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An approximate dynamic programming approach for coordinated charging control at vehicle-to-grid aggregator Xu, Jinbiao

Abstract

A vehicle-to-grid (V2G) aggregator is an agent between the power grid and the plug-in hybrid electrical vehicles (PHEVs). In this thesis, we study the coordinated charging control at a V2G aggregator. The coordinated charging control brings the advantages of minimizing the charging cost and reducing the power losses, by coordinating the control sequences of a group of PHEVs. On one hand, the lower cost of charging gives the users of PHEVs an incentive to cooperate. On the other hand, with an increasing popularity of PHEVs, the impact on the power distribution grid such as power losses should be of concern to the aggregator. To this end, we investigate the tradeoffs between reducing the charging cost and the power losses. We formulate the coordinated charging control as a dynamic programming problem, given the planned schedules of all the vehicles at an aggregator. As an inherent property of a V2G aggregator, we enable bidirectional electric power flows between PHEVs and the power grid. Due to the curse of dimensionality, we apply an approximate dynamic programming approach to decrease the dimensionality of both the state space and control space. Simulation results show that coordinated charging control can reduce both the total charging cost and the aggregated power losses significantly, compared with the uncoordinated control where every vehicle starts charging as soon as it is plugged in. We also show that the charging control with bidirectional power flows outperforms remarkably the one with unidirectional flows.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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