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Mitigation of the Impact of High Plug-in Electric Vehicle Penetration on Residential Distribution Grid Using Smart Charging Strategies

机译:使用智能充电策略缓解高插电式电动车普及率对住宅配电网的影响

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Vehicle electrification presents a great opportunity to reduce transportation greenhouse gas emissions. The greater use of plug-in electric vehicles (PEVs), however, puts stress on local distribution networks. This paper presents an optimal PEV charging control method integrated with utility demand response (DR) signals to mitigate the impact of PEV charging to several aspects of a grid, including load surge, distribution accumulative voltage deviation, and transformer aging. To build a realistic PEV charging load model, the results of National Household Travel Survey (NHTS) have been analyzed and a stochastic PEV charging model has been defined based on survey results. The residential distribution grid contains 120 houses and is modeled in GridLAB-D. Co-simulation is performed using Matlab and GridLAB-D to enable the optimal control algorithm in Matlab to control PEV charging loads in the residential grid modeled in GridLAB-D. Simulation results demonstrate the effectiveness of the proposed optimal charging control method in mitigating the negative impacts of PEV charging on the residential grid.
机译:车辆电气化为减少运输温室气体排放提供了巨大的机会。但是,插电式电动汽车(PEV)的更多使用给本地配电网络带来了压力。本文提出了一种与公用事业需求响应(DR)信号集成的最佳PEV充电控制方法,以减轻PEV充电对电网几个方面的影响,包括负载浪涌,分布累积电压偏差和变压器老化。为了建立现实的PEV充电负荷模型,分析了全国家庭出行调查(NHTS)的结果,并根据调查结果定义了随机PEV充电模型。住宅配电网格包含120栋房屋,并以GridLAB-D建模。使用Matlab和GridLAB-D进行协同仿真,以使Matlab中的最佳控制算法能够控制以GridLAB-D建模的住宅电网中的PEV充电负载。仿真结果证明了所提出的最佳充电控制方法在减轻PEV充电对住宅电网的负面影响方面的有效性。

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