Suresh Gautam

Bio: Suresh Gautam is an academic researcher from New Mexico State University. The author has contributed to research in topics: Fault (power engineering) & Electric power system. The author has an hindex of 6, co-authored 6 publications receiving 340 citations.

Detection of High Impedance Fault in Power Distribution Systems Using Mathematical Morphology

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.

Overview of mathematical morphology in power systems — A tutorial approach

Abstract: Use of mathematical morphology (MM) in power system has been reported recently in open literature. However, MM has not been adequately discussed as a filtering tool for power system signals. This paper takes a tutorial-approach and explains the concept of MM, its derivative processes, basic MM based filters and their applications through simple reproducible examples. Characteristics of MM based filters and their associated delays are explained. The paper also shows the effect of varying different filter and signal parameters on the performance of MM based filters. The process of event detection using MM based filters is described as a typical application. Finally, a comprehensive list of the published applications of MM is provided.

Out-of-step blocking function in distance relay using mathematical morphology

Abstract: Out-of-step condition arising from an unstable power swing requires quick detection of the power swing followed by a controlled separation of different areas of power system at predetermined locations. However, in order to perform such separation, local operation of distance relays needs to be blocked using out-of-step blocking (OSB) function. Conventional blinder-based method to implement the OSB function cannot detect a symmetrical fault once the relay is blocked during a power swing. Different schemes are proposed to overcome this drawback. This study presents detection methods for power swing and symmetrical faults, based on mathematical morphology. These methods offer distinct advantages over other schemes proposed in the literature. The methods are combined and rigorously tested on waveforms generated using PSCAD/EMTDC®. These methods are then used to propose a reliable and fast OSB tool that imposes a very low computation burden at low sampling rate.

Guidelines for selection of an optimal structuring element for Mathematical Morphology based tools to detect power system disturbances

Abstract: Mathematical Morphology (MM) has been reported as a promising application to detect power system disturbances. The real-time applications of MM based tools are also reported to detect disturbances. However, there is no clear guideline for selection of the structuring element for a particular application, despite the fact that the structuring element is a key component of any MM based tool. This paper shows a method to generalize and numerically optimize the structuring element to detect power system disturbances. Power system fault cases are simulated using a professional time-domain software, and the current and voltage waveforms from these cases are used to illustrate the methodology. Results are observed and analyzed. Some guidelines to select an optimum structuring element to detect power system disturbances are provided based on the results.

Application of Mathematical Morphology based filters to detect a power swing

Abstract: Mathematical Morphology (MM) has been discussed in recent literature for its possible applications in power systems. However, the application of MM as a real-time filtering tool in power systems has not been explored adequately. This paper reports further contributions to our previous efforts in this direction. The paper shows how an appropriate choice of the structuring element (SE) can help develop a method to detect power system phenomena characterized by low frequency. To illustrate the effectiveness of the proposed method, it is used to detect a power swing simulated using PSCAD/EMTDC®. Results are presented and analyzed. Based on the analysis, future work is outlined in order to construct an improved out-of-step blocking tool using this method, and to integrate this tool with a distance relay.

Detection of High Impedance Fault in Power Distribution Systems Using Mathematical Morphology

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.

High-Impedance Fault Detection in the Distribution Network Using the Time-Frequency-Based Algorithm

Abstract: A new high-impedance fault (HIF) detection method using time-frequency analysis for feature extraction is proposed. A pattern classifier is trained whose feature set consists of current waveform energy and normalized joint time–frequency moments. The proposed method shows high efficacy in all of the detection criteria defined in this paper. The method is verified using real-world data, acquired from HIF tests on three different materials (concrete, grass, and tree branch) and under two different conditions (wet and dry). Several nonfault events, which often confuse HIF detection systems, were simulated, such as capacitor switching, transformer inrush current, nonlinear loads, and power-electronics sources. A new set of criteria for fault detection is proposed. Using these criteria, the proposed method is evaluated and its performance is compared with the existing methods. These criteria are accuracy, dependability, security, safety, sensibility, cost, objectivity, completeness, and speed. The proposed method is compared with the existing methods, and it is shown to be more reliable and efficient than its existing counterparts. The effect of choice of the pattern classifier on method efficacy is also investigated.

Traveling Wave-Based Protection Scheme for Inverter-Dominated Microgrid Using Mathematical Morphology

Abstract: Inverter-dominated microgrids impose significant challenges on the distribution network, as inverters are well known for their limited contribution to fault current, undermining the performance of traditional overcurrent protection schemes This paper introduces a new protection scheme based on the initial current traveling wave utilizing an improved mathematical morphology (MM) technology, with simplified polarity detection and new logics introduced for meshed networks and feeders with single-end measurement The proposed protection scheme provides ultrafast response and can be adapted to varied system operational modes, topologies, fault conditions, and load conditions Only low-bandwidth communication is required to achieve high-speed operation and adequate discrimination level in meshed networks Simulation in PSCAD/EMTDC verifies both the sensitivity and stability of the proposed protection scheme under different microgrid operational scenarios

Comparative Study of Advanced Signal Processing Techniques for Islanding Detection in a Hybrid Distributed Generation System

Abstract: In this paper, islanding detection in a hybrid distributed generation (DG) system is analyzed by the use of hyperbolic S-transform (HST), timetime transform, and mathematical morphology methods. The merits of these methods are thoroughly compared against commonly adopted wavelet transform (WT) and S-transform (ST) techniques, as a new contribution to earlier studies. The hybrid DG system consists of photovoltaic and wind energy systems connected to the grid within the IEEE 30-bus system. Negative sequence component of the voltage signal is extracted at the point of common coupling and passed through the above-mentioned techniques. The efficacy of the proposed methods is also compared by an energy-based technique with proper threshold selection to accurately detect the islanding phenomena. Further, to augment the accuracy of the result, the classification is done using support vector machine (SVM) to distinguish islanding from other power quality (PQ) disturbances. The results demonstrate effective performance and feasibility of the proposed techniques for islanding detection under both noise-free and noisy environments, and also in the presence of harmonics.