Linear-quadratic mean-field-type games-based stochastic model predictive control: A microgrid energy storage application

J. Barreiro-Gomez, T. E. Duncan, H. Tembine

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

Abstract

In this paper, we study the design of a stochastic predictive controller based on discrete-time mean-field-type games (MFTG-SPC) involving an arbitrary number of decision makers. We consider a dynamical system described by a stochastic difference equation that includes mean-field terms, e.g., the expected value for both the system state and control inputs. In addition, the cost function incorporates the mean and variance of both system state and control inputs. We provide a semi-explicit solution for the optimization problem that is behind the predictive controller. Finally, we present some simulations over a microgrid application consisting of the energy storage problem.

Original languageEnglish (US)
Title of host publication2019 American Control Conference, ACC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3224-3229
Number of pages6
ISBN (Electronic)9781538679265
DOIs
StatePublished - Jul 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: Jul 10 2019Jul 12 2019

Publication series

NameProceedings of the American Control Conference
Volume2019-July
ISSN (Print)0743-1619

Conference

Conference2019 American Control Conference, ACC 2019
CountryUnited States
CityPhiladelphia
Period7/10/197/12/19

Keywords

  • Direct method
  • Mean-field-type games
  • Mean-variance minimization
  • Semiexplicit solution
  • Stochastic predictive control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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