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Relieving the pressure of electric vehicle battery charging on distribution transformer via particle swarm optimization method

机译:通过粒子群优化方法减轻配电变压器上电动汽车电池的充电压力

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In this paper, a stochastic model of plug-in hybrid electric vehicle (PHEV) is developed in Matlab to investigate its impact on distribution transformer. Two types of PHEVs are included in this model, sedan and SUV. These two types of PHEV share the same charging schedule, but possess different charging characteristics. Charging power, Full-charge time for example. If dumb charging method (V0G) is applied, that will surely result in a load peak in the evening. From the simulation results, it is proven that this scale of load peak will lead to the increase of loss of life (LOL) of distribution transformer. To mitigate the load peak, particle swarm optimization method is performed to reschedule the charging pattern of each PHEV. Eventually, the LOL of distribution transformer is minimized with smoother charging load curve after optimization.
机译:本文在Matlab中建立了插电式混合动力汽车(PHEV)的随机模型,以研究其对配电变压器的影响。该模型包括两种类型的PHEV:轿车和SUV。这两种类型的PHEV共享相同的充电时间表,但具有不同的充电特性。充电功率,例如充满电时间。如果采用哑式充电方式(V0G),则肯定会导致晚上出现负载高峰。从仿真结果可以证明,这种负载峰值的规模将导致配电变压器寿命损失(LOL)的增加。为了减轻负荷峰值,执行了粒子群优化方法以重新安排每个插电式混合电动汽车的充电模式。最终,优化后的配电变压器的LOL最小,充电负载曲线更平滑。

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