This paper proposes a decentralized hierarchical price function design for charging coordination of Plug-in Electric Vehicles (PEVs) based on the reverse Stackelberg mechanism. We consider an aggregator who purchases energy from the wholesale energy market. The aggregator acts as the leader for a group of PEVs and determines the price of energy versus consumption at each hour a day as its decision function. In the followers level, the optimal charging strategies of the PEVs are coupled through the electricity price. The PEVs in a group are considered to cooperate in finding their Nash-Pareto-optimal charging strategy, by minimizing a social cost function. We propose a decentralized algorithm by combination of mean-filed control and reverse ...
This paper presents a game theoretic decentralized electric vehicle charging schedule for minimizing...
International audienceThis paper provides a Dynamic Programming (DP)approach to optimally manage the...
Defining tools and algorithms to support the decision-making process for charging electric vehicles ...
In the reverse Stackelberg mechanism, by considering a decision function for the leader rather than ...
In this paper, the problem of grid-to-vehicle energy exchange between a smart grid and plug-in elect...
In this paper, the problem of grid-to-vehicle energy exchange between a smart grid and plug-in elect...
We address the problem of charging plug-in electric vehicles (PEVs) in a decentralized way and under...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Abstract—The paper develops a novel decentralized charging control strategy for large populations of...
Abstract — As the number of charging Plug-in Electric Ve-hicles (PEVs) increase, it is crucial to co...
With the increasing scale of Electric Vehicles (EVs) connected to the grid, in order to achieve a wi...
In this paper, we deal with the charging scheduling optimization problem of electric vehicle using S...
This paper proposes a non-cooperative game pricing strategy framework by the approach of profit-shar...
Constrained charging control of large populations of Plug-in Electric Vehicles (PEVs) is addressed u...
We consider the problem of optimal charging of heterogeneous plug-in electric vehicles (PEVs). We ap...
This paper presents a game theoretic decentralized electric vehicle charging schedule for minimizing...
International audienceThis paper provides a Dynamic Programming (DP)approach to optimally manage the...
Defining tools and algorithms to support the decision-making process for charging electric vehicles ...
In the reverse Stackelberg mechanism, by considering a decision function for the leader rather than ...
In this paper, the problem of grid-to-vehicle energy exchange between a smart grid and plug-in elect...
In this paper, the problem of grid-to-vehicle energy exchange between a smart grid and plug-in elect...
We address the problem of charging plug-in electric vehicles (PEVs) in a decentralized way and under...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Abstract—The paper develops a novel decentralized charging control strategy for large populations of...
Abstract — As the number of charging Plug-in Electric Ve-hicles (PEVs) increase, it is crucial to co...
With the increasing scale of Electric Vehicles (EVs) connected to the grid, in order to achieve a wi...
In this paper, we deal with the charging scheduling optimization problem of electric vehicle using S...
This paper proposes a non-cooperative game pricing strategy framework by the approach of profit-shar...
Constrained charging control of large populations of Plug-in Electric Vehicles (PEVs) is addressed u...
We consider the problem of optimal charging of heterogeneous plug-in electric vehicles (PEVs). We ap...
This paper presents a game theoretic decentralized electric vehicle charging schedule for minimizing...
International audienceThis paper provides a Dynamic Programming (DP)approach to optimally manage the...
Defining tools and algorithms to support the decision-making process for charging electric vehicles ...