Wavelet data decomposition for (micro)grid phasor measurement unit systems

Data from Phasor Measurement Units (PMUs) and Phasor Data Concentrators (PDCs) are getting more common in power system operation. These data are currently utilized for real-time operation monitoring and offline analysis. This paper presents an intercommunication technique for efficient synchro-measurement data analysis. Both on-line and off-line data exploration are employed on the proposed wavelet coefficient decomposition. It provides a new approach to the analysis and interpretation of collected PDC/PMU data in a semantically interoperable manner. Τhe wavelet decomposition and synchro-measurement analytics can also been extended into the domain of microgrids. In this context, wavelet decomposition provides resilience by improving the detection of disturbances even from sparse measurements. Statistical characteristics obtained from wavelet coefficients such as energy concentration at specific scales or entropy measures, can serve as reliable indicators of unusual behavior. The experimental evaluation and the results presented in this study demonstrate that wavelet-based decomposition can extract rich feature sets from synchrophasor data, providing reliable detection of discontinuities, oscillations, and noise components. The proposed technique from a data standpoint found to be more efficient, selective and depicted for the study of control applications.