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Remote Monitoring Integrated State Variables for AR Model Prediction of Daily Total Building Air‐Conditioning Power Consumption
Author(s) -
Ninagawa Chuzo,
Sato Tomotaka
Publication year - 2010
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20580
Subject(s) - autoregressive model , power consumption , air conditioning , consumption (sociology) , state (computer science) , set (abstract data type) , power (physics) , variable (mathematics) , computer science , environmental science , reliability engineering , engineering , statistics , mathematics , mechanical engineering , mathematical analysis , social science , physics , algorithm , quantum mechanics , sociology , programming language
It is extremely difficult to predict daily accumulated power consumption of the entire building air‐conditioning facilities because of a huge number of variables. We propose new integrated state variables, i.e. the daily operation amount and the daily operation‐capacity‐weighted average set temperature. Taking advantage of a remote monitoring technology, time series data of the integrated state variables were collected and an autoregressive (AR) model prediction for the daily total power consumption has been tried. © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.