Title :
Next day load curve forecasting using hybrid correction method
Author :
Senjyu, Tomonobu ; Takara, Hitoshi ; Asato, Kentarou ; Uezato, Katsumi ; Funabashi, Toshihisa
Author_Institution :
Dept. of Electr. & Electron. Eng., Ryukyus Univ., Okinawa, Japan
Abstract :
In this paper, the authors propose a next day load curve forecasting using a hybrid correction method which is a combination of neural network and fuzzy logic. In this proposed prediction method, the forecasted load power is obtained by adding a correction that is obtained from the neural network and a fuzzy logic to the selected similar day´s data. The neural network has the advantage of dealing with the nonlinear part of forecasted load curves. The fuzzy rules are constructed based on expert knowledge. Therefore, combining these methods, the proposed method is useful in situations where accurate forecasting models are difficult to obtain. The suitability of the proposed approach is illustrated through an application to actual load data of the Okinawa Electric Power Company in Japan.
Keywords :
expert systems; fuzzy logic; load forecasting; neural nets; power system analysis computing; power system planning; Japan; expert knowledge; fuzzy logic; hybrid correction method; neural network; next day load curve forecasting; Demand forecasting; Fuzzy logic; Input variables; Load forecasting; Neural networks; Power system modeling; Prediction methods; Predictive models; Temperature; Weather forecasting;
Conference_Titel :
Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES
Print_ISBN :
0-7803-7525-4
DOI :
10.1109/TDC.2002.1177710