What is it about?
This paper describes a low computational algorithm threaded for compressing repetitive, slow varying data array to a character string of much reduced size. The performance of the algorithm was investigated with practical data sets associated with power system and an encouraging result was obtained. The real time testing of the algorithm establishes its importance in compressed data transfer as well.
Featured Image
Why is it important?
The available works on compressing power system operational data were based on lossless compression algorithms which require probability distribution information for decoding the information. This will limit the use of algorithm for data storage only. To overcome this drawback, investigations were carried out to develop a novel algorithm having the following features: (a) Reduced computation (b) High compression ratio for majority of data sets (c) Elimination of the need of probability distribution information so that compressed data transfer can be easier
Perspectives
It is expected that this article can be useful in many applications dealing with enormous volume of data sets. As simplicity of the algorithm enables its implementation at micro-controller level, realization of compressed DAS is also possible. The work can be useful for SCADA and health monitoring data acquisition as well. As grayscale images are often represented as integer values varing between 0 to 255, the proposed algorithm may be useful compression of such images containing containing repetitive pixel values.
SUBHRA JYOTI SARKAR
Jadavpur University
Read the Original
This page is a summary of: Development of Lossless Compression Algorithms for Power System Operational Data , IET Generation Transmission & Distribution, August 2018, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-gtd.2018.5600.
You can read the full text:
Contributors
The following have contributed to this page
