配电系统中电动汽车集成的数据驱动概率评估：充电行为、承载能力和电网影响

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks Pub Date : 2025-06-20 DOI:10.1016/j.segan.2025.101770

Priscila Costa Nascimento , Silvia Trevisan , Monika Topel , Björn Laumert

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引用次数: 0

摘要

脱碳政策大大增加了全球插电式电动汽车（pev）的采用。本文开发并应用了一种概率方法来评估瑞典斯德哥尔摩县实际低压配电系统（DS）中pev的大规模集成。该框架采用蒙特卡罗模拟来捕捉驾驶员行为、每日距离、充电开始时间和车辆分配等方面的不确定性。它的主要贡献是：(i)一个可复制的数据驱动的蒙特卡洛框架，它将DS运营商（DSO）的负载数据与旅行习惯统计数据合并在一起；（ii）现实的收费概况生成；（iii）证明，增加价格信号加上网络约束几乎可以使托管容量翻倍，并降低用户成本；（iv）系统地比较了不受控制的收费与受控制的收费，从而澄清了技术-经济权衡。分析认为PEV渗透水平(Pls) -定义为拥有PEV的客户单位（cu）在所有永久访问乘用车的客户单位中所占的百分比-高达100% %。关键性能指标，在第95个百分位数进行分析，以代表接近最坏情况的结果，包括电压分布、变压器和线路负载、总峰值功率、技术损耗和托管容量。不受控制的充电提高了峰值需求，导致电压和过载违规，使托管容量上限为Pl 27 %。加上峰值需求上限的价格信号，可将运力提升至Pl 49 %，超载减半，并将收费成本降低约10 %。夜间充电可达Pl 49 %；在Pl 75 %以上，需要早晨充电以保持电能质量在限制范围内。该方法具有广泛的可复制性，并为市政当局、dso和政策制定者提供了可操作的指导，以确保向电气化交通的可持续和经济有效过渡，同时保持可靠的DS运行。

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Data-driven probabilistic evaluation of electric-vehicle integration in distribution systems: charging behavior, hosting capacity, and grid impact

Decarbonization policies have significantly increased the adoption of plug-in electric vehicles (PEVs) worldwide. This paper develops and applies a probabilistic method for assessing large-scale integration of PEVs in a real low voltage distribution system (DS) in Stockholm County, Sweden. The framework employs Monte Carlo simulations to capture uncertainties in driver behaviors, daily distances, charging start times, and vehicle allocation. Its key contributions are: (i) a replicable data-driven Monte Carlo framework that merges DS operator (DSO) load data with travel habit statistics, (ii) realistic charging-profile generation, (iii) demonstrate that adding price signals plus a network constraint almost doubles hosting capacity and cuts user costs, and (iv) a systematic comparison of uncontrolled versus controlled charging that clarifies technical-economic trade-offs. The analysis considers PEV penetration levels (

P l

s)—defined as the percentage of customer units (CUs) with a PEV among all CUs with permanent access to a passenger vehicle—up to 100 %. Key performance indicators, analyzed at the

95^{t h}

percentile to represent near-worst-case outcomes, include voltage profiles, transformer and line loading, aggregated peak power, technical losses, and hosting capacity. Uncontrolled charging raises peak demand, causing voltage and overload violations that cap hosting capacity at

P l

 27 %. Adding price signals with a peak demand cap lifts capacity to

P l

 49 %, halves overloads, and lowers charging costs by about 10 %. Night-time charging suffices up to

P l

 49 %; above

P l

 75 %, morning charging is needed to keep power quality within limits. The method is broadly replicable and offers actionable guidance for municipalities, DSOs, and policymakers seeking to ensure a sustainable and cost-effective transition toward electrified transportation while maintaining reliable DS operation.

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来源期刊

Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology

CiteScore

7.90

自引率

13.00%

发文量

206

审稿时长

49 days

期刊介绍： Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.