电动汽车充电和路由优化策略:综合评述

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Prabhakar Karthikeyan Shanmugam, Polly Thomas
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引用次数: 0

摘要

根据最近的研究信息,到 2045 年,电动汽车(EV)将占道路行驶车辆的 80% 以上。因此,这些车辆在电网中的渗透率也将相应提高,这对现有电网基础设施的可靠性和能源管理能力提出了挑战。随着电动汽车的出现,从电网中存储和消耗大量能源,以及根据电网需求在电动汽车中注入自备能源的新技术也在不断涌现。只有利用调度算法更优化、更高效地安排电动汽车的运行(充电/放电),一切才能顺利进行。尽管存在许多路由和充电计划计算方法,但自然启发的优化方法可能会在应对此类路由挑战中发挥关键作用。研究人员创造了多种优化调度方法,如动态编程、差分进化优化技术、协同优化调度、两阶段优化调度策略等。最优调度回顾通过综合启发式和元启发式技术,在考虑不确定性来源和不同电动汽车运行环境的同时,对电动汽车车队的运行进行了研究。本文对各种电动汽车优化调度技术和采用的算法进行了深入评述,这些技术和算法是新兴的最佳实践,如预测分析、动态路由、以用户为中心的规划、多目标优化等,反映了业界对利用先进技术、数据驱动决策和协作方法来提高电动汽车路由和充电调度的效率和可持续性的关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review
Based on information from recent research, by 2045, Electric Vehicles (EV) will dominate the roads with presence of more than 80% of its kind. Hence, these vehicles' grid level penetration will increase proportionally, which challenges the existing grid infrastructure in terms of its reliability and energy management capabilities. New techniques to store and consume massive quantities of energy from the power grid, as well as infusing the captive energy within the EV in response to grid demands, are emerging with the advent of electric vehicles. Everything could be handled smoothly only if we schedule the EV operation (charging/discharging) more optimally and efficiently using scheduling algorithms. Despite the existence of many routings and charging schedule computations, nature-inspired optimization approaches might play a critical role in responding to such routing challenges. Researchers have created several optimum scheduling approaches, such as Dynamic Programming, Differential Evolutionary Optimization Techniques, Collaborative Optimization Scheduling, Two-stage optimal scheduling strategy, and so on. The optimum schedule review examines the operation of an EV fleet while considering uncertainty sources and varied EV operating circumstances by integrating heuristic and meta-heuristic techniques. This paper exhibits a deep review on the various EV optimal scheduling techniques and adopted algorithms which are the emerging best practices like predictive analytics, dynamic routing, user centric planning, multi-objective optimization, etc. that reflect the industry's focus on leveraging advanced technologies, data-driven decision-making, and collaborative approaches to enhance the efficiency and sustainability of electric vehicle routing and charging scheduling.
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来源期刊
gazi university journal of science
gazi university journal of science MULTIDISCIPLINARY SCIENCES-
CiteScore
1.60
自引率
11.10%
发文量
87
期刊介绍: The scope of the “Gazi University Journal of Science” comprises such as original research on all aspects of basic science, engineering and technology. Original research results, scientific reviews and short communication notes in various fields of science and technology are considered for publication. The publication language of the journal is English. Manuscripts previously published in another journal are not accepted. Manuscripts with a suitable balance of practice and theory are preferred. A review article is expected to give in-depth information and satisfying evaluation of a specific scientific or technologic subject, supported with an extensive list of sources. Short communication notes prepared by researchers who would like to share the first outcomes of their on-going, original research work are welcome.
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