Smart grid is a fully automated power supply network, in which each user and node are monitored in real time, and ensure the two-way flow of current and information from the power plant to each point of the user's electrical appliances. Through distributed intelligent and broadband communication and the inheritance of automatic control system, smart grid ensures the real-time transaction of the power market and the seamless connection and real-time action among grid members. With the continuous expansion of the scale, the smart grid system has produced a large amount of power data. However, affected by the infrastructure of information and communication system, the smart grid has some problems, such as weak real-time performance of data sharing, weak flexibility of data acquisition and processing applications, and low intelligence, which restricts the safe and stable operation of smart grid and the improvement of system service quality.
Edge computing technology is an extension of cloud computing, which provides users with nearby services near edge infrastructure or a large number of data terminals. Edge computing is an open platform integrating network, computing, storage, and application core capabilities. Based on edge computing, power equipment terminals can analyze power data locally, so as to improve data processing efficiency and reduce system delay and load of cloud computing. Meanwhile, the edge computing system can provide personalized customized services for different power consumption needs of power users, provide users with faster demand response, and realize one-stop management and control for power customers. This Special Issue aims to collect original papers about the recent advance of edge computing technology applied to the smart grid and present important results in the fields of system optimization, fault detection, intelligent protection, load analysis and forecasting, security and privacy, etc. The works can be applied to the research anddevelopment of new procedures or components, original application of existing knowledge, or new design approaches. Review articles describing the state of the art are also welcomed.
Potential topics include but are not limited to the following:
• Integration framework of computing, communication, perception at the edge of smart grid
• Resource allocation and task scheduling at the edge of smart grid
• Terminal key management and access authentication technology for smart grid
• Fault detection of equipment and network at the edge of smart grid
• Topology identification and line loss rate calculation of smart grid
• Analysis of user behavior characteristics at the edge of smart grid
• Non-invasive load monitoring of smart grid household electrical equipment
• Load forecasting of end users at the edge of smart grid
• Demand response at the edge of smart grid
• Optimal control of microgrid system with distributed energy
• Distributed cooperative optimal scheduling of multi-microgrid system
• Distributed intelligent transaction decision of multi-microgrid system
• Electric vehicle charging behavior analysis and charging optimization
• Service security of intelligent charging of electric vehicles
Smart grid is a fully automated power supply network, in which each user and node are monitored in real time, and ensure the two-way flow of current and information from the power plant to each point of the user's electrical appliances. Through distributed intelligent and broadband communication and the inheritance of automatic control system, smart grid ensures the real-time transaction of the power market and the seamless connection and real-time action among grid members. With the continuous expansion of the scale, the smart grid system has produced a large amount of power data. However, affected by the infrastructure of information and communication system, the smart grid has some problems, such as weak real-time performance of data sharing, weak flexibility of data acquisition and processing applications, and low intelligence, which restricts the safe and stable operation of smart grid and the improvement of system service quality.
Edge computing technology is an extension of cloud computing, which provides users with nearby services near edge infrastructure or a large number of data terminals. Edge computing is an open platform integrating network, computing, storage, and application core capabilities. Based on edge computing, power equipment terminals can analyze power data locally, so as to improve data processing efficiency and reduce system delay and load of cloud computing. Meanwhile, the edge computing system can provide personalized customized services for different power consumption needs of power users, provide users with faster demand response, and realize one-stop management and control for power customers. This Special Issue aims to collect original papers about the recent advance of edge computing technology applied to the smart grid and present important results in the fields of system optimization, fault detection, intelligent protection, load analysis and forecasting, security and privacy, etc. The works can be applied to the research anddevelopment of new procedures or components, original application of existing knowledge, or new design approaches. Review articles describing the state of the art are also welcomed.
Potential topics include but are not limited to the following:
• Integration framework of computing, communication, perception at the edge of smart grid
• Resource allocation and task scheduling at the edge of smart grid
• Terminal key management and access authentication technology for smart grid
• Fault detection of equipment and network at the edge of smart grid
• Topology identification and line loss rate calculation of smart grid
• Analysis of user behavior characteristics at the edge of smart grid
• Non-invasive load monitoring of smart grid household electrical equipment
• Load forecasting of end users at the edge of smart grid
• Demand response at the edge of smart grid
• Optimal control of microgrid system with distributed energy
• Distributed cooperative optimal scheduling of multi-microgrid system
• Distributed intelligent transaction decision of multi-microgrid system
• Electric vehicle charging behavior analysis and charging optimization
• Service security of intelligent charging of electric vehicles
