Detection and time localization of power quality events using orthogonal polynomial

This paper proposes a new and simple approach based on orthogonal polynomial approximation (OPA) to detect, localize, and investigate the feasibility of classification of various types of power quality disturbances. The key idea in this approach is to approximate a given disturbance signal in the least square sense, such that the uncorrelated part (disturbance) of the signal is not present in the approximated version of the signal. It is, therefore, possible to detect and localize power quality (PQ) disturbances by analyzing the difference of the original and approximated signals. This is achieved by choosing the degree of the polynomial using the criterion of minimum error-variance. The effectiveness of the proposed approach is tested and demonstrated to detect and localize PQ disturbances with simulated and actual power line disturbance data.