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

Yin Yao, Wenzhong Gao
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引用次数: 4

Abstract

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.
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利用粒子群优化方法缓解电动汽车蓄电池充电对配电变压器的压力
本文在Matlab中建立了插电式混合动力汽车的随机模型,研究了插电式混合动力汽车对配电变压器的影响。这款车型包括两种类型的插电式混合动力车,轿车和SUV。这两种插电式混合动力车的充电方案相同,但充电特性不同。充电功率,完全充电时间等。如果采用哑充电方式(V0G),势必会导致晚间的负荷高峰。仿真结果表明,这种规模的负荷峰值将导致配电变压器的寿命损失(LOL)增加。为了缓解负荷峰值,采用粒子群优化方法对插电式混合动力汽车的充电模式进行重新调度。优化后的配电变压器最大负荷负荷最小,充电负荷曲线更平滑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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