Title :
Load profiling with fuzzy self-organizing algorithms
Author :
Gavrilas, Mihai ; Ivanov, Ovidiu ; Gavrilas, Gilda
Author_Institution :
Power Syst. Dept., Tech. Univ. of Iasi, Iasi
Abstract :
This paper describes an enhanced fuzzy self-organizing algorithm (EF-SOM) to address the problem of consumer classification in electric distribution networks based on the shape of the load profiles (LPs). This algorithm is a modified form of the standard fuzzy Kohonen algorithm, which determines the deviations between metered-LPs and the prototypes of the typical LPs using weighted windows around the peak and valley hours. The EF-SOM algorithm was tested on an independent load profile database, proofing its ability to filter outliers LPs and to produce realistic classification results.
Keywords :
distribution networks; electricity supply industry; fuzzy set theory; load distribution; power markets; self-organising feature maps; consumer classification; electric distribution network; enhanced fuzzy self-organizing algorithm; fuzzy Kohonen algorithm; load profiling; Databases; Electronic mail; Energy consumption; Iterative algorithms; Neural networks; Power system control; Power systems; Prototypes; Shape; Testing; Distribution systems; Fuzzy logic; Load profiling; Self-organization;
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2008. NEUREL 2008. 9th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4244-2903-5
Electronic_ISBN :
978-1-4244-2904-2
DOI :
10.1109/NEUREL.2008.4685564