Open AccessCompression Techniques of Electrical Energy Data for Load Monitoring: A Review
Author(s) -
F.M. Dahunsi,
O. A. Somefun,
A.A. Ponnle,
K.B. Adedeji
Publication year - 2021
Publication title -
nigerian journal of technological development
Language(s) - English
Resource type - Journals
ISSN - 2437-2110
DOI - 10.4314/njtd.v18i3.4
Subject(s) - lossless compression , computer science , data compression , lossy compression , context (archaeology) , smart grid , real time computing , efficient energy use , reliability engineering , engineering , electrical engineering , artificial intelligence , paleontology , biology
In recent years, the electric grid has experienced increasing deployment, use, and integration of smart meters and energy monitors. These devices transmit big time-series load data representing consumed electrical energy for load monitoring. However, load monitoring presents reactive issues concerning efficient processing, transmission, and storage. To promote improved efficiency and sustainability of the smart grid, one approach to manage this challenge is applying data-compression techniques. The subject of compressing electrical energy data (EED) has received quite an active interest in the past decade to date. However, a quick grasp of the range of appropriate compression techniques remains somewhat a bottleneck to researchers and developers starting in this domain. In this context, this paper reviews the compression techniques and methods (lossy and lossless) adopted for load monitoring. Selected top-performing compression techniques metrics were discussed, such as compression efficiency, low reconstruction error, and encoding-decoding speed. Additionally reviewed is the relation between electrical energy, data, and sound compression. This review will motivate further interest in developing standard codecs for the compression of electrical energy data that matches that of other domains.