Wavelet transform has received great attention in power community in the last years, because are better suited for the analysis of certain types of transient waveforms than the other transforms approach. This paper presents a descriptive overview of the wavelet transform applications in power systems. The main publications carried out in this field have been analyzed and classified by areas. A list of 116 references is also provided.

/pdf/an-overview-of-wavelet-transforms-application-in-power-5apalk6m24.pdf

An overview of wavelet transforms application in power systems

This paper proposes a neuro-fuzzy based methodology for power system dynamic security assessment, focusing on transient stability. The proposed method utilizes a concurrent neuro-fuzzy system based on dynamic performance indices calculation. An Artificial Neural Network (ANN) is trained to determine the performance indices, which allow the classification of the operative system state security. The ANN inputs are composed by signals that indicate the disturbance severity and its ability to reestablish an acceptable equilibrium point. A diagnosis fuzzy is applied to the ANN result in order to classify the security state and to indicate the necessity of detailed analysis in doubtful situations. In this way, only doubtful classifications will require full time-domain simulations, which is a very time consuming task. The proposed methodology was applied to a test system that represents part of the South region of the Brazilian electric system. The results have shown the potential benefits of the proposed scheme. is arising. This paper proposes a methodology for power systems dynamic security assessment focusing on transient stability. The proposed method uses a concurrent neuro-fuzzy system based on dynamic performance indices calculation. An Artificial Neural Network (ANN) is trained to estimate the performance indices, allowing the classification of the operative status of the system. A fuzzy diagnosis is applied to the ANN output to indicate the necessity of detailed analysis in doubtful situations. The paper is organized as follows. Section II exposes an overview of the power system transient stability problem. Section III presents a brief description of the intelligent techniques used in this work. The proposed methodology is depicted in Section IV and Section V presents the obtained results. The conclusions are addressed in Section VI.

Power System Dynamic Security Assessment through a Neuro-Fuzzy Scheme

This paper proposes a protection scheme for turbo generators to detect stator ground faults in particular closer to neutral. The scheme considers total generated voltage of the machine and makes use of Wavelet Multi Resolution Analysis. A Fault Index is defined in terms of peak and valley values of the highest-level wavelet decomposition, which is compared with a threshold value to discriminate from other transients like sudden unbalance in load. The results of digital simulation are presented for different fault impedances and fault locations.

A new Wavelet based ground fault protection scheme for turbo generators

This article proposes a protection scheme for turbo generators to detect stator ground faults in particular closer to neutral. The scheme considers total generated voltage of the machine and makes use of wavelet multi-resolution analysis. A fault index is defined in terms of peak and valley values of the highest-level wavelet decomposition, which is compared with a threshold value to discriminate from other transients, like sudden unbalance, in load. To identify the faulty coil, an ANN employing back propagation algorithm is used with the lowest level wavelet coefficients as inputs. The results of digital simulation are presented for different fault impedances and fault locations.

Wavelet ANN Based Stator Ground Fault Protection Scheme for Turbo Generators

The frequency property of wavelet transformation (WT) has been studied in depth in this paper with comparison to the discrete Fourier transform (DFT). The band overlapping and frequency leakage among different scales of WT is discussed. Several new wavelet functions with compact-supported property in frequency domain are constructed. A general process for selecting proper wavelet function according to practical requirements is proposed. A novel WT based method is developed to detect generator inner faults. Comparing with the DFT method, the WT based signal analysis requires no frequency tracking and is not affected by frequency deviation. No leakage of frequency occurs with the new method applied. Simulation results prove the feasibility and advantages of the new method presented by the paper.

A novel method for large turbine generator protection based on wavelet transformation

A novel multi-layer TSA scheme is presented in this paper to tackle the fast transient stability assessment (TSA) problem for large-scale power systems. A sample-based correlation algorithm is proposed for screening the input attributes. Identification of the critical clustering and estimation of the stability level and CCT based on fuzzy reasoning are realized. Simulation tests confirm the feasibility and advantages of the proposed method.

http://ieeexplore.ieee.org/iel5/7546/20550/00950382.pdf

L. Guan

Papers

A novel method for large turbine generator protection based on wavelet transformation

A real-time transient stability assessment scheme for large-scale power systems based on fuzzy reasoning