Modified Differential Golomb Arithmetic Lossless Compression Algorithm for Smart Grid Applications

The advancement of the electric grid has led to tremendous growth in data generated from the installed sensors. Efficient storage and transmission of this data pose a challenge for the utilities. Thus, it is required to have a data compression technique to reduce the data size. There are state of the art compression algorithms that can be applied to reduce the amount of data for storage and transmission in the smart grid environment. Some of these algorithms exploit characteristics of the load profile data, where consecutive data samples have very small differences. However, performance of these algorithms deteriorate when there are frequent large differences. We propose a modification that improves compression performance when there are large value differences. The algorithm is evaluated on smart meter load profile data at different data resolution. We show that the proposed changes improve performance by 2−20% for different resolutions.