Electrical Vehicles in the Smart Grid: A Mean Field Game Analysis

Couillet, Romain; Perlaza, Samir M.; Tembiné, Hamidou; Debbah, Mérouane

doi:10.1109/jsac.2012.120707

Cited by 144 publications

(101 citation statements)

References 16 publications

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“…In other words, each appliance regulates automatically and in a decentralized fashion its power demand based on the mains frequency. A similar concept characterizes a recent literature on "load control" in power systems [12,14,26,28,37]. In particular, [12] surveys issues related to the redistribution of the load away from peak hours and the design of decentralized strategies to produce a predefined load trajectory (see also [14]).…”

Section: Introductionmentioning

confidence: 86%

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Mean-Field Games and Dynamic Demand Management in Power Grids

Bagagiolo

Bauso

2013

Dyn Games Appl

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This paper applies mean field game theory to dynamic demand management. For a large population of electrical heating or cooling appliances (called agents), we provide a mean field game that guarantees desynchronization of the agents thus improving the power network resilience. Second, for the game at hand, we exhibit a mean field equilibrium, where each agent adopts a bang-bang switching control with threshold placed at a nominal temperature. At the equilibrium, through an opportune design of the terminal penalty, the switching control regulates the mean temperature (computed over the population) and the mains frequency around the nominal value. To overcome Zeno phenomena we also adjust the bang-bang control by introducing a thermostat. Third, we show that the equilibrium is stable in the sense that all agents' states, initially at different values, converge to the equilibrium value or remain confined within a given interval for an opportune initial distribution.

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Section: Introductionmentioning

confidence: 86%

“…This paper applies mean field game theory to dynamic demand management in the same spirit as [14,37]. The latter is a recent and promising research area aiming at improving resilience in power networks [3,15,16].…”

Section: Introductionmentioning

confidence: 99%

Mean-Field Games and Dynamic Demand Management in Power Grids

Bagagiolo

Bauso

2013

Dyn Games Appl

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“…Some studies have tested methods and operation models in advanced countries as well as comparing various models in order to suggest reasonable approaches to the development of vehicle charging facilities in their own countries [11]. Others have analyzed the relationship among stakeholders in electric vehicle charging facility construction and operation projects from the perspective of game theory, which showed that the level of support from the government as well as the charging prices may affect the provision of charging facilities [12][13][14]. In addition, the layout of charging facilities [15][16][17] and business operation models have been analyzed [7].…”

Section: Introductionmentioning

confidence: 99%

Innovative Application of the Public–Private Partnership Model to the Electric Vehicle Charging Infrastructure in China

Yang

Long

et al. 2016

Sustainability

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Abstract:The electric vehicle charging infrastructure is in the initial development period in China, where there is an imbalanced supply and demand structure, an increasingly mature institutional environment, and an imperfect support system. The infrastructure is important for supplying energy to electric vehicles, and it needs to be provided in a reasonable manner with a moderately advanced layout. Due to large-scale investment, unclear financing rights and responsibilities, a single participant, interlinked risks, and other factors, "absence" and "dislocation" of the charging infrastructure coexist. The public-private partnership (PPP) model is an effective supply path for the infrastructure. Thus, introducing the PPP model into the charging infrastructure can leverage social capital, eases the burden on local finance, enhances the level of project management and profitability, and reduces construction and operation risks. For the participant level of PPP projects in the charging infrastructure, the present study elucidates the support mechanisms required by the government, social capital, and intermediaries in order to construct an effective charging infrastructure in China.

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“…The goal was to obtain ancillary service to help regulate the power grid, as in many prior works [2], [11].…”

Section: Introductionmentioning

confidence: 99%

Passive dynamics in mean field control

Bušíć¹,

Meyn²

2014

53rd IEEE Conference on Decision and Control

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Abstract-Mean-field models are a popular tool in a variety of fields. They provide an understanding of the impact of interactions among a large number of particles or people or other "self-interested agents", and are an increasingly popular tool in distributed control.This paper considers a particular randomized distributed control architecture introduced in our own recent work. In numerical results it was found that the associated mean-field model had attractive properties for purposes of control. In particular, when viewed as an input-output system, its linearization was found to be minimum phase.In this paper we take a closer look at the control model. The results are summarized as follows:(i) The Markov Decision Process framework of Todorov is extended to continuous time models, in which the "control cost" is based on relative entropy. This is the basis of the construction of a family of Markovian generators, parameterized by a scalar ζ ∈ R. (ii) A decentralized control architecture is proposed in which each agent evolves as a controlled Markov process. A central authority broadcasts a common control signal {ζ t } to each agent. The central authority chooses {ζ t } based on an aggregate scalar output of the Markovian agents. This is the basis of the mean field model. (iii) Provided the control-free system (with ζ ≡ 0) is a reversible Markov process, the following identity holds for the transfer function G obtained from the linearization,where the right hand side denotes the power spectral density for the output of any one of the individual Markov processes (with ζ ≡ 0).

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Electrical Vehicles in the Smart Grid: A Mean Field Game Analysis

Cited by 144 publications

References 16 publications

Mean-Field Games and Dynamic Demand Management in Power Grids

Mean-Field Games and Dynamic Demand Management in Power Grids

Innovative Application of the Public–Private Partnership Model to the Electric Vehicle Charging Infrastructure in China

Passive dynamics in mean field control

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