Edge-cloud Computing Systems for Smart Grid: State-of-the-art, Architecture, and Applications

Abstract

The quantity and heterogeneity of intelligent energy generation and consumption terminals in the smart grid are increasing drastically over the years. These edge devices have created significant pressures on cloud computing (CC) system and centralised control for data storage and processing in realtime operation and control. The integration of edge computing (EC) can effectively alleviate the pressure and conduct real-time processing while ensuring data security. This paper conducts an extensive review of the EC-CC computing system and its application to the smart grid, which will integrate a vast number of dispersed devices. It first comprehensively describes the relationship among CC, fog computing (FC), and EC to provide a theoretical basis for the differentiation. It then introduces the architecture of the EC-CC computing system in the smart grid, where the architecture consists of both hardware structure and software platforms, and key technologies are introduced to support functionalities. Thereafter, the application to the smart grid is discussed across the whole supply chain, including energy generation, transportation (transmission and distribution networks), and consumption. Finally, future research opportunities and challenges of EC-CC while being applied to the smart grid are outlined. This paper can inform future research and industrial exploitations of these new technologies to enable a highly efficient smart grid under decarbonisation, digitalisation, and decentralisation transitions.

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

“…For example, Carlos et al [1] propose a cloudedge-fog architecture for smart grid systems that uses edge computing for real-time data processing and decision-making, and weather data to predict power consumption. Li et al proposed an edge cloud architecture for power grid monitoring, using edge devices to collect and process data, and using cloud servers for long-term storage and analysis [2].…”

A Taxonomy and Lessons Learned From Blockchain Adoption Within the Internet of Energy Paradigm

“…By the means of offloading the computational tasks to edge/fog nodes and thus providing context-aware services that could be deployed within these small-scale edge/fog servers. The integration of edge computing with smart grid infrastructures has been evaluated in the literature [95], [96]. Whereas the integration of the paradigm with blockchain was also investigated.…”

Privacy-Preserving Data Aggregation with Dynamic Billing in Fog-Based Smart Grid

“…Since the number of SMs in grid-covered areas is exploding [8], and the real-time electricity consumption data generated by SMs have the characteristics of being high volume, velocity as well as variety [9], transmitting large amounts of data directly to the SP imposes heavy computational and communication-related burden on the system. Meanwhile, the SP may not be able to process the massive amount of data in time [10], thus inducing network latency, which is impractical for delay-sensitive SG applications.…”

“…As a supplement to the cloud computing model, FC enables users to realize computation, communication and storage locally by extending computing power to the network edge [16]. Moreover, FC has advantages over cloud computing, such as low latency and location awareness [17], which satisfies the delay-sensitive demand of SG applications and can improve the real-time performance and quality of service of the SG system [8]. Considering the promotion of FC for the sustainable development of SG, introducing FC into the SG is a current hot topic.…”