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Design and Value Evaluation of Demand Response Based on Model Predictive Control

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Title: Design and Value Evaluation of Demand Response Based on Model Predictive Control
Authors: Miyazaki, Kodai Browse this author
Kobayashi, Koichi Browse this author →KAKEN DB
Azuma, Shun-ichi Browse this author →KAKEN DB
Yamaguchi, Nobuyuki Browse this author
Yamashita, Yuh Browse this author →KAKEN DB
Keywords: Aggregator
demand response
energy management systems
model predictive control
Issue Date: Aug-2019
Publisher: IEEE (Institute of Electrical and Electronics Engineers)
Journal Title: IEEE transactions on industrial informatics
Volume: 15
Issue: 8
Start Page: 4809
End Page: 4818
Publisher DOI: 10.1109/TII.2019.2920373
Abstract: Demand response is one of the key technologies in energy management systems, and is defined as the changes in electricity usage of end-use consumers that occur as a result of changing the electricity price, the incentive, etc. In this paper, a design method for demand response is proposed based on model predictive control. Model predictive control is a control method using prediction by a mathematical model, which is used for controlling systems with constraints. Because constraints are considered in the design of demand response, it is appropriate to utilize model predictive control. First, the model-predictive-based demand response problem is formulated. By solving this problem, demand response is performed based on the actual power consumption. Next, constraints on the peak shift effect are imposed, and an event-triggered mechanism is introduced. Third, the effects of demand response are theoretically analyzed. Finally, the economic value of the proposed approach is evaluated by numerical simulations. The proposed approach provides us a fundamental result for the design of demand response and aggregators such as retailers.
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Type: article
URI: http://hdl.handle.net/2115/75444
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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