Multiresolution matrix factorisation as a compression method for smart meter data

Abstract

The development of a smart grid electricity distribution network with advanced technology in smart metering will produce a massive amount of data. However, the limitation in communication network bandwidth makes it hard to transmit these data to the control center. Data compression is one of the best solutions to overcome this limitation. This study presents the use of multiresolution matrix factorisation (MMF) as a data compression technique for a smart distribution system. MMF will compress a data matrix into a core matrix with lower dimension via a series of orthogonal transformations. Experimental results gained from this study show that MMF is applicable in compressing large size data into lower dimension matrix with low error rates and high in speed. The MMF compression technique is able to reduce the volume of data to be transmitted through the communication network and thus save the bandwidth. Besides, MMF compression performs faster than the singular value decomposition method, especially with large size matrix. Findings from this study prove that MMF can serve as an alternative data compression technique for the smart distribution system, with a potential for an online application due to the high speed and high accuracy of the algorithm.

Keywords

• matrix decomposition
• smart power grids
• data compression
• smart meters
• singular value decomposition
• distribution networks
• image coding
• alternative data compression technique
• size matrix
• singular value decomposition method
• mmf compression performs
• mmf compression technique
• lower dimension matrix
• size data
• core matrix
• data matrix
• smart distribution system
• control center
• communication network bandwidth
• smart metering
• smart grid electricity distribution network
• smart meter data
• compression method
• multiresolution matrix factorisation