Review of Clustering Algorithms for Microgrid Formation

Derek Li Kwok Cheong, Tyrone Fernando, Herbert Iu, Mark Reynolds, James Fletcher

Research output: Chapter in Book/Conference paperConference paperpeer-review

8 Citations (Scopus)

Abstract

Transitioning from a traditional distribution network grid or diesel only systems to microgrids, offers end-users economic benefits and higher power quality at a reduced environmental cost. Particularly, an upcoming research area, multi-microgrids, aims to provide a more reliable network capable of self-healing. The aim of this paper is to assess well-known clustering algorithms for cost effective microgrid formation and develop a planning framework for uncoupled multi-microgrid networks. In each microgrid, a minimum spanning tree represented the network, resulting in a linear relationship between the microgrid cost and the transmission/power demand. In addition, a diversity factor was introduced to showcase the ability of larger microgrids to more reliably meet peak power demands. Simulation results from three real life datasets suggested that hierarchical clustering algorithms were more suited for microgrid planning due to their adaptability to any datasets, complete solution space search guaranteeing global optimum networks and relative computational efficiency.
Original languageEnglish
Title of host publication2017 IEEE Innovative Smart Grid Technologies - Asia
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-6
Number of pages6
ISBN (Electronic)9781538649503
DOIs
Publication statusPublished - 8 Jun 2018
Event2017 IEEE Innovative Smart Grid Technologies - Auckland, New Zealand
Duration: 4 Dec 20177 Dec 2017

Publication series

Name2017 IEEE Innovative Smart Grid Technologies - Asia: Smart Grid for Smart Community, ISGT-Asia 2017

Conference

Conference2017 IEEE Innovative Smart Grid Technologies
Country/TerritoryNew Zealand
CityAuckland
Period4/12/177/12/17

Fingerprint

Dive into the research topics of 'Review of Clustering Algorithms for Microgrid Formation'. Together they form a unique fingerprint.

Cite this