Open AccessTimeliness Study of Home Energy Management System Based on Dynamic Allocation of Bandwidth
Author(s) -
Wei Zhang,
ChenHao Huang
Publication year - 2024
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2024.3381624
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Household electrical appliances have developed into a significant part of demand response as a result of the widespread use of smart meters and the popularity of home energy management systems. Load-side resources will still be wasted as a result of the transmission and queuing delays brought on by insufficient communication resources. To address the difficulties of large-scale, decentralized, and dispatchable household electricity load engaging in demand response, this study presents an approach to enhance the timeliness of dispatchable resources in home energy management systems, which may be separated into two categories. The most effective approach to allocate bandwidth is determined in the first section using historical bandwidth demand data and ARIMA models. The second section, meanwhile, makes use of offloading strategies and the cloud edge cooperation architecture to decrease queuing delays brought on by computational workloads. The results demonstrate that the suggested strategy can effectively reduce the time needed for information transmission and queuing, as well as alleviate the information interaction time between supply and demand. The timeliness of the proposed strategy is evaluated based on the number, value, transmission delay, and queuing delay of schedulable loads at each node.