Owing to very rapid growth in electronics and technology, it has become very essential to maintain power quality at the consumer end. Since power quality has vast no of assets, mainly important and frequently occurring disturbances are considered in this paper. Power quality is mainly defined by disturbances associated with voltage. However, the voltage disturbances can be classified based on t...

Identification and classification ofvoltage and current disturbances in power systems is an important task in power system monitoring and protection. Most power quality disturbances are non-stationary and transitory and the detection and classification have proved to be very demanding. New intelligent system technologies using wavelet transform, expert systems and artificial neural networks pro...

This paper presents the application of Hilbert transform and artificial neural network (ANN) for power quality (PQ) disturbance classification. The input features of the ANN are extracted from the envelope of the disturbance signals by applying Hilbert transform (HT). The features obtained from the Hilbert transform are distinct, understandable and immune to noise. These features after normaliz...

Power quality monitoring has advanced to an important tool for system evaluation. The increased amount of recorded data requires more sophisticated analysis methods. The paper describes the development and operation of a system for automated classification of power quality events. Different to existing approaches the proposed system introduces a new frame-based event model similar to speech mod...

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...

By using the optimum-interval interpolation estimation, in this paper, a new composite model which is based on the improved second generation wavelet transform and second order nonhomogeneous Hidden Markov Model(ISGWT-SNHMM) is proposed and applied in the power quality disturbance classification. By adopting the interpolating scheme and the optimum-interval interpolation estimation, the predict...

Power Quality is defined as the study of the quality of electric power lines. The detection and classification of the different disturbances which cause power quality problems is a difficult task which requires a high level of engineering expertise. Thus, neural networks are usually a good choice for the detection and classification of these disturbances. This paper describes a powerful tool, d...

In this paper, a SVM classifier based on S-Transform is presented for power quality disturbances classification. Firstly, seven types of PQ events are created using Matlab simulation. These signals are analyzed to detect and localize PQ events via S-Transform by visual inspection. Then five significant features of the PQ disturbances are extracted from the S-Transform output. Afterwards, PQ dis...

Nowerdays, due to the penetration of power electronics based loads and microprocessor based controlled loads. We have to give more importance to power Quality problems. In order to improve the power quality, the sources of power quality disturbances should be recognized and classified earlier. So many techniques are proposed so far in many research papers under feature extraction and classifica...

The use of sensitive electronic equipments is on the rise lately and power quality studies have progressed a lot. Detection and classification of power quality signals is of greater importance both in case of Power quality studies and denoising. This paper proposes a detection and classification technique for several power quality disturbances, by introspecting the energy of the distorted signa...