• HOME
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • Chinese
Site search        
文章摘要
基于人工鱼群算法的电动汽车优化充电策略
Optimal Charging Strategy of Electric Vehicles Based on Artificial Fish Swarm Algorithm
Received:June 01, 2020  Revised:June 01, 2020
DOI:10.19753/j.issn1001-1390.2023.07.005
中文关键词: 电动汽车  有序充电  人工鱼群算法  优化策略  多目标优化模型
英文关键词: electric  vehicles,orderly  charging,artificial  fish swarm  algorithm,optimization  strategy,multi-objective  optimizing model
基金项目:智慧能源服务系统关键技术研究与示范应用
Author NameAffiliationE-mail
WANG Tianyun* NARI Group Co,LtdState Grid Electric Power Research Institute,Nanjing 649575621@qq.com 
ZHANG Hao NARI Group Co,LtdState Grid Electric Power Research Institute,Nanjing zhanghao8@sgepri.sgcc.com.cn 
Hits: 1582
Download times: 264
中文摘要:
      为了缓解电动汽车大规模未经引导的充电行为对电网造成的压力,维持电网的安全稳定运行,提出了一种电动汽车的充电优化策略。主要思路是通过分时电价制定充电计划,将电动汽车移动至平时段和谷时段进行充电。该算法以用户充电费用最少和电网峰谷差最小为目标函数,建立多目标优化的数学模型,并采用人工鱼群算法对模型进行优化求解。最后以某地区为例进行了仿真分析,仿真结果验证了该算法的有效性,并且随着电动汽车渗透率的提高,算法的效果更为显著,这说明对于未来电动汽车高渗透率的场景下,该算法也具有较强的适应性。
英文摘要:
      In order to relieve the pressure of grid which was caused by massive unguided charging behavior of electric vehicles,at the same time,maintained the safe and stable operation of the power grid,this paper presents a charging optimization strategy for electric vehicles.The main idea of this strategy is to make charging plan through time-of-use electricity price,thus,the electric vehicle can be moved to normal period and valley period for charging.The objective function of the algorithm is to minimize the charging cost and the peak-valley difference,based on this system,the paper builds a mathematic model of multi-objective optimization,and artificial fish swarm algorithm is used to solve the model.Finally,a distribution network is used as an example to carry out simulation analysis.This simulation results verify the effectiveness of the algorithm,and with the increase of electric vehicles’ penetration rate,the effect of the algorithm is more significant,which means that the algorithm will also have strong adaptability in the scenario that the number of electric vehicles will increase in the future.
View Full Text   View/Add Comment  Download reader
Close
  • Home
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • 中文页面
Address: No.2000, Chuangxin Road, Songbei District, Harbin, China    Zip code: 150028
E-mail: dcyb@vip.163.com    Telephone: 0451-86611021
© 2012 Electrical Measurement & Instrumentation
黑ICP备11006624号-1
Support:Beijing Qinyun Technology Development Co., Ltd