A Mean Field Game Approach for Distributed Control of Thermostatic Loads Acting in Simultaneous Energy-Frequency Response Markets

Antonio De Paola; Vincenzo Trovato; David Angeli; Goran Strbac

doi:10.1109/TSG.2019.2895247

A Mean Field Game Approach for Distributed Control of Thermostatic Loads Acting in Simultaneous Energy-Frequency Response Markets

Antonio De Paola, Vincenzo Trovato, David Angeli, Goran Strbac

Research output: Contribution to journal › Article › peer-review

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Abstract

This paper proposes a novel distributed solution for the operation of large populations of thermostatically controlled loads (TCLs) providing frequency support. A game-theory framework is adopted, modeling the TCLs as price-responsive rational agents that schedule their energy consumption and allocate frequency response provision in order to minimize their operational costs. The novelty of this work lies in the use of mean field games to abstract the complex interactions of large numbers of TCLs with the grid and in the introduction of an innovative market structure, envisioning distinct price signals for electricity and response. Differently from previous approaches, such prices are not designed ad hoc but are derived instead from an underlying system scheduling model.

Original language	English
Article number	8625448
Pages (from-to)	5987-5999
Number of pages	13
Journal	IEEE Transactions on Smart Grid
Volume	10
Issue number	6
Early online date	24 Jan 2019
DOIs	https://doi.org/10.1109/TSG.2019.2895247
Publication status	Published - 30 Nov 2019

Keywords

Game theory
distributed control
load management
power system control
thermal energy storage

ASJC Scopus subject areas

Computer Science(all)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TSG.2019.2895247

DePaolaTrovatoAngeliStrbac_TCLCoordinationMFG_FinalManuscript_OnlineVersion
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Accepted author manuscript, 1.76 MB

Cite this

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note = "Funding Information: Manuscript received September 13, 2018; revised December 18, 2018; accepted January 17, 2019. Date of publication January 24, 2019; date of current version October 30, 2019. This work was supported by the Leverhulme Trust under Grant ECF-2016-394. Paper no. TSG-01344-2018. (Corresponding author: Antonio De Paola.) A. De Paola is with the Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, U.K. (e-mail: a.de.paola@bath.ac.uk). Publisher Copyright: {\textcopyright} 2010-2012 IEEE.",

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A Mean Field Game Approach for Distributed Control of Thermostatic Loads Acting in Simultaneous Energy-Frequency Response Markets

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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