Subhransu Ranjan Samantaray

Bio: Subhransu Ranjan Samantaray is an academic researcher from Indian Institute of Technology Bhubaneswar. The author has contributed to research in topics: Fault (power engineering) & Phasor. The author has an hindex of 39, co-authored 167 publications receiving 4880 citations. Previous affiliations of Subhransu Ranjan Samantaray include Indian Institutes of Technology & Siksha O Anusandhan University.

Fault Classification and Section Identification of an Advanced Series-Compensated Transmission Line Using Support Vector Machine

Abstract: Distance protection of flexible ac transmission lines, including the thyristor-controlled series compensator (TCSC), static synchronous compensator, and static var compensator has been a very challenging task. This paper presents a new approach for the protection of TCSC line using a support vector machine (SVM). The proposed method uses postfault current samples for half cycle (ten samples) from the inception of the fault and firing angle as inputs to the SVM. Three SVMs are trained to provide fault classification, ground detection, and section identification, respectively, for the line using TCSC. The SVMs are trained with polynomial kernel and Gaussian kernel with different parameter values to get the most optimized classifier. The proposed method converges very fast with fewer numbers of training samples compared to neural-network and neuro-fuzzy systems which indicates fastness and accuracy of the proposed method for protection of the transmission line with TCSC

A Combined Wavelet and Data-Mining Based Intelligent Protection Scheme for Microgrid

Abstract: This paper presents an intelligent protection scheme for microgrid using combined wavelet transform and decision tree. The process starts at retrieving current signals at the relaying point and preprocessing through wavelet transform to derive effective features such as change in energy, entropy, and standard deviation using wavelet coefficients. Once the features are extracted against faulted and unfaulted situations for each-phase, the data set is built to train the decision tree (DT), which is validated on the unseen data set for fault detection in the microgrid. Further, the fault classification task is carried out by including the wavelet based features derived from sequence components along with the features derived from the current signals. The new data set is used to build the DT for fault detection and classification. Both the DTs are extensively tested on a large data set of 3860 samples and the test results indicate that the proposed relaying scheme can effectively protect the microgrid against faulty situations, including wide variations in operating conditions.

Data-Mining Model Based Intelligent Differential Microgrid Protection Scheme

Abstract: This paper presents a data-mining-based intelligent differential protection scheme for the microgrid. The proposed scheme preprocesses the faulted current and voltage signals using discrete Fourier transform and estimates the most affected sensitive features at both ends of the respective feeder. Furthermore, differential features are computed from the corresponding features at both ends of the feeder and are used to build the decision tree-based data-mining model for registering the final relaying decision. The proposed scheme is extensively validated for fault situations in the standard IEC microgrid model with wide variations in operating parameters for radial and mesh topology in grid-connected and islanded modes of operation. The extensive test results indicate that the proposed intelligent differential relaying scheme can be highly reliable in providing an effective protection measure for safe and secured microgrid operation.

Variational Mode Decomposition and Decision Tree Based Detection and Classification of Power Quality Disturbances in Grid-Connected Distributed Generation System

Abstract: This paper presents a variational mode decomposition (VMD) and decision tree based detection and classification method of single and mixed power quality (PQ) disturbances in grid-connected distributed generation system. Applicability of VMD technique is investigated for discrimination of stationary PQ disturbances (such as harmonics, interharmonics, and flicker), non-stationary events (e.g., transients) and noise. Studies indicate usefulness of VMD for accurate estimation of phasor quantities such as amplitude, phase angle, and frequency and other describing features. Features namely, mode central frequencies, relative mode energy ratios, zero crossings, and instantaneous amplitude (IA) are extracted for classification of single and mixed PQ disturbances using a decision tree algorithm. A set of synthetic test signals, disturbance signals obtained from real events as well as signals generated from real time digital simulator platform are used to test effectiveness of proposed method, under various system operating scenarios and noise levels. Proposed method is found to be capable of accurate detection, estimation, localization, and classification of all kinds of PQ disturbances in both noisy and noise-free cases.

Detection and Classification of Power Quality Disturbances Using Sparse Signal Decomposition on Hybrid Dictionaries

Abstract: Several methods have been proposed for detection and classification of power quality (PQ) disturbances using wavelet, Hilbert transform, Gabor transform, Gabor-Wigner transform, S transform, and Hilbert-Haung transform. This paper presents a new method for detection and classification of single and combined PQ disturbances using a sparse signal decomposition (SSD) on overcomplete hybrid dictionary (OHD) matrix. The method first decomposes a PQ signal into detail and approximation signals using the proposed SSD technique with an OHD matrix containing impulse and sinusoidal elementary waveforms. The output detail signal adequately captures morphological features of transients (impulsive and oscillatory) and waveform distortions (harmonics and notching). Whereas the approximation signal contains PQ features of fundamental, flicker, dc-offset, and short- and long-duration variations (sags, swells, and interruptions). Thus, the required PQ features are extracted from the detail and approximation signals. Then, a hierarchical decision-tree algorithm is used for classification of single and combined PQ disturbances. The proposed method is tested using both synthetic and microgrid simulated PQ disturbances. Results demonstrate the accuracy and robustness of the method in detection and classification of single and combined PQ disturbances under noiseless and noisy conditions. The method can be easily expanded for compressed sensing based PQ monitoring networks.

Energy function analysis for power system stability

Abstract: (1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

AC-microgrids versus DC-microgrids with distributed energy resources: A review

Abstract: This paper presents the latest comprehensive literature review of AC and DC microgrid (MG) systems in connection with distributed generation (DG) units using renewable energy sources (RESs), energy storage systems (ESS) and loads. A survey on the alternative DG units' configurations in the low voltage AC (LVAC) and DC (LVDC) distribution networks with several applications of microgrid systems in the viewpoint of the current and the future consumer equipments energy market is extensively discussed. Based on the economical, technical and environmental benefits of the renewable energy related DG units, a thorough comparison between the two types of microgrid systems is provided. The paper also investigates the feasibility, control and energy management strategies of the two microgrid systems relying on the most current research works. Finally, the generalized relay tripping currents are derived and the protection strategies in microgrid systems are addressed in detail. From this literature survey, it can be revealed that the AC and DC microgrid systems with multiconverter devices are intrinsically potential for the future energy systems to achieve reliability, efficiency and quality power supply.

State of the Art in Research on Microgrids: A Review

Abstract: The significant benefits associated with microgrids have led to vast efforts to expand their penetration in electric power systems. Although their deployment is rapidly growing, there are still many challenges to efficiently design, control, and operate microgrids when connected to the grid, and also when in islanded mode, where extensive research activities are underway to tackle these issues. It is necessary to have an across-the-board view of the microgrid integration in power systems. This paper presents a review of issues concerning microgrids and provides an account of research in areas related to microgrids, including distributed generation, microgrid value propositions, applications of power electronics, economic issues, microgrid operation and control, microgrid clusters, and protection and communications issues.

Coded Communication over Fading Channels

Abstract: In studying the performance of coded communications over memoryless channels (with or without fading), the results are given as upper bounds on the average bit error probability (BEP). In principle, there are three different approaches to arriving at these bounds, all of which employ obtaining the so-called pairwise error probability , or the probability of choosing one symbol sequence over another for a given pair of possible transmitted symbol sequences, followed by a weighted summation over all pairwise events. In this chapter, we will focus on the results obtained from the third approach since these provide the tightest upper bounds on the true performance. The first emphasis will be placed on evaluating the pairwise error probability with and without CSI, following which we shall discuss how the results of these evaluations can be used via the transfer bound approach to evaluate average BEP of coded modulation transmitted over the fading channel.

Review on Control of DC Microgrids and Multiple Microgrid Clusters

Abstract: This paper performs an extensive review on control schemes and architectures applied to dc microgrids (MGs). It covers multilayer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active damping aspects, as well as nonlinear control algorithms. Islanding detection, protection, and MG clusters control are also briefly summarized. All the mentioned issues are discussed with the goal of providing control design guidelines for dc MGs. The future research challenges, from the authors’ point of view, are also provided in the final concluding part.