Load Profiling with Fuzzy Self-Organizing Algorithms

被引：0

作者：

Gavrilas, Mihai ^{[1
]}

Ivanov, Ovidiu ^{[1
]}

Gavrilas, Gilda

机构：

[1] Tech Univ Iasi, Power Syst Dept, Iasi, Romania

来源：

NEUREL 2008: NINTH SYMPOSIUM ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING, PROCEEDINGS | 2008年

关键词：

Distribution systems; Fuzzy logic; Load profiling; Self-organization;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 It he 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.

引用

页码：60 / +

页数：2

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