基于云-物联网框架的电动汽车充电站分配与调度：斑点鬣狗水母搜索优化方法

IF 3.8 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems Pub Date : 2025-03-22 DOI:10.1016/j.suscom.2025.101118

Gopal Saravanan , Ramamani Tripathy , Rayavarapu Umamaheswara Rao , Manikonda Srinivasa Seshasai

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引用次数: 0

摘要

电动汽车代表了一项技术进步，有望为减少污染和燃料消耗提供解决方案。这种电动汽车技术受到各种因素的阻碍，如电池大小、充电时间、行驶里程短、调度不均匀等。基于云的物联网（IoT）技术使电动汽车能够通过智能无线充电来规划路线和处理信息。本文介绍了斑点鬣狗水母搜索优化算法（SHJSO）用于电动汽车充电调度。最初，通过云模拟来复制充电站和电动汽车的位置。SHJSO综合考虑平均等待时间、距离、电量预测、充电成本、用户偏好、到达时间和电动汽车数量等因素对电动汽车充电进行调度。DNFN预测功率，SHJSO结合了斑点鬣狗优化（SHO）和水母搜索优化（JSO）。等待时间为27.72 s，距离为1.067 m，充电电动汽车为60辆，功率为53.67 W等指标显示了效果。与分数反馈树算法（FFTA）、智能充电调度、自我控制快速充电站管理（SC-EXP）和充电控制深度确定性策略梯度（CDDPG）方法相比，SHJSO可使电动汽车充电数量分别增加10 %、36.6 %、28.3 %和18.3 %。

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Cloud-IoT framework for EV charge station allocation and scheduling: A spotted hyena jellyfish search optimization approach

Electric Vehicles (EVs) represent a technological advancement that promises a solution to reduce pollution and fuel consumption. This EV technology is obstructed by various factors, like the size of the battery, charging time, short driving ranges, and uneven scheduling. Cloud-based Internet of Things (IoT) technology enables EVs to plan routes and process information with smart wireless charging. This study introduces the Spotted Hyena Jellyfish Search Optimization (SHJSO) for scheduling EV charges. Initially, cloud simulations are performed to replicate charging stations and EV locations. SHJSO schedules EV charges considering average waiting time, distance, power prediction, charging cost, user preference, arrival time, and the number of EVs. DNFN predicts power, and SHJSO combines Spotted Hyena Optimization (SHO) and Jellyfish Search Optimization (JSO). Metrics like waiting time is 27.72 s, distance is 1.067 m, EVs charged is 60, and power is 53.67 W show the effectiveness. Compared to Fractional Feedback Tree Algorithm (FFTA), Smart charge scheduling, Self-Controlling Express Station Management (SC-EXP), and Charging control deep deterministic policy gradient (CDDPG) methods, SHJSO increases the number of charged EVs by 10 %, 36.6 %, 28.3 %, and 18.3 %.

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来源期刊

Sustainable Computing-Informatics & Systems COMPUTER SCIENCE, HARDWARE & ARCHITECTUREC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

10.70

自引率

4.40%

发文量

142

期刊介绍： Sustainable computing is a rapidly expanding research area spanning the fields of computer science and engineering, electrical engineering as well as other engineering disciplines. The aim of Sustainable Computing: Informatics and Systems (SUSCOM) is to publish the myriad research findings related to energy-aware and thermal-aware management of computing resource. Equally important is a spectrum of related research issues such as applications of computing that can have ecological and societal impacts. SUSCOM publishes original and timely research papers and survey articles in current areas of power, energy, temperature, and environment related research areas of current importance to readers. SUSCOM has an editorial board comprising prominent researchers from around the world and selects competitively evaluated peer-reviewed papers.