The development of digital technologies has been penetrating all areas of energy revolution. Based on the in-depth integration of advanced digital technologies, distribution networks are gradually transforming into digital distribution networks (DDNs) with a tremendous change ranging from the structure to the operation mode. DDNs will be the digitalized appearance of the physical distribution network, in which ubiquitous connections and massive data will become the basic characteristics. The construction of DDNs has the potential to apply cloud computing, big data, Internet of Things, mobile internet, artificial intelligence, blockchain, and other new-generation digital technologies to accelerate high-quality electricity service and intelligent operation. Among these digital technologies, edge computation is a critical part allowing computation to be performed at the edge of network. The researches on edge computation and DDNs are essential to promote the transformation and upgrading of the intelligent energy industry.
The research goal is to use data as the core to realize the system organization and functional operation of distribution networks. Without completely relying on the physical model, it will become an irreversible direction to realize the integration of data and modeling of DDNs. Moreover, in-depth research on refining the mechanism, rules, and knowledge of DDNs is needed for intelligent operation based on data. As the edge computation can process applications transferred to the edge side and conduct basic data analysis with rapid response, it is effective to alleviate the pressure of massive data communication. The key to intelligent control of DDN lies in the performance of edge computing chips, on-site data fusion mining methods, and effective collaboration of differentiated applications on the edge side. To develop high-quality intelligent electricity services, it is necessary to find out advanced digital technology to build DDNs as well as electric edge computing core chips and equipment.
This Research Topic will mainly focus on edge computation and DDNs. The aim is to present a state-of-the-art collection of innovative approaches, algorithms, and tools for edge computation and intelligent operation of DDNs. This will provide an opportunity for researchers and practicing engineers to share their latest discoveries and best practices in these areas.
The topics of interest to this issue include, but are not limited to, the following:
1. Concept and technical features of digital distribution networks
2. Edge computation in digital distribution networks
3. Data-driven/artificial Intelligence-based methods for intelligent operation of DDNs
4. Advanced computational, simulation and analysis methods for large-scale DDNs
5. Design of power edge computing core chips for DDNs
6. Planning and construction of DDNs based on digital twin and digital platform
7. Pilot projects of edge computation and intelligent operation of DDNs.
The development of digital technologies has been penetrating all areas of energy revolution. Based on the in-depth integration of advanced digital technologies, distribution networks are gradually transforming into digital distribution networks (DDNs) with a tremendous change ranging from the structure to the operation mode. DDNs will be the digitalized appearance of the physical distribution network, in which ubiquitous connections and massive data will become the basic characteristics. The construction of DDNs has the potential to apply cloud computing, big data, Internet of Things, mobile internet, artificial intelligence, blockchain, and other new-generation digital technologies to accelerate high-quality electricity service and intelligent operation. Among these digital technologies, edge computation is a critical part allowing computation to be performed at the edge of network. The researches on edge computation and DDNs are essential to promote the transformation and upgrading of the intelligent energy industry.
The research goal is to use data as the core to realize the system organization and functional operation of distribution networks. Without completely relying on the physical model, it will become an irreversible direction to realize the integration of data and modeling of DDNs. Moreover, in-depth research on refining the mechanism, rules, and knowledge of DDNs is needed for intelligent operation based on data. As the edge computation can process applications transferred to the edge side and conduct basic data analysis with rapid response, it is effective to alleviate the pressure of massive data communication. The key to intelligent control of DDN lies in the performance of edge computing chips, on-site data fusion mining methods, and effective collaboration of differentiated applications on the edge side. To develop high-quality intelligent electricity services, it is necessary to find out advanced digital technology to build DDNs as well as electric edge computing core chips and equipment.
This Research Topic will mainly focus on edge computation and DDNs. The aim is to present a state-of-the-art collection of innovative approaches, algorithms, and tools for edge computation and intelligent operation of DDNs. This will provide an opportunity for researchers and practicing engineers to share their latest discoveries and best practices in these areas.
The topics of interest to this issue include, but are not limited to, the following:
1. Concept and technical features of digital distribution networks
2. Edge computation in digital distribution networks
3. Data-driven/artificial Intelligence-based methods for intelligent operation of DDNs
4. Advanced computational, simulation and analysis methods for large-scale DDNs
5. Design of power edge computing core chips for DDNs
6. Planning and construction of DDNs based on digital twin and digital platform
7. Pilot projects of edge computation and intelligent operation of DDNs.
