A survey of intelligent load monitoring in IoT-enabled distributed smart grids

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Jixiang Gan, Lei Zeng, Qi Liu, Xiaodong Liu
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引用次数: 1

Abstract

Power load monitoring has been a research hotspot since a few years ago. With development of artificial intelligence, construction of smart grid has become the most important part of power load monitoring. At the same time, task scheduling mechanism combined with the distributed internet of things (IoT) improves efficiency of smart grid. In this paper, applications of cloud/edge platform in the data acquisition, processing and scheduling of the IoT is introduced step by step, as well as applications and differences of artificial intelligence algorithm in each step, including data acquisition, load disaggregation, load forecasting and so on. Finally, combined with various optimisation methods, future research directions are prospected, including data and network security issues, and challenges faced by cloud/edge architecture, adaptive fine-grained load disaggregation, and load forecasting.
基于物联网的分布式智能电网智能负荷监测研究
近年来,电力负荷监测一直是一个研究热点。随着人工智能的发展,智能电网的建设已成为电力负荷监测的重要组成部分。同时,与分布式物联网相结合的任务调度机制提高了智能电网的效率。本文逐步介绍了云/边缘平台在物联网数据采集、处理和调度中的应用,以及人工智能算法在数据采集、负荷分解、负荷预测等各个步骤中的应用和差异。最后,结合各种优化方法,展望了未来的研究方向,包括数据和网络安全问题,以及云/边缘架构、自适应细粒度负载分解和负载预测面临的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.00
自引率
0.00%
发文量
69
审稿时长
7 months
期刊介绍: IJAHUC publishes papers that address networking or computing problems in the context of mobile and wireless ad hoc networks, wireless sensor networks, ad hoc computing systems, and ubiquitous computing systems.
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