DocumentCode :
1257790
Title :
Automated Load Curve Data Cleansing in Power Systems
Author :
Chen, Jiyi ; Li, Wenyuan ; Lau, Adriel ; Cao, Jiguo ; Wang, Ke
Author_Institution :
Simon Fraser Univ., Vancouver, BC, Canada
Volume :
1
Issue :
2
fYear :
2010
Firstpage :
213
Lastpage :
221
Abstract :
Load curve data refers to the electric energy consumption recorded by meters at certain time intervals at delivery points or end user points, and contains vital information for day-to-day operations, system analysis, system visualization, system reliability performance, energy saving and adequacy in system planning. Unfortunately, it is unavoidable that load curves contain corrupted data and missing data due to various random failure factors in meters and transfer processes. This paper presents the B-Spline smoothing and Kernel smoothing based techniques to automatically cleanse corrupted and missing data. In implementation, a man-machine dialogue procedure is proposed to enhance the performance. The experiment results on the real British Columbia Transmission Corporation (BCTC) load curve data demonstrated the effectiveness of the presented solution.
Keywords :
data mining; power systems; regression analysis; B-Spline smoothing; BCTC; British Columbia transmission corporation; Kernel smoothing; automated load curve data cleansing; electric energy consumption; energy saving; power systems; system analysis; system reliability; system visualization; transfer processes; Data visualization; Energy consumption; Information analysis; Performance analysis; Power system analysis computing; Power system planning; Power system reliability; Power systems; Smoothing methods; Spline; Load management; load modeling; power quality; power systems; smoothing methods;
fLanguage :
English
Journal_Title :
Smart Grid, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3053
Type :
jour
DOI :
10.1109/TSG.2010.2053052
Filename :
5524054
Link To Document :
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