalies, large scale transients, and voltage swings can be captured by TSE for real time or post failure data analytics. This work presents a cloud edge framework for the efficient calculation of TSE which, albeit its benefits, demands high computational resources at the edge (close to the measurement units) along with ultra low latency communications. The framework enables TSE as a service through the coordination of Virtual Machines (VMs) running on virtualized infrastructure and other non-virtualized physical nodes. In order to support the stringent time requirements, part of the TSE is offloaded to dedicated hardware acceleration units (FPGA). The proposed TSE framework is validated using an IEEE 30-bus, and the results show a significant superiority in terms of total latency compared to conventional cloud and edge deployments.
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