eCite Digital Repository

An observability index for distribution networks using information entropy

Citation

Brinkmann, B and Negnevitsky, M and Yee, T and Nguyen, T, An observability index for distribution networks using information entropy, 2015 Australasian Universities Power Engineering Conference (AUPEC), 27-30 September, Wollongong, NSW, pp. 1-6. ISBN 978-1-4799-8725-2 (2015) [Refereed Conference Paper]


Preview
PDF
690Kb
  

Copyright Statement

Copyright 2015 IEEE

DOI: doi:10.1109/AUPEC.2015.7324798

Abstract

Information about the accuracy of state estimation results in distribution networks is crucial for an effective and safe network management. This paper explores a new method of quantifying the uncertainty of a state estimation result by using information entropy as an index for observability. This index has the ability to represent the network observability as a single continuous number, making it possible for the network operator to objectively evaluate the reliability of a state estimation result. This paper also investigates the changes in observability due to load variations and demonstrates how an optimal meter placement method based on the proposed observability index can be implemented. The proposed method has been tested via simulations on a modified IEEE 34 Bus Test Feeder and was compared with an existing method.

Item Details

Item Type:Refereed Conference Paper
Keywords:state estimation, observability, information entropy, optimal meter placement
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Power and Energy Systems Engineering (excl. Renewable Power)
Objective Division:Energy
Objective Group:Energy Storage, Distribution and Supply
Objective Field:Energy Services and Utilities
Author:Brinkmann, B (Mr Bernd Brinkmann)
Author:Negnevitsky, M (Professor Michael Negnevitsky)
Author:Yee, T (Mr Timothy Yee)
ID Code:105795
Year Published:2015
Deposited By:Engineering
Deposited On:2016-01-14
Last Modified:2017-11-06
Downloads:56 View Download Statistics

Repository Staff Only: item control page