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EV charging scheduling for cost and greenhouse gases emissions minimization

机译:电动汽车充电计划,以最大限度地降低成本和减少温室气体排放

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This paper investigates the potential impact of a fleet of electric vehicles charging on the cost of electricity generation, greenhouse gas emissions (GHG) and power system demand through low voltage residential demand-side management (DSM). The proposed optimisation algorithm is used to shift electric vehicles charging loads to minimize the combined impact of three key parameters: financial, environmental, and demand variability. The results show that it is effective to reshape the power demand and reduce electricity cost and GHG emissions without affecting people's driving patterns.
机译:本文研究了通过低电压住宅需求侧管理(DSM)进行充电的电动汽车车队对发电成本,温室气体排放(GHG)和电力系统需求的潜在影响。提出的优化算法用于转移电动汽车的充电负荷,以最大程度地降低三个关键参数(财务,环境和需求可变性)的综合影响。结果表明,在不影响人们的驾驶方式的情况下,重塑电力需求,降低电力成本和减少温室气体排放是有效的。

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