Loooseless encodings and compression algorithms applied on power quality datasets

In this paper we are presenting behaviour of various encodings and lossless compression methods for data stores of power quality measuring campaigns and the achieved results with different generated and real datasets. The main purpose of this work is to ease the selection of an optimal encoding for a typical power quality data in the measuring device. The most important criteria for selecting of an optimal method are a compression ratio, its stability, reliability and fitness of such algorithm for an embedded platform with limited memory and computational power. The implemented benchmarking system is designed to be modular so that each part of it can be separately modified or completely replaced while still the whole system is delivering comparable results. Our target platforms are a resource limited, micro-controller based devices so the most attention was paid to choose an algorithm performing sufficiently with reasonable requirements. The experiments have been performed on different artificial and real data from our measuring campaigns.