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Using information entropy to quantify uncertainty in distribution networks

conference contribution
posted on 2023-05-23, 09:42 authored by Michael NegnevitskyMichael Negnevitsky, Terry, J, Nguyen, T
Information about the certainty of the predicted state of a network is crucial for the effective management of a modern power system. In transmission systems, observability analysis is used to assess whether the estimated state is valid, based on the available measurements. In distribution systems there is no method for quantifying the uncertainty in a modelled state; this places limitations on how the modelled state can be used. This paper explores a new method of quantifying the uncertainty in a state estimation solution, with information entropy. A Monte Carlo simulation approach was used to determine the probability of the network being in a specific state. The proposed approach allows for the objective evaluation of the certainty of a state solution in distribution networks, which can be easily interpreted by distribution network service providers. Case studies were conducted, results are resented and discussed.

History

Publication title

Proceedings of the 24th Australasian Universities Power Engineering Conference

Editors

A Abu-Siada and MAS Masoum

Pagination

1-6

ISBN

978-0-646-92375-8

Department/School

School of Engineering

Publisher

IEEE

Place of publication

Perth, Australia

Event title

The 24th Australasian Universities Power Engineering Conference

Event Venue

Perth, Australia

Date of Event (Start Date)

2014-09-28

Date of Event (End Date)

2014-10-01

Rights statement

Copyright 2014 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Energy systems and analysis

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    University Of Tasmania

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