A resilience-oriented pre-positioning approach for electric vehicle routing and scheduling in coupled energy and transport sectors

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Sustainable Energy Grids & Networks Pub Date : 2024-07-24 DOI:10.1016/j.segan.2024.101484
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Abstract

High-impact low-probability (HILP) events have occurred more frequently than before and caused severe damage to conventional power systems. Energy hubs (EHs) consist of various distributed energy resources (DERs) for energy generation, conversion and storage across different sectors. The high energy integration of EH systems makes them more robust under extreme events than traditional power systems. In addition, the large penetration of electric vehicles (EVs) has been witnessed in modern energy systems due to their significant benefits in accelerating transport electrification and reducing carbon emissions. Due to the characteristics of mobility and flexibility, EVs can be utilised as mobile energy resources in coupled energy and transport sectors and shift energy between different regions via effective routing and scheduling behaviours. In this context, this paper proposes a resilient-oriented pre-positioning approach for the routing and scheduling of multiple EVs in a coupled energy-transport system, where the energy system includes multiple EHs across both electricity and heat sectors. To simulate real-world scenarios, uncertainties associated with renewable generation, load profiles, and EV commuting time as well as contingencies related to component failures are incorporated into the proposed pre-positioning approach via stochastic programming. Extensive case studies are carried out based on an EH system including three EHs and five EVs, which illustrate that EVs can coordinate with static DERs in the system and perform energy shifting between different EHs via appropriate routing and scheduling behaviours. Additionally, results demonstrate that the proposed pre-positioning approach can achieve higher resilience level and ensure the supply continuity of critical loads.

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在能源和交通耦合领域采用以弹性为导向的电动汽车路由和调度预定位方法
高影响低概率(HILP)事件比以往发生得更为频繁,对传统电力系统造成了严重破坏。能源中枢(EH)由各种分布式能源资源(DER)组成,用于不同领域的能源生产、转换和存储。与传统电力系统相比,EH 系统的高能量集成使其在极端事件中更加稳健。此外,由于电动汽车(EV)在加速交通电气化和减少碳排放方面具有显著优势,因此在现代能源系统中的普及率很高。由于电动汽车具有移动性和灵活性的特点,因此可作为移动能源资源用于能源和交通耦合领域,并通过有效的路由和调度行为在不同区域之间转移能源。在此背景下,本文提出了一种以弹性为导向的预定位方法,用于在能源-交通耦合系统中对多辆电动汽车进行路由和调度,其中能源系统包括电力和热力部门的多辆电动汽车。为了模拟真实世界的场景,通过随机编程将与可再生能源发电、负荷曲线和电动汽车通勤时间相关的不确定性以及与组件故障相关的突发事件纳入到所提出的预定位方法中。基于一个包括三个 EH 和五个电动汽车的 EH 系统进行了广泛的案例研究,结果表明电动汽车可以与系统中的静态 DER 相协调,并通过适当的路由和调度行为在不同的 EH 之间进行能量转换。此外,研究结果表明,建议的预定位方法可以实现更高的弹性水平,并确保关键负载的供电连续性。
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来源期刊
Sustainable Energy Grids & Networks
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.
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