Application of new multi-objective optimization algorithm for EV scheduling in smart grid through the uncertainties

被引:0
|
作者
WanJun Yin
Dinesh Mavaluru
Munir Ahmed
Mazhar Abbas
Aida Darvishan
机构
[1] Xidian University,School of Electronic & Mechanical Engineering
[2] Sichuan Vocational College of Information Technology,College of Computing and Informatics
[3] Saudi Electronic University,Department of Management Sciences
[4] COMSATS University Islamabad,Department of Industrial Engineering
[5] University of Houston,undefined
关键词
Multi-objective scheduling; EV; Renewables source; Demand response; Optimization;
D O I
暂无
中图分类号
学科分类号
摘要
Ecological and economics issues are caused to give careful consideration to electric vehicles (EV) and sustainable power source assets. One of the proposed answers for increment the impact of these assets, is to utilize the electric vehicles potential. The capability of electric vehicles require planning for Smart Distribution Systems (SDS). Request reaction programs, as a suitable device to utilize endorsers’ potential in ideal administration of the system, gives dynamic nearness of supporters in control framework execution change and these projects, in basic conditions, can give the request prerequisites diminishment, in a brief timeframe. In this work, attempts to presents a multi-objective scheduling of EV based on the sustainable assets in smart grid, cover uncertainty caused by inexhaustible assets and EVs, by considering of the request reaction projects and EV battery stockpiling framework, limit the working expenses and the measure of intensity framework contamination, with enhancing procedures. Improved optimization algorithm is utilized for taking care of the advancing issue. Operating costs dropped much further utilizing monetary model of the demand response and vehicle charge/discharge and smart program in the hours when the load is lower. Effectiveness of proposed method is applied on 33 bus standard power system.
引用
收藏
页码:2071 / 2103
页数:32
相关论文
共 50 条
  • [41] Multi-objective Particle Swarm Optimization to Solve Energy Scheduling with Vehicle-to-Grid in Office Buildings Considering Uncertainties
    Borges, Nuno
    Soares, Joao
    Vale, Zita
    [J]. IFAC PAPERSONLINE, 2017, 50 (01): : 3356 - 3361
  • [42] Application of multi-objective memetic algorithm in multi-objective flexible job-shop scheduling problem
    Zhenwen, H.U.
    [J]. Academic Journal of Manufacturing Engineering, 2019, 17 (03): : 24 - 28
  • [43] Multi-objective Scheduling for Parallel Jobs on Grid
    Liu, Pengfei
    Dong, Shoubin
    [J]. ADVANCED MEASUREMENT AND TEST, PARTS 1 AND 2, 2010, 439-440 : 1281 - +
  • [44] Order scheduling multi-objective optimization
    Chen, Xin-lin
    Zhang, Shuang-Wu
    Wang, Xiang-gang
    [J]. 2009 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND COMPUTER SCIENCE, VOL 1, PROCEEDINGS, 2009, : 281 - +
  • [45] Handling uncertainties in evolutionary multi-objective optimization
    Tan, Kay Chen
    Goh, Chi Keong
    [J]. COMPUTATIONAL INTELLIGENCE: RESEARCH FRONTIERS, 2008, 5050 : 262 - +
  • [46] Multi-objective Power Management on Smart Grid
    Guo, Xian-Chang
    Liao, Chung-Shou
    Chu, Chia-Chi
    [J]. PROCEEDINGS OF THE 2014 IEEE 18TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), 2014, : 733 - 737
  • [47] A new dynamic multi-objective optimization evolutionary algorithm
    Liu, Chun-An
    Wang, Yuping
    [J]. INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2008, 4 (08): : 2087 - 2096
  • [48] New hybrid algorithm for multi-objective structural optimization
    Samira, El Moumen
    Rachid, Ellaia
    Rajae, Aboulaich
    [J]. PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND SYSTEMS MANAGEMENT (IEEE-IESM 2013), 2013, : 458 - 462
  • [49] Fast Workflow Scheduling for Grid Computing Based on a Multi-objective Genetic Algorithm
    Khajemohammadi, Hassan
    Fanian, Ali
    Gulliver, T. Aaron
    [J]. 2013 IEEE PACIFIC RIM CONFERENCE ON COMMUNICATIONS, COMPUTERS AND SIGNAL PROCESSING (PACRIM), 2013, : 96 - 101
  • [50] A new optimization algorithm to solve multi-objective problems
    Sharifi, Mohammad Reza
    Akbarifard, Saeid
    Qaderi, Kourosh
    Madadi, Mohamad Reza
    [J]. SCIENTIFIC REPORTS, 2021, 11 (01)