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Real-time coordinated management of PHEVs at residential level via MDPs and game theory

机译:通过MDP和博弈论实时协调PHEVS的PHEVS

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This paper proposes a novel Markov decision process (MDP) with dynamic transition probabilities for the stochastic modeling of the charging process of plug-in hybrid electric vehicles (PHEVs). In the proposed dynamic MDP, PHEVs can be controlled in such a way that the effectiveness of the control strategy is maintained in the presence of uncertainties such as early departure events. Then a game theory based decentralized system is formulated to coordinate the PHEVs fleet in a residential network. The authors also proposed a decentralized coordinated optimization (DCO) algorithm to solve the formulated Nash game. Various simulations are carried out to verify the effectiveness of the proposed DCO approach. The results show that the DCO approach is robust in the face of uncertainties and is effective in enhancing both power quality and economic profits.
机译:本文提出了一种新的马尔可夫决策过程(MDP),具有动态转换概率,用于插入式混合动力电动车(PHEVS)的充电过程的随机模型。 在所提出的动态MDP中,可以以这样的方式控制PHEV,使得控制策略的有效性保持在存在不确定性,例如早期离开事件的情况下。 然后,基于博弈论的分散系统被配制成在住宅网络中协调PHEVS车队。 作者还提出了一种分散的协调优化(DCO)算法来解决配制的纳什游戏。 进行各种模拟以验证所提出的DCO方法的有效性。 结果表明,在面对不确定性方面,DCO方法是强大的,有效地提高了电能质量和经济利润。

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