A Novel Approach to Power Quality Analysis: Adaptive FEM Algorithm with Sparse Signal Decomposition

Abstract

An adaptive approach of discretized triangular mesh based on finite element method hybrid with type‐2 fuzzy is utilized for detection and classification of power quality events. The concept of sparse signal decomposition is utilized with extraction of disturbances from power signals. An adaptive finite element method is then applied with the concept of stiffness matrix which extracts some relevant features of power quality events that act as input to type‐2 fuzzy classifiers. Finally performance comparison is carried out, the results of which show that the proposed technique has potential to analyze disturbances with high accuracy and minimum computational overhead.

Review of Signal Processing Techniques and Machine Learning Algorithms for Power Quality Analysis

“…A new method of adaptive FEM has been reported in ref. [171] for power quality events analysis with the help of sparse signal decomposition. The proposed method achieved high accuracy but computational overhead is large.…”