불규칙하게 취득된 데이터 기반의 배전선로 구간별 일부하 패턴 생성 방법

다국어 초록 (Multilingual Abstract)

Daily load pattern of each part of distribution line is the most important data for distribution operation applications such as service restoration, protection coordination and network reconfiguration. Since distribution system is operated based on the events driven, a periodic state estimation is not an essential function in DAS. Voltage and current data from the FRTUs(Feeder Remote Terminal Units) are measured sparsely and irregularly. This paper proposes a new method for generating daily load pattern of the sections based on incomplete voltage and current data set from the historical database. Matlab simulation case studies has been performed to verify the feasibility of the proposed method.

목차 (Table of Contents)

• Abstract
• 1. 서론
• 2. 본론
• 3. 결론
• References

참고문헌 (Reference)

1 박재형, "배전선로에서 전압측정치의 오차보정을 통한 정확한 구간부하 추정 방법" 한국조명.전기설비학회 30 (30): 43-48, 2016

2 G. Chaojun, "Spatial Load Forecasting With Communication Failure Using Time-Forward Kriging" 29 (29): 2875-2882, 2014

3 S. H. Ling, "Short-term electric load forecasting based on a neural fuzzy network" 50 (50): 1305-1316, 2003

4 Y. Chen, "Short-Term Load Forecasting: Similar Day-Based Wavelet Neural Networks" 25 (25): 322-330, 2010

5 V. H. Hinojosa, "Short-Term Load Forecasting Using Fuzzy Inductive Reasoning and Evolutionary Algorithms" 25 (25): 565-574, 2010

6 I. Dzafic, "Real Time Estimation of Loads in Radial and Unsymmetrical Three-Phase Distribution Networks" 28 (28): 4839-4848, 2013

7 T. Senjyu, "Next day load curve forecasting using hybrid correction method" 20 (20): 102-109, 2005

8 Z. A. Bashir, "Applying Wavelets to Short-Term Load Forecasting Using PSO-Based Neural Networks" 24 (24): 20-27, 2009