An EMD Based Protection Scheme for Distribution System

Abstract: The aim of this paper is to develop a method based on combination of Empirical Mode Decomposition (EMD) and Hilbert Transform for assessment of power quality events. A distorted waveform can be conceived as superimposition of various oscillating modes and EMD is used to separate out these intrinsic modes known as intrinsic mode functions (IMF). Hilbert transform is applied to first three IMF to obtain instantaneous amplitude and phase which are then used for constructing feature vector. The work evaluates the detection capability of the methodology and a comparison with S-Transform is made to show the superiority of the technique in detecting the PQ disturbance like voltage spike and notch. A Probabilistic Neural Network is used as a mapping function for identifying the various disturbance classes. Results show a better classification accuracy of the methodology.

Abstract: This article presents a fault identification technique that makes use of the empirical mode decomposition of three-phase current signals of a distribution network. The current signals measured at the substation bus over a moving window are decomposed to obtain the first-level intrinsic mode function and residue. The standard deviation of the first-level residue is calculated as a fault index for each phase and compared with a threshold to detect and categorize the type of fault. A ground fault index based on the average value of the first-level residue of the neutral current is proposed to discriminate the phase–phase and phase–phase–ground faults. The proposed algorithm has been successfully tested on the IEEE 13 bus and 34 bus distribution systems in the presence of the solar photovoltaic power plant by varying the type of fault, fault incidence angle, and fault location in the presence of noise. The selectivity of the proposed algorithm has been established by testing the algorithm with nonfaulty transients such as transformer excitation and deexcitation, feeder energization and deenergization, load switching, capacitor switching, and also those associated with distributed generation (DG) penetration like islanding and tripping of DG. Subsequently, the residue-based features are fed to a decision tree to locate the faults on the distribution system. Thus, the proposed algorithm has been successful in detecting, classifying, and locating faults with DG penetration in the presence of noise within half cycle by utilizing only current signals.

Abstract: A high impedance fault (HIF) is characterized by a small, nonlinear, random, unstable, and widely varying fault current in a power distribution system. HIFs draw very low fault currents, and hence are not always effectively cleared by conventional overcurrent relays. Various schemes are proposed to detect such faults. This paper presents a method to detect HIFs using a tool based on mathematical morphology (MM). The method is implemented alongside the conventional overcurrent relay at the substation to improve the performance of this relay in detecting HIFs. It is rigorously tested on standard test systems using PSCAD/EMTDC® to generate test waveforms, and Matlab® to implement the method. Simulation results show that the proposed method is fast, secure, and dependable.

Abstract: The study presents a differential scheme for microgrid protection using time-frequency transform such as S-transform Initially, the current at the respective buses are retrieved and processed through S-transform to generate time-frequency contours Spectral energy content of the time-frequency contours of the fault current signals are calculated and differential energy is computed to register the fault patterns in the microgrid at grid-connected and islanded mode The proposed scheme is tested for different shunt faults (symmetrical and unsymmetrical) and high-impedance faults in the microgrid with radial and loop structure It is observed that a set threshold on the differential energy can issue the tripping signal for effective protection measure within four cycles from the fault inception The results based on extensive study indicate that the differential energy-based protection scheme can reliably protect the microgrid against different fault situations and thus, is a potential candidate for wide area protection

Abstract: An intelligent approach for high impedance fault (HIF) detection in power distribution feeders using advanced signal-processing techniques such as time-time and time-frequency transforms combined with neural network is presented. As the detection of HIFs is generally difficult by the conventional over-current relays, both time and frequency information are required to be extracted to detect and classify HIF from no fault (NF). In the proposed approach, S- and TT-transforms are used to extract time-frequency and time-time distributions of the HIF and NF signals, respectively. The features extracted using S- and TT-transforms are used to train and test the probabilistic neural network (PNN) for an accurate classification of HIF from NF. A qualitative comparison is made between the HIF classification results obtained from feed forward neural network and PNN with same features as inputs. As the combined signal-processing techniques and PNN take one cycle for HIF identification from the fault inception, the proposed approach was found to be the most suitable for HIF classification in power distribution networks with wide variations in operating conditions.

Abstract: Time-frequency-based differential scheme is proposed for microgrid protection using non-stationary signal analysis. The non-stationary signal processing algorithm Hilbert-Huang Transform (HHT) have been implemented for the protection objective and the comparative assessment with that of S-transform, differential current is carried out in order to demonstrate the reliability of the proposed protection scheme with different case studies. The series of simulation results demonstrates the efficacy of HHT, than that of S-transform in some critical cases such as high impedance fault where accurate detection is a challenge. The configuration of the microgrid test model has been developed in PSCAD with different distributed generation such as photovoltaic and wind generation system penetrated at different buses. Thus, it is found that the HHT scheme is quite reliable and efficient for fault detection objective.

Abstract: The distribution static compensator (DSTATCOM) provides fast control of active and reactive powers to enable load compensation, harmonics current elimination, voltage flicker mitigation, voltage and frequency regulation. This paper presents power quality improvement technique in the presence of grid disturbances and wind energy penetration using DSTATCOM with battery energy storage system. DSTATCOM control is provided based on synchronous reference frame theory. A modified IEEE 13 bus test feeder with DSTATCOM and wind generator is used for the study. Power quality events during grid disturbances such as feeder tripping and re-closing, voltage sag, swell and load switching have been studied in association with DSTATCOM. The power quality disturbances due to wind generator outage, synchronization and wind speed variations have also been investigated. The study has been carried out using MATLAB/SIMULINK and the simulation results are compared with real time results obtained by the use of real time digital simulator (RTDS) for validating the effectiveness of proposed methodology. The proposed method has been proved to be effective in improvement of power quality with all disturbances stated above.