This effort focus at identifying statistically significant time/frequency domain features with adequate separability and extensive interclass variability to discriminate probable Power Quality (PQ) disturbances such as sag, swell, harmonics, outage, transients etc. Understanding of disturbances is vital to investigate the origin and causes of PQ perturbances, events of equipment failure and for...

Power quality (PQ) issue has attained considerable attention in the last decade due to large penetration of power electronics based loads and/or microprocessor based controlled loads. On one hand these devices introduce power quality problem and on other hand these mal-operate due to the induced power quality problems. PQ disturbances/events cover a broad frequency range with significantly diff...

Electrical power quality (PQ) disturbance has become an important issue in India. On a distribution network, it is mainly caused by various nonlinear loads. Due to the varying power produced, it is affected by penetration of solar PV system as well. Therefore it is necessary detect and classify PQ events in account of evaluating a PQ problem. In other side due to increase of smart meters in sma...

Researchers are exploring challenging techniques for the analysis of power quality signals for the detection of power quality (PQ) disturbances. PQ disturbances have become a serious problem for the end users and electric utilities. Numerous algorithms have been developed for the classification of unstructured data. In this paper, the classification of power quality signals are performed based ...

A multiple power quality (MPQ) disturbance has two or more (PQ) disturbances superimposed on a voltage signal. compact and robust technique is required to identify classify the MPQ disturbances. This manuscript investigated hybrid algorithm which designed using parallel processing of with stockwell transform (ST) hilbert (HT). will reduce computational time disturbances, makes fast. identificat...

Classifying power quality (PQ) disturbances is one of the most important issues for power quality control. A novel high-performance classification system based on the S-transform and a probabilistic neural network (PNN) is proposed. The original power quality signals are analysed by the S-transform and processed into a complex matrix named the S-matrix. Eighteen types of time–frequency features...

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 ...

This paper present the features extraction of the real time voltage signal performed by S-Transform analysis for the purpose of detection and classification of PQ disturbance, which focus on voltage sag, voltage swell and transient. The extracted features will be used as a parameter in detecting and classifying the single and multiple PQ disturbances. As for validation purpose, the real time S-...

This paper presents the combination of advanced signal processing techniques and the machine intelligence approach to classify the power quality events. The Wavelet Transform (WT) and the S – Transform (ST) are utilized to extract the important useful features of the disturbance signal. The features extracted by using the above approaches are used to train a PNN classifier for automatic classif...

Concern towards power quality (PQ) has increased immensely due to the growing usage of high technology devices which are very sensitive towards voltage and current variations and the de-regulation of the electricity market. The impact of these voltage and current variations can lead to devices malfunction and production stoppages which lead to huge financial loss for the production company. The...