Power quality evaluation in smart grids considering modern distortion in electric power systems

Abstract

High power quality level is required in smart grids especially for non-stationary situations due to increased use of nonlinear loads and PQ disturbances such as dips, swells, transients and interruptions. Many power quality indices (PQIs) are available. In this paper a new fuzzy-wavelet packet transform-based power quality Index (FWPTPQI) is developed to amalgamate existing power quality indices as the output of a fuzzy based module based on fuzzy inference systems, knowledge base and existing PQI as input. Fuzzy systems allow handling the uncertainties associated with the electric power quality evaluation. The proposed approach has been applied to two case studies; stationary balanced and non-stationary unbalanced three-phase systems. The results are compatible with prevalent situations. The new index gives significant sense of the quality of transmitted electrical power. A comparative study of using different wavelet basis functions is considered and results indicate that Daubechies 10 and Daubechies 15 could be considered as the overall best wavelet basis functions. Since the new index represents an amalgamation of the PQ indices with less number of wavelet coefficients, it helps reduce the size of data processed which is required in smart grid applications.