Training Method for Smart Grid Power Limitation Prediction Model of Building Air-conditioners with FastADR Signal Modulation during Normal Operation
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- Ninagawa Chuzo
- Department of Electrical and Electronic Engineering, Gifu University
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- Aoki Yoshifumi
- Department of Electrical and Electronic Engineering, Gifu University
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- Nakamura Atsushi
- Department of Electrical and Electronic Engineering, Gifu University
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- Morikawa Junji
- Mitsubishi Heavy Industries Thermal Systems, Ltd.
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- Kondo Seiji
- Mitsubishi Heavy Industries Thermal Systems, Ltd.
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- Inaba Takashi
- Mitsubishi Heavy Industries Thermal Systems, Ltd.
Bibliographic Information
- Other Title
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- ビル空調設備スマートグリッド電力抑制予測モデルの平常運転FastADR信号モジュレーション訓練法
- ビル クウチョウ セツビ スマートグリッド デンリョク ヨクセイ ヨソク モデル ノ ヘイジョウ ウンテン FastADR シンゴウ モジュレーション クンレンホウ
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Description
<p>Fast Automated Demand Response (FastADR), which controls the power consumption of customers' loads, is one of the future smart grid technologies. In this paper, a neural network modeling of the FastADR response property for the power consumption of building air-conditioners is studied. We propose an efficient training data collection method with operation condition zoning using the FastADR-like signal modulation during normal air-conditioning operation.</p>
Journal
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- IEEJ Transactions on Industry Applications
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IEEJ Transactions on Industry Applications 138 (3), 199-205, 2018
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390282679636541696
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- NII Article ID
- 130006407511
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- NII Book ID
- AN10012320
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- ISSN
- 13488163
- 09136339
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- NDL BIB ID
- 028903479
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed
