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- Title
Modulation training method of prediction model for smart grid FastADR power limitation of building air-conditioners.
- Authors
Ninagawa, Chuzo; Nakamura, Atsushi; Morikawa, Junji
- Abstract
Fast automated demand response (FastADR) of building air-conditioners is a future smart grid demand-side technology. Neural network models will be useful to predict the power limitation result of the FastADR. However, neural networks require training data, which are collected by the experimental air-conditioning operations. In this letter, we propose a new training data collection method in which the FastADR-like signal is modulated into the normal air-conditioning operations. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
- Subjects
ARTIFICIAL neural networks; ACQUISITION of data; ELECTRICAL engineers; AIR conditioning; SIGNAL processing
- Publication
IEEJ Transactions on Electrical & Electronic Engineering, 2018, Vol 13, Issue 2, p343
- ISSN
1931-4973
- Publication type
Article
- DOI
10.1002/tee.22533