7,620 research outputs found
Charging Games in Networks of Electrical Vehicles
In this paper, a static non-cooperative game formulation of the problem of
distributed charging in electrical vehicle (EV) networks is proposed. This
formulation allows one to model the interaction between several EV which are
connected to a common residential distribution transformer. Each EV aims at
choosing the time at which it starts charging its battery in order to minimize
an individual cost which is mainly related to the total power delivered by the
transformer, the location of the time interval over which the charging
operation is performed, and the charging duration needed for the considered EV
to have its battery fully recharged. As individual cost functions are assumed
to be memoryless, it is possible to show that the game of interest is always an
ordinal potential game. More precisely, both an atomic and nonatomic versions
of the charging game are considered. In both cases, equilibrium analysis is
conducted. In particular, important issues such as equilibrium uniqueness and
efficiency are tackled. Interestingly, both analytical and numerical results
show that the efficiency loss due to decentralization (e.g., when cost
functions such as distribution network Joule losses or life of residential
distribution transformers when no thermal inertia is assumed) induced by
charging is small and the corresponding "efficiency", a notion close to the
Price of Anarchy, tends to one when the number of EV increases.Comment: 8 pages, 4 figures, keywords: Charging games - electrical vehicle -
distribution networks - potential games - Nash equilibrium - price of anarch
Nash and Wardrop equilibria in aggregative games with coupling constraints
We consider the framework of aggregative games, in which the cost function of
each agent depends on his own strategy and on the average population strategy.
As first contribution, we investigate the relations between the concepts of
Nash and Wardrop equilibrium. By exploiting a characterization of the two
equilibria as solutions of variational inequalities, we bound their distance
with a decreasing function of the population size. As second contribution, we
propose two decentralized algorithms that converge to such equilibria and are
capable of coping with constraints coupling the strategies of different agents.
Finally, we study the applications of charging of electric vehicles and of
route choice on a road network.Comment: IEEE Trans. on Automatic Control (Accepted without changes). The
first three authors contributed equall
Competitive Charging Station Pricing for Plug-in Electric Vehicles
This paper considers the problem of charging station pricing and plug-in
electric vehicles (PEVs) station selection. When a PEV needs to be charged, it
selects a charging station by considering the charging prices, waiting times,
and travel distances. Each charging station optimizes its charging price based
on the prediction of the PEVs' charging station selection decisions and the
other station's pricing decision, in order to maximize its profit. To obtain
insights of such a highly coupled system, we consider a one-dimensional system
with two competing charging stations and Poisson arriving PEVs. We propose a
multi-leader-multi-follower Stackelberg game model, in which the charging
stations (leaders) announce their charging prices in Stage I, and the PEVs
(followers) make their charging station selections in Stage II. We show that
there always exists a unique charging station selection equilibrium in Stage
II, and such equilibrium depends on the charging stations' service capacities
and the price difference between them. We then characterize the sufficient
conditions for the existence and uniqueness of the pricing equilibrium in Stage
I. We also develop a low complexity algorithm that efficiently computes the
pricing equilibrium and the subgame perfect equilibrium of the two-stage
Stackelberg game.Comment: 15 pages, 21 figure
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy
management mechanism for the smart grid that enables each prosumer of the
network to participate in energy trading with one another and the grid. This
poses a significant challenge in terms of modeling the decision-making process
of each participant with conflicting interest and motivating prosumers to
participate in energy trading and to cooperate, if necessary, for achieving
different energy management goals. Therefore, such decision-making process
needs to be built on solid mathematical and signal processing tools that can
ensure an efficient operation of the smart grid. This paper provides an
overview of the use of game theoretic approaches for P2P energy trading as a
feasible and effective means of energy management. As such, we discuss various
games and auction theoretic approaches by following a systematic classification
to provide information on the importance of game theory for smart energy
research. Then, the paper focuses on the P2P energy trading describing its key
features and giving an introduction to an existing P2P testbed. Further, the
paper zooms into the detail of some specific game and auction theoretic models
that have recently been used in P2P energy trading and discusses some important
finding of these schemes.Comment: 38 pages, single column, double spac
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