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Probabilistic reliability evaluation of distribution systems considering the spatial and temporal distribution of electric vehicles

机译:考虑电动汽车时空分布的配电系统概率可靠性评估

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摘要

Fast-growing electric vehicles load can impose various reliability concerns and peak demand increase in electric power systems, particularly distribution networks. From a power system point of view, electric vehicles can be considered as random moving loads. A new probabilistic approach is, therefore, proposed in this paper to evaluate the impact of electric vehicles on the reliability performance of power distribution systems. A two-layer stochastic electric vehicle charging demand estimation model is proposed. The model comprises of a traffic layer representing the spatial-temporal distributions of electric vehicles and an electrical network layer describing the electric vehicles charging demand. A Dynamic Hidden Markov Model is used to capture the electric vehicle movements in the traffic layer. Electric vehicle travel patterns and charging demand are simulated using a sequential Monte Carlo simulation approach considering the vehicle distance traveled, the type of charging location and the driver class. The proposed approach and the models are used to perform reliability studies on an example test system, and a series of analysis results are presented.
机译:快速增长的电动汽车负载会带来各种可靠性问题,并且电力系统(尤其是配电网络)的峰值需求会增加。从电力系统的角度来看,电动汽车可被视为随机移动负载。因此,本文提出了一种新的概率方法,以评估电动汽车对配电系统可靠性性能的影响。提出了一种两层随机电动汽车充电需求估算模型。该模型包括代表电动汽车时空分布的交通层和描述电动汽车充电需求的电网层。动态隐马尔可夫模型用于捕获电动汽车在交通层的运动。考虑到行进的车辆距离,充电位置的类型和驾驶员等级,使用顺序蒙特卡洛模拟方法对电动汽车的行驶模式和充电需求进行了模拟。所提出的方法和模型用于在示例测试系统上进行可靠性研究,并给出了一系列分析结果。

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