decarbonized unit commitment applying water cycle algorithm integrating plug-in electric vehicles

被引:0
|
作者
El-Azab, Heba-Allah Ibrahim [1 ]
Swief, Rania Abdel-Wahed [2 ]
El-Amary, Noha Hany [3 ]
Temraz, Hesham Kamel [2 ]
机构
[1] Ahram Canadian Univ, Fac Engn, Giza, Egypt
[2] Ain Shams Univ, Fac Engn, Cairo, Egypt
[3] AASTMT, Fac Engn, Cairo, Egypt
关键词
decarbonization; Combined Economic Emission Dispatch problem (CEED); plug-in electric vehicles (PEVs); water cycle algorithm (WCA); dynamic programming (DP); DEMAND RESPONSE;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper introduces a potentially decarbonizing study on IEEE 30 bus electric network, where the target of electricity production is met the supply side by using alternative sources instead of burning fossil fuel such as renewable energy resources. Continuous improvements and using low-carbon technologies is considered to decarbonize CO2 emissions. A unit commitment study is to optimally minimize emission, losses and costs by replacing conventional generating units with stochastic resources and PEVs. PEVs are provided to vanquish the intermittency and uncertainty of wind and solar energies. Combined Economic Emission Dispatch problem (CEED) is proposed an optimally scheduling of Renewable Energy Resources (RERs) and predetermined processes of (charging/discharging) of PEVs with dispatchable generating units. Two algorithms are used to validate the results. Water cycle algorithm (WCA) is the meta-heuristic algorithm shows its efficiency and durability in minimizing the cost function incorporating costs of CO2 emission. The other conventional technique is dynamic programming (DP) is used to assure the obtained results from WCA.
引用
收藏
页码:455 / 462
页数:8
相关论文
共 50 条
  • [31] Evaluating plug-in vehicles (plug-in hybrid and battery electric vehicles) using standard dynamometer protocols
    Duoba, Michael
    Lohse-Busch, Henning
    Rask, Eric
    World Electric Vehicle Journal, 2012, 5 (01): : 196 - 209
  • [32] Electric Grid Integration Costs for Plug-In Electric Vehicles
    Berkheimer, Jeff
    Tang, Jeff
    Boyce, Bill
    Aswani, Deepak J.
    SAE INTERNATIONAL JOURNAL OF ALTERNATIVE POWERTRAINS, 2014, 3 (01) : 1 - 11
  • [33] Integrating Traffic Velocity Data into Predictive Energy Management of Plug-in Hybrid Electric Vehicles
    Sun, Chao
    Sun, Fengchun
    Hu, Xiaosong
    Hedrick, J. Karl
    Moura, Scott
    2015 AMERICAN CONTROL CONFERENCE (ACC), 2015, : 3267 - 3272
  • [34] Assessment Framework of Plug-in Electric Vehicles Strategies
    Senart, Aline
    Kurth, Scott
    Le Roux, Gaelle
    2010 IEEE 1ST INTERNATIONAL CONFERENCE ON SMART GRID COMMUNICATIONS (SMARTGRIDCOMM), 2010, : 155 - 160
  • [35] Optimal Plug-in Electric Vehicles Management by Aggregators
    Benalcazar, Patricio
    Samper, Mauricio E.
    Vargas, Alberto
    2015 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP), 2015,
  • [36] Plug-In Electric Vehicles: What Role for Washington?
    Parag, Yael
    TRANSPORT REVIEWS, 2010, 30 (06) : 806 - 808
  • [37] Scheduling for Charging Plug-in Hybrid Electric Vehicles
    Xu, Yunjian
    Pan, Feng
    2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2012, : 2495 - 2501
  • [38] Optimization of incentive polices for plug-in electric vehicles
    Nie, Yu
    Ghamami, Mehrnaz
    Zockaie, Ali
    Xiao, Feng
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2016, 84 : 103 - 123
  • [39] Overview on Battery Chargers for Plug-in Electric Vehicles
    Bertoluzzo, Manuele
    Zabihi, Nima
    Buja, Giuseppe
    2012 15TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE (EPE/PEMC), 2012,
  • [40] SPECIAL SECTION ON PLUG-IN HYBRID ELECTRIC VEHICLES
    Williamson, Sheldon S.
    Zhu, Chunbo
    Cai, William
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2010, 57 (02) : 584 - 586