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http://dx.doi.org/10.5370/KIEEP.2013.62.2.065

Static Load Modeling Based on Artificial Neural Network and Harmonics  

Lee, Jong-Pil (한국교통대학교 전기공학과)
Kim, Sung-Soo (충북대학교 전기공학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.62, no.2, 2013 , pp. 65-71 More about this Journal
Abstract
Nonlinear loads with harmonics exist in an actual power system where harmonic currents make voltage distortion. The sum of reactive power measured at individual load is different from the measured reactive power at a bus in a power system with linear and non-linear loads. In this study, ANN(artificial neural network) load modeling technique with consideration of harmonics is introduced for more accurate component load modeling and an impact coefficient is proposed for aggregation of component loads. Results of this research show more accurate load modeling method. Since precise data for power system analysis can be acquired, the proposed method will be used for power system planning and maintenance.
Keywords
Component-based load model; Composition rate; Harmonics; Load model;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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