Fuzzy-wavelet-based electric power quality assessment of distribution systems under stationary and nonstationary disturbances

Evaluating the electric power quality become very important task due to the widespread use of nonlinear loads, distributed generations, renewable energy sources and the economic impact of poor power quality. In deregulated environment, having different power quality indices (PQIs) with different values has no significance unless they are combined into single value that could represent them. In this paper, a new fuzzy-wavelet packet transform based power quality index is introduced that amalgamated the recommended power quality indices after being redefined in the time-frequency domain using the wavelet packet transform in order to be compatible with nonstationary disturbances. The use of fuzzy systems is required in order to handle the uncertainties that are associated with the electric power system operation. In order to study the effect of wavelet filter length and the choice of the best wavelet basis function, the new fuzzy developed modules along with the reformulated PQIs are used in three case studies considering electric arc furnace load supplied from stationary low distorted voltage, stationary high distorted voltage and nonstationary distorted voltage (voltage dip). The results indicates the sensitivity of the new index to any change in the electric power quality and the comparative study shows that the most suitable wavelet basis to be used with this module is db 10 since it could provide the most accurate result while processing less number of the filter coefficients therefore reducing the computational time and reducing the size of the memory required. The new index could be efficient in deciding the most appropriate PQ mitigation technique, evaluating the influence of distributed resources on the electric power network while providing a fair strategy for billing the consumers especially those generating time varying harmonics.