Abstract
Edge computing provides an ideal platform to enable many critical and time-sensitive applications in monitoring and operation of critical cyber-physical systems, such as smart grids. In this paper, we consider one of the key operations for smart gridâ™s reliability, which is situational awareness and discuss the role that the edge computing can play to enhance this operation by providing distributed state estimation (DSE) locally at the edge nodes. We specifically focus on the network of the phasor measurement units (PMUs) as an example of the industrial internet of things in smart grids and discuss the edge-computing platform architecture to enable data analytics for DSE using the PMU time-series. We discuss that it is important to consider the physics of the smart grid in designing the edge-computing layer. As an example, we present a data-driven method for detecting power line trips using the PMU data and the designed physics-aware edge-computing platform.
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings |
| ISBN (Electronic) | 9781728109602 |
| DOIs | |
| State | Published - Dec 2019 |
| Event | 2019 IEEE Globecom Workshops, GC Wkshps 2019 - Waikoloa, United States Duration: Dec 9 2019 → Dec 13 2019 |
Publication series
| Name | 2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings |
|---|
Conference
| Conference | 2019 IEEE Globecom Workshops, GC Wkshps 2019 |
|---|---|
| Country/Territory | United States |
| City | Waikoloa |
| Period | 12/9/19 → 12/13/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Edge Computing
- Energy Data Analytics
- Fog Computing
- Internet of Things
- Situational Awareness
- Smart Grids
- State Estimation
ASJC Scopus subject areas
- Computer Networks and Communications
- Hardware and Architecture
- Software
- Control and Optimization
