Mean field constrained charging policy for large populations of plug-in electric vehicles
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Date
2014Type
- Conference Paper
ETH Bibliography
yes
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Abstract
Constrained charging control of large populations of Plug-in Electric Vehicles (PEVs) is addressed using mean field game theory. We consider PEVs as heterogeneous agents, with different charging constraints (plug-in times and deadlines). The agents minimize their own charging cost, but are weakly coupled by the common electricity price. We propose an iterative algorithm that, in the case of an infinite population, converges to the Nash equilibrium associated with a related decentralized optimization problem. In this way we approximate the centralized optimal solution, which in the unconstrained case fills the overnight power demand valley, via a decentralized procedure. The benefits of the proposed formulation in terms of convergence behavior and overall charging cost are illustrated through numerical simulations. Show more
Publication status
publishedExternal links
Book title
2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014)Pages / Article No.
Publisher
IEEEEvent
Subject
Large-scale systems; Game theoryOrganisational unit
03751 - Lygeros, John / Lygeros, John
08814 - Smith, Roy (Tit.-Prof.)
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ETH Bibliography
yes
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