TY - JOUR
T1 - Short-term load forecasting via ARMA model identification including non-Gaussian process considerations
AU - Huang, Shyh Jier
AU - Shih, Kuang Rong
N1 - Funding Information:
Manuscript received September 5, 2002. This work was supported in part by the National Science Council of the Republic of China under Contract NSC88-2213-E-006-075 and in part by Taiwan Power Company under Contract NSC88-TPC-E-006-013. The authors are with the Department of Electrical Engineering, National Cheng Kung University, Tainan, 70101, Taiwan, R.O.C. Digital Object Identifier 10.1109/TPWRS.2003.811010
PY - 2003/5
Y1 - 2003/5
N2 - In this paper, the short-term load forecast by use of autoregressive moving average (ARMA) model including non-Gaussian process considerations is proposed. In the proposed method, the concept of cumulant and bispectrum are embedded into the ARMA model in order to facilitate Gaussian and non-Gaussian process. With embodiment of a Gaussianity verification procedure, the forecasted model is identified more appropriately. Therefore, the performance of ARMA model is better ensured, improving the load forecast accuracy significantly. The proposed method has been applied on a practical system and the results are compared with other published techniques.
AB - In this paper, the short-term load forecast by use of autoregressive moving average (ARMA) model including non-Gaussian process considerations is proposed. In the proposed method, the concept of cumulant and bispectrum are embedded into the ARMA model in order to facilitate Gaussian and non-Gaussian process. With embodiment of a Gaussianity verification procedure, the forecasted model is identified more appropriately. Therefore, the performance of ARMA model is better ensured, improving the load forecast accuracy significantly. The proposed method has been applied on a practical system and the results are compared with other published techniques.
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U2 - 10.1109/TPWRS.2003.811010
DO - 10.1109/TPWRS.2003.811010
M3 - Article
AN - SCOPUS:0037505508
SN - 0885-8950
VL - 18
SP - 673
EP - 679
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 2
ER -