Nonintrusive Load Management Based on Distributed Edge and Secure Key Agreement

Abstract

With the advancement of national policies and the rise of Internet of things (IoT) technology, smart meters, smart home appliances, and other energy monitoring systems continue to appear, but due to the fixed application scenarios, it is difficult to apply to different equipment monitoring. At the same time, the limited computing resources of sensing devices make it difficult to guarantee the security in the transmission process. In order to help users better understand the energy consumption of different devices in different scenarios, we designed a nonintrusive load management based on distributed edge and secure key agreement, which uses narrowband Internet of things (NB-IoT) for transmission and uses edge devices to forward node data to provide real-time power monitoring for users. At the same time, we measured the changes of server power under different behaviors to prepare for further analysis of the relationship between server operating state and energy consumption.

A spatio‐temporal graph convolutional approach to real‐time load forecasting in an edge‐enabled distributed Internet of Smart Grids energy system

“…Under the background of the various power acquisition equipment and the rapid development of the Internet of Smart Grids (IoSG), Intelligent equipment is gradually used for load data RT acquisition at various power consumption sides 1–5 . The popularity of smart sockets creates favorable conditions for using edge computing when processing and analyzing a large number of power load data 6,7 . Since the end of the epidemic, the society has resumed business and production, and the load power consumption of the whole society has increased sharply.…”

“…[1][2][3][4][5] The popularity of smart sockets creates favorable conditions for using edge computing when processing and analyzing a large number of power load data. 6,7 Since the end of the epidemic, the society has resumed business and production, and the load power consumption of the whole society has increased sharply. At present, few companies embed efficient AI algorithms in the products of the power industry.…”