基于鸡群优化的电动汽车充电站多目标运行启发式方法

IF 9 1区工程技术 Q1 ENERGY & FUELS

Energy Pub Date : 2024-11-09 DOI:10.1016/j.energy.2024.133749

Sulabh Sachan

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引用次数: 0

摘要

温室气体排放和高昂的汽车运营成本是普遍存在的问题，这主要是由大量使用化石燃料的传统汽车造成的。这促使许多汽车制造商转向电动汽车（EV）。然而，电动汽车由于需要为电池重新充电，因此对电网产生了很大影响。本研究引入了一种有效的多目标函数，利用鸡群优化（CSO）为配电网络中的充电站（CS）执行最佳操作。其目的是减少功率损耗、平均电压偏差指数（AVDI）、电压稳定指数（VSI）和谐波畸变的影响。模拟在 69 总线径向配电网络上进行。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Heuristics for multi-objective operation of EV charging stations based on Chicken Swarm Optimization

The emissions of greenhouse gasses and high vehicle operating cost are the widespread issues, majorly derived by the large number of conventional fossil-fuel based vehicles. This had led many automobile manufacturers to move towards electric vehicles (EVs). However, EVs significantly impact the power grid because of the energy needed to re-energize their batteries. This study introduces an effective multi-objective function that utilizes Chicken Swarm Optimization (CSO) to perform the optimal operation for the Charging Stations (CSs) within the distribution network. The aim here is to reduce the power losses, the average voltage deviation index (AVDI), voltage stability index (VSI), and the impact of harmonic distortion. The simulations are conducted on 69-bus radial distribution network.

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来源期刊

Energy 工程技术-能源与燃料

CiteScore

15.30

自引率

14.40%

发文量

审稿时长

14.2 weeks

期刊介绍： Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics. The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management. Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.