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Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
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Stochastic modeling and scalable predictive control for automated demand response
This item is licensed under:Creative Commons Attribution 4.0 International
| Title: | Stochastic modeling and scalable predictive control for automated demand response |
| Authors: | Kobayashi, Koichi Browse this author →KAKEN DB | | Hiraishi, Kunihiko Browse this author |
| Keywords: | aggregators | | automated demand response | | Markov chain | | model predictive control |
| Issue Date: | Apr-2021 |
| Publisher: | John Wiley & Sons |
| Journal Title: | International journal of robust and nonlinear control |
| Volume: | 31 |
| Issue: | 6 |
| Start Page: | 2001 |
| End Page: | 2017 |
| Publisher DOI: | 10.1002/rnc.5313 |
| Abstract: | 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. |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| Type: | article |
| URI: | http://hdl.handle.net/2115/80597 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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