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http://dx.doi.org/10.5370/KIEE.2010.59.10.1712

Customer Classification Method Using Customer Attribute Information to Generate the Virtual Load Profile of non-Automatic Meter Reading Customer  

Kim, Young-Il (한국전력공사 전력연구원)
Ko, Jong-Min (한국전력공사 전력연구원)
Song, Jae-Ju (한국전력공사 전력연구원)
Choi, Hoon (충남대학교 컴퓨터공학과)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.59, no.10, 2010 , pp. 1712-1717 More about this Journal
Abstract
To analyze the load of distribution line, real LPs (Load Profile) of AMR (Automatic Meter Reading) customers and VLPs (Virtual Load Profile) of non-AMR customers are required. Accuracy of VLP is an important factor to improve the analysis performance. There are 2 kinds of methods to generate the VLP; one is using ALP (Average Load Profile) per each industrial code and PNN (Probability neural networks) algorithm; the other is using LSI (Load Shape Index) and C5.0 algorithm. In this paper, existing researches are studied, and new method is suggested. Each methods are compared the performance with same LP data of real high voltage customers.
Keywords
Customer classification; Virtual load profile; K-means; PNN; C5.0;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
Times Cited By SCOPUS : 0
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