耦合共享自主电动汽车和电网的优化管理:可再生能源集成的潜力

IF 7.6 1区 工程技术 Q1 TRANSPORTATION SCIENCE & TECHNOLOGY
Xianyi Yang , Adam Abdin , Jakob Puchinger
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引用次数: 0

摘要

共享自主电动汽车(SAEV)在未来的交通运输中举足轻重,与电网的整合既带来了希望,也带来了挑战。这种共生关系通过车辆对电网(V2G)服务增强了电力系统的灵活性、稳定性和可靠性,并优化了运输效率。然而,这也扩大了高峰期对强大充电基础设施和电力的需求。本文提出了一种采用后退视界优化方法的框架,用于管理 SAEV 的流动性和充电动态。该模型侧重于在确保电网稳定的同时最大限度地提高交通服务质量,利用滚动视平线算法满足动态的出行请求和发电量。值得注意的是,该研究探索了 SAEV 在加强可再生能源(RES)与电网整合方面的潜力。我们的研究旨在为政策制定者和系统规划者提供一个强大的工具,以打造高效、可持续的未来城市交通和能源系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal management of coupled shared autonomous electric vehicles and power grids: Potential of renewable energy integration

Shared Autonomous Electric Vehicles (SAEVs) are pivotal for future transportation, offering both promise and challenges upon integration with the power grid. This symbiosis augments power system flexibility, stability and reliability through Vehicle-to-Grid (V2G) services, and optimize transportation efficiency. However, it amplifies the demand for robust charging infrastructure and electricity power during peak periods. This paper proposes a framework employing a sequential receding horizon optimization approach to manage SAEV mobility and charging dynamics. Focused on maximizing transportation service quality while ensuring power grid stability, the model accommodates dynamic trip requests and electricity generation, utilizing a rolling horizon algorithm. Notably, the study explores the potential of SAEVs in fortifying the integration of renewable energy resources (RES) into the power grid. Our research strives to equip policymakers and system planners with a robust tool for crafting efficient and sustainable future urban transportation and energy systems.

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来源期刊
CiteScore
15.80
自引率
12.00%
发文量
332
审稿时长
64 days
期刊介绍: Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.
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