Title :
Clustering of Power System Data and Its Use in Load Pocket Identification
Author :
Rogers, Katherine M. ; Overbye, Thomas J.
Author_Institution :
Univ. of Illinois, Urbana, IL, USA
Abstract :
When lines in a power system are constrained, the sensitivity of the power flows on these lines to generator output provides information about how the constraints divide the system and about the ability of sets of generators to increase revenue without increasing dispatch. Clustering is used to identify generators into groups with the potential for market advantage. In this paper, we discuss the implementation of several different clustering methods for identifying load pockets with potential market advantage.
Keywords :
electric generators; pattern clustering; power engineering computing; power system economics; generator output; load pocket identification; power system data clustering; Algorithm design and analysis; Approximation algorithms; Artificial neural networks; Clustering algorithms; Generators; Nearest neighbor searches; Vectors;
Conference_Titel :
System Sciences (HICSS), 2011 44th Hawaii International Conference on
Conference_Location :
Kauai, HI
Print_ISBN :
978-1-4244-9618-1
DOI :
10.1109/HICSS.2011.104