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Energy storage-photovoltaic-load topology diagram.
Source publication
With the continuous deployment of smart grids, various new smart technologies applied to the power grids have emerged, and the security boundaries of the power systems have gradually blurred, so that the power security protection measures urgently need to be updated. Aiming at the smart micro-grid system based on edge computing, this paper introduc...
Contexts in source publication
Context 1
... is a small power distribution system that combines distributed power sources, energy storage devices, inverters, related loads and protection devices. Figure 1 is an energy storage-photovoltaic-load topology diagram. The system consists of photovoltaic units, energy storage units, general loads and important loads. ...
Context 2
... risks will lead to abnormal activities of the terminal's feedback data [13], allowing the micro-grid central controller to collect wrong information and then make wrong decision-making activities, causing the local or even the entire system of the micro-grid to collapse [14]. In response to this problem, we designed an edge computing module based on NILM for malicious activities detection, and placed it at the same level as the microgrid central controller shown in Figure 1. The edge computing module has the functions of online judgment and instant feedback, which helps to improve the safety performance of the entire system. ...
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Citations
... With the massive access of a large number of distributed energy sources and terminals containing power electronic equipment, the terminal equipment in the smart energy system is vulnerable to permission attacks, data storage and encryption attacks, vulnerability threats, and remote control (Lei et al., 2020). These risks will lead to abnormal activities of the terminal's feedback data, allowing the micro-grid central controller to collect wrong information and then make wrong decisionmaking activities, causing the local or even the entire system of the micro-grid to collapse (Komninos et al., 2014;Lei et al., 2020). ...
... With the massive access of a large number of distributed energy sources and terminals containing power electronic equipment, the terminal equipment in the smart energy system is vulnerable to permission attacks, data storage and encryption attacks, vulnerability threats, and remote control (Lei et al., 2020). These risks will lead to abnormal activities of the terminal's feedback data, allowing the micro-grid central controller to collect wrong information and then make wrong decisionmaking activities, causing the local or even the entire system of the micro-grid to collapse (Komninos et al., 2014;Lei et al., 2020). In order to monitor malicious behaviors of users online in real time, the smart energy system uses the microgrid central controller, distributed energy grid-connected interface devices, and charging piles, as edge computing modules to form an edge computing platform. ...
The Edge computing paradigm has been increasingly well-liked in academic and business circles in recent years. By linking cloud computing facilities and services to end users, it acts as a major enabler for numerous upcoming technologies, including 5G, the Internet of Things (IoT), augmented reality, and vehicle-to-vehicle communications. Applications that are sensitive to delays can benefit from low latency, mobility, and location awareness offered by the Edge computing paradigm. Considerable investigation has been conducted in the field of edge computing, which is examined in light of recent advancements including fog computing, cloudlet, and mobile edge computing. resulting in providing researchers with more insight into the existing solutions and future applications. This article is meant to serve as a comprehensive survey of recent advancements in Edge computing highlighting the core applications. It also discusses the importance of Edge computing in real life scenarios where response time constitutes the fundamental requirement for many applications. The article concludes with identifying the requirements and discuss open research challenges in Edge computing.
... With the massive access of a large number of distributed energy sources and terminals containing power electronic equipment, the terminal equipment in the smart energy system is vulnerable to permission attacks, data storage and encryption attacks, vulnerability threats, and remote control (Lei et al., 2020). These risks will lead to abnormal activities of the terminal's feedback data, allowing the micro-grid central controller to collect wrong information and then make wrong decisionmaking activities, causing the local or even the entire system of the micro-grid to collapse (Komninos et al., 2014;Lei et al., 2020). ...
... With the massive access of a large number of distributed energy sources and terminals containing power electronic equipment, the terminal equipment in the smart energy system is vulnerable to permission attacks, data storage and encryption attacks, vulnerability threats, and remote control (Lei et al., 2020). These risks will lead to abnormal activities of the terminal's feedback data, allowing the micro-grid central controller to collect wrong information and then make wrong decisionmaking activities, causing the local or even the entire system of the micro-grid to collapse (Komninos et al., 2014;Lei et al., 2020). In order to monitor malicious behaviors of users online in real time, the smart energy system uses the microgrid central controller, distributed energy grid-connected interface devices, and charging piles, as edge computing modules to form an edge computing platform. ...
The Ubiquitous Power Internet of Things (UPIoT) is a concrete manifestation of the Internet of things (IoT) in the power industry, which is a deep integration of the interconnected power network and communication network, realizing full perception of the system status and full business penetration in all links of power production, transmission, and consumption. The introduction of edge computing in UPIoT fully meets the requirements of rapid response, real-time perception, and to some extent, privacy protection. However, there is currently no comprehensive investigation on the application of edge computing technology in UPIoT. First, this paper introduces the development background and construction of UPIoT and its technical architecture. Then the challenges faced by UPIoT in the process of construction are analyzed. Furthermore, the paper elaborates on the functions and features of edge computing, proposes that the support of edge computing technology can solve the challenges of efficient, fast, and secure processing of massive edge data faced by the traditional cloud-based centralized big data processing technology of UPIoT, and analyzes the architecture of the edge computing-assisted UPIoT. For the three typical scenarios of UPIoT, namely power monitoring system, smart energy system and power metering system, the edge computing architecture of the three scenarios are analyzed, and the specific application methods and roles played by edge computing in the three scenarios are also elaborated. Finally, we discuss the challenges of edge computing in UPIoT, in terms of policy challenges, market challenges, and technical challenges, as well as outline the outlooks of the technical challenges.
