A statistical study on topological features of high voltage distribution networks in Western Australia

Author

Li, Yingliang ; Wolfs, Peter

fYear

2010

fDate

5-8 Dec. 2010

Firstpage

1

Lastpage

6

Abstract

The assessment of changes in technology or load behaviors on distribution networks requires a rigorous understanding of the features of the network itself. In a typical distribution network, there will be hundreds of high voltage (HV) feeders and ten thousands of low voltage (LV) feeders. This work uses cluster analysis to identify statistically representative or prototypical HV feeders in the West Australian context. The representative HV feeder data will be used as an input to the development of Monte Carlo models to assess the impact of technology changes driven by Smart Grid deployments or load changes due to solar panel, air conditioning or electric vehicle uptake.

Keywords

Monte Carlo methods; distribution networks; statistical analysis; Monte Carlo model; Western Australia; air conditioning; cluster analysis; electric vehicle uptake; high voltage distribution network; high voltage feeder; low voltage feeder; prototypical HV feeder; smart grid deployment; solar panel; statistical study; topological feature; Australia; Biological system modeling; Data models; Euclidean distance; Load modeling; Monte Carlo methods; Smart grids;

fLanguage

English

Publisher

ieee

Conference_Titel

Universities Power Engineering Conference (AUPEC), 2010 20th Australasian

Conference_Location

Christchurch

Print_ISBN

978-1-4244-8379-2

Electronic_ISBN

978-1-4244-8380-8

Type

conf

Filename

5710756