TY - GEN
T1 - Review of Clustering Algorithms for Microgrid Formation
AU - Li Kwok Cheong, Derek
AU - Fernando, Tyrone
AU - Iu, Herbert
AU - Reynolds, Mark
AU - Fletcher, James
PY - 2018/6/8
Y1 - 2018/6/8
N2 - 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.
AB - 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.
U2 - 10.1109/ISGT-Asia.2017.8378350
DO - 10.1109/ISGT-Asia.2017.8378350
M3 - Conference paper
T3 - 2017 IEEE Innovative Smart Grid Technologies - Asia: Smart Grid for Smart Community, ISGT-Asia 2017
SP - 1
EP - 6
BT - 2017 IEEE Innovative Smart Grid Technologies - Asia
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - United States
T2 - 2017 IEEE Innovative Smart Grid Technologies
Y2 - 4 December 2017 through 7 December 2017
ER -