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Incentive-based coordinated charging control of plug-in electric vehicles at the distribution-transformer level

机译:基于激励的插电式电动汽车配电变压器协调充电控制

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Distribution utilities are becoming increasingly aware that their networks may struggle to accommodate large numbers of plug-in electric vehicles (PEVs). In particular, uncoordinated overnight charging is expected to be problematic, as the corresponding aggregated power demand exceeds the capacity of most distribution substation transformers. In this paper, a dynamical model of PEVs served by a single temperature-constrained substation transformer is presented and a centralized scheduling scheme is formulated to coordinate charging of a heterogeneous PEV fleet. We employ the dual-ascent method to derive an iterative, incentive-based and non-centralized implementation of the PEV charging algorithm, which is optimal upon convergence. Then, the distributed open-loop problem is embedded in a predictive control scheme to introduce robustness against disturbances. Simulations of an overnight charging scenario illustrate the effectiveness of the so-obtained incentive-based coordinated PEV control scheme in terms of performance and enforcing the transformer's thermal constraint.
机译:配电公司越来越意识到其网络可能难以容纳大量的插电式电动汽车(PEV)。尤其是,由于相应的合计电力需求超过了大多数配电变电站变压器的容量,预计不协调的通宵充电会带来问题。本文提出了一种由温度受限的变电站变压器服务的PEV的动力学模型,并制定了集中调度方案来协调异构PEV车队的充电。我们采用双重上升方法得出PEV充电算法的迭代,基于激励和非集中式实现,这在收敛时是最佳的。然后,将分布式开环问题嵌入到预测控制方案中,以引入针对干扰的鲁棒性。对通宵充电场景的仿真说明了如此获得的基于激励的协调式PEV控制方案在性能和加强变压器的热约束方面的有效性。

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