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Daily Peak Load Forecasting by Taguchi's T Method
Author(s) -
NEGISHI SHINTARO,
MORIMOTO YUSUKE,
TAKAYAMA SATOSHI,
ISHIGAME ATSUSHI
Publication year - 2017
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.22988
Subject(s) - mahalanobis distance , taguchi methods , nonlinear system , multivariate statistics , probabilistic forecasting , computer science , statistics , mathematics , artificial intelligence , data mining , physics , quantum mechanics , probabilistic logic
SUMMARY In this paper, a new technique of daily peak load forecasting is proposed. At first, we propose nonlinear correction T method as improvement technique of T method that is one of the multivariate analysis techniques, called Mahalanobis–Taguchi (MT) system, suggested in Quality Control. Moreover, we examine the daily peak load forecasting technique, which is based on data in the last year on a forecasting day, by T method and nonlinear correction T method. Furthermore, we examine the technique, which is based on the data of most recent several weeks of a forecasting day, by the T method and Nonlinear correction T method. In addition, the effectiveness of the proposed method by comparing the multiple regression analysis is discussed.