TY - JOUR
T1 - Prediction interval estimation of demand curve in electric power distribution system
AU - Yamazaki, Tomohide
AU - Wakao, Shinji
AU - Ito, Hirokazu
AU - Sano, Tsuneyo
N1 - Publisher Copyright:
© 2016 The Institute of Electrical Engineers of Japan.
PY - 2016
Y1 - 2016
N2 - In a distribution line, power system control and power equipment investment are planned based on a measured power system current. However, recently the mass introduction of PV make it difficult for us to precisely measure the demand curve that is a current consumed by electrical equipment because the reversal power flow from PV systems is superposed. Therefore, the prediction of demand curves of distribution line is indispensable for power system management. Additionally, it is also necessary to estimate the reliability of the predicted values as well as predicted current itself. In this paper, we propose the estimation method of the prediction interval that is the index of reliability based on the past demand curve database. The feature of the proposed method based on Just-In-Time (JIT) modeling make it possible for us to accurately estimate the prediction interval by the normalized database of demand curve. In this paper, some numerical examples are presented, which demonstrate the effectiveness of the proposed method.
AB - In a distribution line, power system control and power equipment investment are planned based on a measured power system current. However, recently the mass introduction of PV make it difficult for us to precisely measure the demand curve that is a current consumed by electrical equipment because the reversal power flow from PV systems is superposed. Therefore, the prediction of demand curves of distribution line is indispensable for power system management. Additionally, it is also necessary to estimate the reliability of the predicted values as well as predicted current itself. In this paper, we propose the estimation method of the prediction interval that is the index of reliability based on the past demand curve database. The feature of the proposed method based on Just-In-Time (JIT) modeling make it possible for us to accurately estimate the prediction interval by the normalized database of demand curve. In this paper, some numerical examples are presented, which demonstrate the effectiveness of the proposed method.
KW - Cluster analysis
KW - Electric power distribution system
KW - Just-in-time modeling
KW - Kernel density estimation
KW - Load forecasting
KW - Prediction interval
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U2 - 10.1541/ieejpes.136.848
DO - 10.1541/ieejpes.136.848
M3 - Article
AN - SCOPUS:85000405882
VL - 136
SP - 848
EP - 857
JO - IEEJ Transactions on Power and Energy
JF - IEEJ Transactions on Power and Energy
SN - 0385-4213
IS - 12
ER -