A. Naresh Kumar

Bio: A. Naresh Kumar is an academic researcher from Gandhi Institute of Technology and Management. The author has contributed to research in topics: Transmission line & Fuzzy logic. The author has an hindex of 4, co-authored 12 publications receiving 51 citations. Previous affiliations of A. Naresh Kumar include SRM University.

Fuzzy inference system-based solution to locate the cross-country faults in parallel transmission line:

Abstract: Locating cross-country faults in a parallel transmission line is a critical and challenging task because faults occur at different locations. In this paper, an accurate fuzzy inference system schem...

Mamdani Fuzzy Expert System Based Directional Relaying Approach for Six-Phase Transmission Line

Abstract: T demand for electrical power is always increasing, as a rule of thumb, it doubles every decade. In order to reach this booming demand, power transfer capability of the transmission lines is required to be improved continuously. It can be done either by enhancing the voltage handling capability or by upgrading the existing power transmission systems to multi-phase (i.e. 6, 9 and 12-phase) transmission systems. The multi-phase transmission serves as an optimal solution to handle high power transfer capacity of existing transmission systems. Existing single and double circuit 3-phase transmission lines can easily be modified to operate as a single circuit 6-phase transmission line. Apart from improved power transfer capacity, 6-phase transmission systems provide several other benefits over traditional 3-phase double circuit transmission line viz. higher efficiency, lesser corona, higher thermal loading capability, better surge impedance, good voltage regulation, lesser audible noise levels, lesser radio interference and lesser conductor surface gradient. The 6-phase line theory and benefits are described in [1]-[2]. Existing 115kV, double circuit 3-phase transmission line was modified into 93kV, 2.4 km,6phase line configuration in between Goudey-Okadale substations. The 93kV, configuration research was conducted for three years from 1992 to 1995, after it was replaced to its original 115kV, double circuit 3-phase transmission line configuration [3] because of the failure of 6-phase line protection. Although 6-phase line offers more benefits to electrical power system operations, the fault protection task in 6-phase line is more difficult than in double circuit 3-phase transmission lines. It can cause permanent damage to the transmission lines. Thus, early identification is needed to minimize the incidences severity of power system damages. Till now, several techniques have been focusing on locating and classifying faults in 6-phase transmission line [4]-[8]. In [4], the fundamental component of measured currents is used for fault detection and classification. In [5], the Haar Wavelet Transform measured currents are employed for fault detection and classification. A methodology based on current measurements for locating faults is provided in [6]. Modular artificial neural network (ANN) scheme is demonstrated [7] for fault classification and location based on fundamental component voltages and currents. Same Modular ANN scheme is addressed [8] for fault classification and location based on wavelet transform voltages and currents. Nonetheless, all the aforementioned schemes are relevant to normal fault classification and location but they are not applicable for directional relaying. Only a few researchers have illustrated directional relaying in 6-phase transmission lines [9]–[10], but these methods do not classify and locate the faults. In [11], a neuro-wavelet algorithm for zone/section identification and fault location in 6-phase transmission lines is suggested. The directional relaying algorithms are developed using linear discriminant analysis [12], adaptive neuro-fuzzy inference system [13], decision tree [14] and ANN [15] methods. Among all the soft computing methods, fuzzy expert system (FES) is employed mostly in transmission line protection applications owing to less computation work and easy implementation, unlike other soft computing techniques. Some notable works have been reported in the literature on the soft computing techniques [16]–[18]. Fuzzy with single end directional relaying scheme for transmission line compensated by fixed series capacitor have been Keywords

Fuzzy Inference System Based Distance Estimation Approach for Multi Location and Transforming Phase to Ground Faults in Six Phase Transmission Line

Abstract: The faults occurring in different phases at multiple locations and different times are difficult to locate exact location using conventional techniques. This paper develops a fault location estimation approach using fuzzy inference system for multi location phase to ground faults and transforming phase to ground faults in six phase transmission (SPT) line. The six phase current data of SPT line are generated by MATLAB software and processed through butter worth filter, sampling and discrete fourier transform for distance locator. The proposed technique is dependent on single terminal data only. Mamdani fuzzy inference system is employed to make decision. Triangular membership functions are used to design input-output fuzzy sets. Fuzzy inference system has been deployed for the fault distance location using IF-THEN rules. The proposed technique is validated during different multi location and transforming phase to ground faults with wide variations in fault resistance and fault inception angle. Simulations and calculations with MATLAB prove that the fault location method is correct and accurate.

AI based Economic Load Dispatch incorporating wind power penetration

Abstract: Economic Load Dispatch (ELD) is one of the most important problems to be solved in the operation and planning of a power system. Its objective is to schedule the power generation properly in order to minimize the total operational cost. Renewable energy resources such as wind power have significant attention in recent years in power system field. It reduces fuel consumption and also benefits in curbing emission. But wind power penetration into conventional systems due to its intermittent nature has some implications like security concerns. Thus a reasonable trade off is required between system risk and operational cost. In this paper a bi-objective economic dispatch problem considering wind power penetration is formulated. A fuzzy membership function is used to represent the dispatch of wind power into the conventional system. A particle swarm optimization algorithm, Genetic algorithm and a bacteria-foraging technique are adopted to develop a dispatch scheme compromising both the economic and security requirements. The results of all these 3 proposed techniques are compared. Numerical analyses are reported based on a typical IEEE-30-bus with six-generator test power system to show the validity and applicability of the proposed approaches.

A single-end directional relaying scheme for double-circuit transmission line using fuzzy expert system

Abstract: The faults occurring in different sections are difficult to identify using the traditional techniques. This paper investigates a fuzzy expert system for directional relaying, classification, and location of faults in double-circuit transmission lines. The current magnitudes measured at only one terminal of the double-circuit transmission line are used to compute discreet Fourier coefficients. Thus, this scheme does not involve any communication channel. The presented fuzzy expert system is achieved from the structure of MAMDANI system in LabVIEW software. Test case studies show the effectiveness of the presented scheme. The simulation results attest that the directional relaying, classification, and location estimation is very accurate. This scheme is adaptive to the change of fault location, fault resistance, fault inception angle, and fault type.

Real-Time Sensing and Fault Diagnosis for Transmission Lines

Abstract: Article Real-Time Sensing and Fault Diagnosis for Transmission Lines Fatemeh Mohammadi Shakiba 1, Milad Shojaee 1, S. Mohsen Azizi 1,2, and Mengchu Zhou 1,* 1 Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark 07102, NJ, USA. 2 The school of Applied Engineering and Technology, New Jersey Institute of Technology, Newark 07102, NJ, USA. * Correspondence: mengchu.zhou@njit.edu Received: 12 October 2022 Accepted: 8 November 2022 Published: 22 December 2022 Abstract: Protection of high voltage transmission lines is one of the crucial problems in the power system engineering. Accurate and timely detection and identification of transmission line short circuit faults can considerably improve and simplify their recovery process and hence save the costs associated with the downtime of a power system. Hence, it is essential that a robust and reliable fault diagnosis system completes its operation within an acceptable time window after fault occurrence in the presence of uncertainties and disturbances in the system. The significant costs of mistakenly detected or undetected faults based on the conventional techniques motivate us to present a robust detection and identification system by using the convolutional neural networks. The robustness of this technique is analyzed for the variations of the phase difference between two connected buses, fault resistance, source inductance fluctuations, fault inception angle, local bus voltage fluctuations, and measurement noises. The time delay analysis is also conducted to indicate that the presented technique is able to detect, identify, and estimate the location of faults before tripping relays and circuit breakers disconnect a faulty region.

Fuzzy inference system-based solution to locate the cross-country faults in parallel transmission line:

Abstract: Locating cross-country faults in a parallel transmission line is a critical and challenging task because faults occur at different locations. In this paper, an accurate fuzzy inference system schem...