Model predictive control for demand response aggregation management system with response delay time and uncertainty model

Yutaka Iino, Takeshi Hatanaka, Masayuki Fujita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In the Smart Grid Technology, Demand Response (DR) scheme had attracted attentions as a new effective electricity supply-demand balance control method. The aim of this paper is to formulate DR aggregation management system with multiple electricity energy users as a control and optimization theory framework. Where, the demand response delay dynamics and stochastic uncertainty as behaviors in each energy user are included as the DR aggregation system model, to represent actual DR aggregation service management process in the electricity market mechanism. For the generalized formulation of the problem, the Model Predictive Optimization & Control scheme is introduced, where control performance, economical value with DR incentive, and also operational risk to fail DR target achievement are formulated. Some practical calculation procedure of dispatching DR command to each energy user as the DR aggregator is also shown.

Original languageEnglish
Title of host publicationProceedings of the SICE Annual Conference
PublisherSociety of Instrument and Control Engineers (SICE)
Pages1478-1483
Number of pages6
ISBN (Electronic)9784907764463
DOIs
Publication statusPublished - 2014 Oct 23
Externally publishedYes
Event2014 53rd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2014 - Sapporo, Japan
Duration: 2014 Sep 92014 Sep 12

Publication series

NameProceedings of the SICE Annual Conference

Conference

Conference2014 53rd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2014
CountryJapan
CitySapporo
Period14/9/914/9/12

Fingerprint

Model predictive control
Time delay
Agglomeration
Electricity
Uncertainty

Keywords

  • demand response
  • model predictive control
  • smart grid

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Iino, Y., Hatanaka, T., & Fujita, M. (2014). Model predictive control for demand response aggregation management system with response delay time and uncertainty model. In Proceedings of the SICE Annual Conference (pp. 1478-1483). [6935279] (Proceedings of the SICE Annual Conference). Society of Instrument and Control Engineers (SICE). https://doi.org/10.1109/SICE.2014.6935279

Model predictive control for demand response aggregation management system with response delay time and uncertainty model. / Iino, Yutaka; Hatanaka, Takeshi; Fujita, Masayuki.

Proceedings of the SICE Annual Conference. Society of Instrument and Control Engineers (SICE), 2014. p. 1478-1483 6935279 (Proceedings of the SICE Annual Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Iino, Y, Hatanaka, T & Fujita, M 2014, Model predictive control for demand response aggregation management system with response delay time and uncertainty model. in Proceedings of the SICE Annual Conference., 6935279, Proceedings of the SICE Annual Conference, Society of Instrument and Control Engineers (SICE), pp. 1478-1483, 2014 53rd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2014, Sapporo, Japan, 14/9/9. https://doi.org/10.1109/SICE.2014.6935279
Iino Y, Hatanaka T, Fujita M. Model predictive control for demand response aggregation management system with response delay time and uncertainty model. In Proceedings of the SICE Annual Conference. Society of Instrument and Control Engineers (SICE). 2014. p. 1478-1483. 6935279. (Proceedings of the SICE Annual Conference). https://doi.org/10.1109/SICE.2014.6935279
Iino, Yutaka ; Hatanaka, Takeshi ; Fujita, Masayuki. / Model predictive control for demand response aggregation management system with response delay time and uncertainty model. Proceedings of the SICE Annual Conference. Society of Instrument and Control Engineers (SICE), 2014. pp. 1478-1483 (Proceedings of the SICE Annual Conference).
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