An introduction to wavelet synopses of electric power system measurements

The measurement and logging of values related to electric power at numerous different locations of a given system in sampling times ranging from the length of some seconds up to a few hours and the following transfer of the aforementioned data from the collection points to the participants of the energy market for central control and assessment (on various periodical bases), renders the ability to compress the data at hand in order for the transfer to be executed in a fast and consistent manner crucial, setting as ultimate goal the significant validity of the control decisions and other various related assessments extracted from the collected data. Taking into account the nature of the queries posed and the data used to answer them, a pair of known techniques of wavelet synopsis on time series will be tested: firstly the Garofalakis-Kumar and secondly the Selection of the Top-k Elements of the Haar Transformation. Following, tests are executed on both real data and data generated from power system simulation software. More specifically, time-series of data concerning the load-curve of a day, the level of a tap changer in a window of a few hours and the status of a switch after numerous errors will be compressed and restructured based on relative tolerances defined by error metrics set according to the input values. The required content for a valid reconstruction of the initial timeseries will be evaluated and some further suggestions will be given for future research in the specific field.