NDLI: Application technique for model-based approach to estimate fault location

Please wait, while we are loading the content...

Biosurface and Biotribology

CAAI Transactions on Intelligence Technology

CIRED - Open Access Proceedings Journal

Chinese Journal of Electronics

Cognitive Computation and Systems

Electronics Letters

Energy Conversion and Economics

Engineering & Technology

Engineering Biology

Healthcare Technology Letters

IET Circuits, Devices & Systems

IET Collaborative Intelligent Manufacturing

IET Communications

IET Computer Vision

IET Computers & Digital Techniques

IET Control Theory & Applications

IET Cyber-Physical Systems: Theory & Applications

IET Cyber-Systems and Robotics

IET Electric Power Applications

IET Electrical Systems in Transportation

IET Energy Systems Integration

IET Generation, Transmission & Distribution

IET Image Processing

IET Information Security

IET Intelligent Transport Systems

IET Microwaves, Antennas & Propagation

IET Nanobiotechnology

IET Nanodielectrics

IET Optoelectronics

IET Power Electronics

IET Quantum Communication

IET Radar, Sonar & Navigation

IET Renewable Power Generation

IET Science, Measurement & Technology

IET Signal Processing

IET Smart Cities

Volume 4 (2021)

Volume 3 (2020)

Volume 3 (2020) : Issue 6, Dec

Volume 3 (2020) : Issue 5, Oct

Volume 3 (2020) : Issue 4, Aug

AI in arcing-HIF detection: a brief review

Adapting big data standards, maturity models to smart grid distributed generation: critical review

Application technique for model-based approach to estimate fault location

Corrigendum: Design and techno-economic analysis of plug-in electric vehicle-integrated solar PV charging system for India

Deep learning for day-ahead electricity price forecasting

Distributed PV generation estimation using multi-rate and event-driven Kalman kriging filter

Fast dynamic voltage security margin estimation: concept and development

Guest Editorial: Machine Learning in Power Systems

Hybrid data-driven physics model-based framework for enhanced cyber-physical smart grid security

Improving primary frequency response in networked microgrid operations using multilayer perceptron-driven reinforcement learning

Phase identification using co-association matrix ensemble clustering

Power system virtual inertia implemented by thermostatically controlled loads

Real-time stability assessment in smart cyber-physical grids: a deep learning approach

Research on hierarchical control and optimisation learning method of multi-energy microgrid considering multi-agent game

Stacking battery energy storage revenues with enhanced service provision

Volume 3 (2020) : Issue 3, Jun

Volume 3 (2020) : Issue 2, Apr

Volume 3 (2020) : Issue 1, Feb

Volume 2 (2019)

Volume 1 (2018)

IET Systems Biology

IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Application technique for model-based approach to estimate fault location

Content Provider	IET Digital Library
Author	Ananthan, Sundaravaradan Navalpakkam Santoso, Surya
Abstract	Impedance-based algorithms commonly used for determining the fault location in transmission lines are prone to several sources of error and are specific to the line and system configuration. Furthermore, these algorithms do not utilise available valuable information about the power system surrounding the faulted line. These issues can be overcome using a model-based fault location (MBFL) approach. It uses a circuit model to simulate possible fault scenarios and compares the simulated fault currents with the measured currents recorded by the relay to identify the fault location. However, there are several difficulties and limitations while applying MBFL. There is a loss in accuracy and precision based on the number of simulated scenarios and a requirement to store voluminous simulation results. Hence, this study presents a novel application technique for implementing model-based approach efficiently to estimate the fault location and fault resistance using artificial neural networks-based approach. A key highlight of the proposed approach is the ability to identify the location of a fault present on neighbouring lines using the measured through fault current. The study also presents representative scenarios to demonstrate the capability and potential of the proposed approach.
Starting Page	421
Ending Page	434
Page Count	14
Volume Number	3
e-ISSN	25152947
Issue Number	Issue 4, Aug (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-stg/3/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0135
Journal	IET Smart Grid
Publisher	The Institution of Engineering and Technology
Publisher Date	2019-12-03
Access Restriction	Open
Rights License	Creative Commons Attribution-Non Commercial-No Derivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
Subject Keyword	Artificial Neural Network Circuit Model Fault Current Fault Location Fault Location Estimation Fault Resistance Faulted Line Impedance-based Algorithm Model-based Fault Location Approach Neural Computing Technique Neural Nets Power Engineering Computing Power System Power System Protection Power Transmission Cables Power Transmission Fault Power Transmission Line Power Transmission, Distribution And Supply Simulated Fault Current System Configuration Transmission Line
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in