Paper Info
Title
Global sensitivity analysis of transmission line fault-locating algorithms using sparse grid regression.
Abstract
Computation of distance to fault on an electrical transmission line is affected by many sources of uncertainty, including parameter setting errors, measurement errors, as well as absence of information and incomplete modelling of a system under fault condition. In this paper we propose an application of the variance-based global sensitivity measures for evaluation of fault location algorithms. The main goal of the evaluation is to identify factors and their interactions that contribute to the fault locator output variability. This analysis is based on the results of Sparse Grid Regression. The method compiles the Functional ANOVA model to represent fault locator output as a function of uncertain factors. The ANOVA model provides a tool for interpretation and sensitivity analysis. In practice, such analysis can help in functional performance tests, especially in: selection of the optimal fault location algorithm (device) for a specific application, calibration process and building confidence in a fault location function result. The paper concludes with an application example which demonstrates use of the proposed methodology in testing and comparing some commonly used fault location algorithms. This example is also used to demonstrate numerical efficiency for this type of application of the proposed Sparse Grid Regression method in comparison to the Quasi-Monte Carlo approach.
Year
DOI
Venue
2012
10.1016/j.ress.2011.12.005
Reliability Engineering & System Safety
Keywords
DocType
Volume
Global sensitivity analysis,Sparse grid regression,Sparse grid integration,Quasi-Monte Carlo,Transmission lines
Journal
107
ISSN
Citations 
PageRank 
0951-8320
1
0.37
References 
Authors
2
1
Name
Order
Citations
PageRank
Rastko Zivanovic1134.74