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Reliability Computation of Neuro-Fuzzy Model Based Short Term Electrical Load Forecasting  

Shim, Hyun-Jeong (팬택 & 큐리텔)
Wang, Bo-Hyeun (강릉대 공대 전자공학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers A / v.54, no.10, 2005 , pp. 467-474 More about this Journal
Abstract
This paper presents a systematic method to compute a reliability measure for a short term electrical load forecasting system using neuro-fuzzy models. It has been realized that the reliability computation is essential for a load forecasting system to be applied practically. The proposed method employs a local reliability measure in order to exploit the local representation characteristic of the neuro-fuzzy models. It, hence, estimates the reliability of each fuzzy rule learned. The design procedure of the proposed short term load forecasting system is as follows: (1) construct initial structures of neuro-fuzzy models, (2) store them in the initial structure bank, (3) train the neuro-fuzzy model using an appropriate initial structure, and (4) compute load prediction and its reliability. In order to demonstrate the viability of the proposed method, we develop an one hour ahead load forecasting system by using the real load data collected during 1996 and 1997 at KEPCO. Simulation results suggest that the proposed scheme extends the applicability of the load forecasting system with the reliably computed reliability measure.
Keywords
단기 전력 수요 예측;신뢰도;뉴로-퍼지 모델;구조 학습;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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