Aim and Scope
Smart grids are being equipped with modern computation, communication, monitoring and control technologies, which transforms the way we operate and interact with these systems. The large volume of generated data and real-time analysis requirements of smart grids call for new solutions to handle various types of processing and communications in these systems. Particularly, Distributed Energy Resources and Energy Storages as well as new reliability and security challenges affecting the smart grids suggest the need for improving monitoring and control of these system with the help of new technologies. The new edge/fog computing technology with close integration with the Internet of Things (IoT) is emerging as a new alternative to existing computation and cloud-based mechanisms proposed for smart grids. Edge computing provides geographically distributed, latency-sensitive and high-resilience computation and storage resources, which are essential for many real-time and computationally intensive data handling and data analytics in smart grids. Such edge layer can be deployed in the distribution, generation or transmission layer of the system for a wide range of applications, such as demand response management as well as mission-critical and real-time applications for monitoring and control of transmission network. This workshop provides a unique platform for researchers and practitioners in the areas of smart grid and communication and computation systems to exchange and discuss their recent ideas, research achievements, design and implementation experiences in enabling smart grids with edge computing technology. This workshop solicits unpublished research work in the following topics of interest including but not limited to:
- Edge/fog computing applications for Smart Grids
- Edge processing for smart grid IoT systems
- Edge computing for distribution and transmission networks
- Edge-enabled Advanced Metering Infrastructure
- Edge computing for distributed energy resource management
- Architecture design and implementation of edge-based smart grid
- Edge-based machine-learning and data analytics for smart grids
- Edge-based distributed analytics for smart grid’s reliability and security
- Resource management and optimization of edge computing for smart grid applications
- Security and privacy for edge-based smart grids
- Reliability of edge computing for smart grid applications
- Experimental evaluations and testbeds for edge-enabled smart grid applications
