Classification of Power Quality Problems by Wavelet Fuzzy Expert System

Abstract

Electric power quality, which is a current interest to several power utilities all over the world, is often severely affected by harmonics and transient disturbances. There is no unique model which can assess the power quality problem and to identify and classify them properly. Existing automatic recognition methods need improvement in terms of their versatility, reliability, and accuracy. The FUZZY LOGIC based tools have been applied for the PQ classification. This paper addresses Power quality problem classification by wavelet and fuzzy expert system. Major Key issues and challenges related to these advanced techniques in automatic classification of PQ problems are highlighted. New intelligent system technologies using DSP, expert systems, AI and machine learning provide some unique advantages in intelligent classification of PQ distortions.

Power Quality Assessment of Perturbed Power System Implementing Fuzzy Logic and Discrete Wavelet Transform

“…The fuzzy logic is used as a tool to classify power quality problems. New intelligent system technologies using DSP,AI [5]and machine learning which have some unique advantage in classifying power quality distortion. In this paper the author describes that wavelet can be applied to identify the required amount of balancing capacity by observing the time varying nature of dominant frequency [12] which remain present in power signal and power system generation must match with the load.…”