DocumentCode
656708
Title
Blind topology identification for power systems
Author
Xiao Li ; Poor, H. Vincent ; Scaglione, Anna
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of California, Davis, Davis, CA, USA
fYear
2013
fDate
21-24 Oct. 2013
Firstpage
91
Lastpage
96
Abstract
In this paper, the blind topology identification problem for power systems only using power injection data at each bus is considered. As metering becomes widespread in the smart grid, a natural question arising is how much information about the underlying infrastructure can be inferred from such data. The identifiability of the grid topology is studied, and an efficient learning algorithm to estimate the grid Laplacian matrix (i.e., the graph equivalent of the grid admittance matrix) is proposed. Finally, the performance of our algorithm for the IEEE-14 bus system is demonstrated, and the consistency of the recovered graph with the true graph associated with the underlying power grid is shown in simulations.
Keywords
IEEE standards; graph theory; learning (artificial intelligence); matrix algebra; power system identification; power system measurement; power system simulation; smart power grids; IEEE-14 bus system; blind topology identification problem; grid Laplacian matrix estimation; grid admittance matrix; grid topology identification; learning algorithm; power grid simulation; power injection data; power system; smart grid metering; true graph recovery; Eigenvalues and eigenfunctions; Laplace equations; Load modeling; Monitoring; Null space; Power grids; Topology;
fLanguage
English
Publisher
ieee
Conference_Titel
Smart Grid Communications (SmartGridComm), 2013 IEEE International Conference on
Conference_Location
Vancouver, BC
Type
conf
DOI
10.1109/SmartGridComm.2013.6687939
Filename
6687939
Link To Document