Stochastic modeling and scalable predictive control for automated demand response

Kobayashi, Koichi; Hiraishi, Kunihiko

International journal of robust and nonlinear control, 2021, 31(6), 2001-2017

Permalink : https://hdl.handle.net/2115/80597

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https://doi.org/10.1002/rnc.5313     54

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アクセス権
open access
URI
https://hdl.handle.net/2115/80597
タイトル
Stochastic modeling and scalable predictive control for automated demand response
著者
e-Rad_Researcher
50452115
著者名
Kobayashi, Koichi
著者名
Hiraishi, Kunihiko
言語
英語
キーワード
aggregators
automated demand response
Markov chain
model predictive control
発行日
2021-04
出版者
John Wiley & Sons
収録物名
International journal of robust and nonlinear control
巻(号)
31(6)
ページ
2001-2017
抄録
Automated demand response (ADR) is a utility program that is designed to achieve electricity conservation. An ADR program is regarded as the problem of controlling the power consumption of a set of consumers. In this article, we propose a control-theoretic approach for an ADR program. First, a mathematical model of the power consumption is proposed. This model can express complex behavior by switching a Markov chain. Its effectiveness is illustrated by modeling the power consumption of an air-conditioner. Next, a new method of model predictive control for a set of consumers is developed using the proposed model. The control strategy at each time is chosen from a given finite set by solving a mixed integer linear programming (MILP) problem. The advantage of the proposed method is that the MILP problem is scalable with respect to the number of consumers. To show its effectiveness, we present a numerical example.
資源タイプ
学術雑誌論文
出版タイプ
Version of Record
権利情報
Creative Commons Attribution 4.0 International
PISSN
1049-8923
関連情報 (isIdenticalTo)
出版社版DOI
https://doi.org/10.1002/rnc.5313