A cumulative standard deviation sum based method for high resistance fault identification and classification in power transmission lines

High resistance fault poses an enormous challenge to the existing algorithms of fault detection and fault classification.In this paper,the standard deviation and accumulation method are employed to perform the fault detection and classification.It is primarily built in two stages.Firstly,the standard deviations for the measured current’s signals of the local and remote terminals is computed to extract the fault feature.Secondly,the cumulative approach is used to enlarge the fault feature to perform the high resistance fault.The proposed scheme is known as Standard Deviation Index(SDI),and it is obtained for the three phases and zero sequence.The proposed algorithm has been tested through different fault circumstances such as multiple faults locations,fault resistances,and fault inception time.Moreover,far-end faults with high-resistance,faults happened nearby the terminal,faults considering variable loading angle,sudden load change,different sampling frequency,bad signaling and a fault occurred in the presence of series compensation are also discussed.The results show that the proposed scheme performed remarkably well regarding the fault with resistance up to 1.5kΩand can be detected within a millisecond after the fault inception.Additionally,the computational simplicity that characterizes the processes makes it more efficient and suitable for domain applications.

Single-phase-to-ground Fault Detection with Distributed Parameters Analysis in Non-direct Grounded Systems

The fast and accurate detection of the single-phaseto-ground fault is of great significance for the reliability and safety of the power supply.In this paper,novel algorithms for distribution network protection were proposed with distributed parameters analysis in non-direct grounded systems.At first,novel generating mechanisms of zero-sequence voltage and residual current were proposed.Then the compositions of residue parameters,including residual current and residual admittances,were decomposed in detail.After that,an improved algorithm for a fault resistance calculation of a single phase-to-earth fault was also proposed,and the algorithm is much more convenient as it only needs to measure the variation of the zero-sequence voltage and does not need the prerequisites of the faulty feeder selection.Furthermore,the fault feeder can also be selected by an improved calculation algorithm of zero-sequence admittance of the faulty feeder,which cannot be affected by the asymmetry of the network.Theoretical analysis and the MATALB/Simulink simulation results demonstrate the effectiveness of the proposed algorithms.

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

This paper presents fault detection,classification,and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINK platform.Initially,DC fault signals are collected from local measurements to examine the outcomes of the proposed system.Accurate detection is carried out for all faults,(i.e.,cable and arc faults)under two cases of fault resistance and distance variation,with the assistance of primary and secondary detection techniques,i.e.second-order differential current derivatived2I3 dt2and sliding mode window-based Pearson’s correlation coefficient.For fault classification a novel approach using modified multifractal detrended fluctuation analysis(M-MFDFA)is presented.The advantage of this method is its ability to estimate the local trends of any order polynomial function with the help of polynomial and trigonometric functions.It also doesn’t require any signal processing algorithm for decomposition resulting and this results in a reduction of computational burden.The detected fault signals are directly passed through the M-MFDFA classifier for fault type classification.To enhance the performance of the proposed classifier,statistical data is obtained from the M-MFDFA feature vectors,and the obtained data is plotted in 2-D and 3-D scatter plots for better visualization.Accurate fault distance estimation is carried out for all types of faults in the DC ring bus microgrid with the assistance of recursive least squares with a forgetting factor(FF-RLS).To verify the performance and superiority of the proposed classifier,it is compared with existing classifiers in terms of features,classification accuracy(CA),and relative computational time(RCT).

A positive-sequence current based directional relaying approach for CCVT subsidence transient condition

In this work,a directional relaying algorithm is proposed for transmission line to prevent relay maloperation during coupling capacitor voltage transformer(CCVT)subsidence transient.The effect of CCVT subsidence transient during single-pole-tripping condition is highlighted in this paper.The proposed method which is based on phase angle difference of post fault and prefault positive sequence current can help the directional relay to take accurate decision during erroneous CCVT secondary response.The available CCVT model in PSCAD is not able to generate significant subsidence transient in the secondary side.So,a new CCVT model is developed in EMTDC/PSCAD domain for transient response analysis and to check the relay operation.Next,the performance of different voltage and current information based directional relaying techniques have been analyzed and compared with the proposed method.The results are evaluated for different system and fault conditions.Results demonstrate the accuracy of the proposed method.