Efficient Energy Management with Emphasis on EV Charging/Discharging Strategy

被引:0
|
作者
Kraiem, Habib [1 ,2 ]
Gadri, Wiem [3 ]
Flah, Aymen [2 ,4 ,5 ,6 ,7 ]
机构
[1] Northern Border Univ, Coll Engn, Dept Elect Engn, Ar Ar, Saudi Arabia
[2] Univ Gabes, Natl Engn Sch Gabes, Proc Energy Environm & Elect Syst Code LR18ES34, Gabes, Tunisia
[3] Northern Border Univ, Coll Sci, Dept Math, Ar Ar, Saudi Arabia
[4] Middle East Univ, MEU Res Unit, Amman, Jordan
[5] Univ Business & Technol UBT, Coll Engn, Jeddah 21448, Saudi Arabia
[6] Univ Gabes, Private Higher Sch Appl Sci & Technol Gabes, Gabes, Tunisia
[7] Appl Sci Private Univ, Appl Sci Res Ctr, Amman 11931, Jordan
关键词
power system enhancement; energy management optimization; Renewable Energy Source (RES); microgrid;
D O I
10.48084/etasr.6807
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Leveraging the Vehicle -to -Grid (V2G) concept, this research explores how a decentralized energy reserve from hybrid electric vehicles can enhance the power system, particularly in large-scale implementations. The study introduces a V2G solution designed for effective microgrid frequency control over a full day. Targeting a scenario with minimal usage, typically in spring or fall, the microgrid is scaled to represent a community of 2000 homes. This is exemplified by integrating 500 Electric Vehicles (EVs) based on a 1:4 vehicle -to -household ratio, reflecting a plausible future scenario. The research conducts a comprehensive examination of the microgrid's voltage, current, and active power. By synchronizing the management of diesel and Renewable Energy Source (RES) generation, power transactions, and EV generation, the microgrid's frequency is effectively regulated through V2G devices adjusting load demand. The implemented V2G-enriched microgrid demonstrates improved energy management and mitigates the inconsistencies and fluctuations inherent in RES power generation, showing notable performance enhancements. In various operational contexts, system parameter fluctuations have been analyzed, revealing that deviations are maintained below a 5% threshold.
引用
下载
收藏
页码:13143 / 13147
页数:5
相关论文
共 50 条
  • [1] Optimizing EV Battery Management: Advanced Hybrid Reinforcement Learning Models for Efficient Charging and Discharging
    Yalcin, Sercan
    Herdem, Muenuer Sacit
    ENERGIES, 2024, 17 (12)
  • [2] Development of Charging/Discharging Scheduling Algorithm for Economical and Energy-Efficient Operation of Multi-EV Charging Station
    Jin, Hojun
    Lee, Sangkeum
    Nengroo, Sarvar Hussain
    Har, Dongsoo
    APPLIED SCIENCES-BASEL, 2022, 12 (09):
  • [3] Charging and Discharging Strategy of Electric Vehicles Within a Hierarchical Energy Management Framework
    Alkhafaji, Mohammed
    Luk, Patrick
    Economou, John
    ADVANCED COMPUTATIONAL METHODS IN ENERGY, POWER, ELECTRIC VEHICLES, AND THEIR INTEGRATION, LSMS 2017, PT 3, 2017, 763 : 704 - 716
  • [4] Demand-Side Management by Regulating Charging and Discharging of the EV, ESS, and Utilizing Renewable Energy
    Tushar, Mosaddek Hossain Kamal
    Zeineddine, Adel W.
    Assi, Chadi
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (01) : 117 - 126
  • [5] An Efficient EV Fleet Management for Charging at Workplace Using Solar Energy
    Dhawan, Ritwik
    Karthikeyan, S. Prabhakar
    2018 NATIONAL POWER ENGINEERING CONFERENCE (NPEC), 2018,
  • [6] Optimization of Home Energy Usage by Intelligently Charging/Discharging EV/PHEV
    Zou, Nan
    Qian, Lijun
    Attia, John
    Xie, Le
    2012 INTERNATIONAL CONFERENCE ON CONNECTED VEHICLES AND EXPO (ICCVE), 2012, : 316 - 321
  • [7] Optimal charging/discharging management strategy for electric vehicles
    Algafri, Mohammed
    Baroudi, Uthman
    APPLIED ENERGY, 2024, 364
  • [8] Integration of EV in the Grid Management: The Grid Behavior in Case of Simultaneous EV Charging-Discharging with the PV Solar Energy Injection
    Rwamurangwa, Evode
    Diaz Gonzalez, Juan
    Butare, Albert
    ELECTRICITY, 2022, 3 (04): : 563 - 585
  • [9] Fuzzy logical control strategy of EV charging/discharging considering perceived urgency
    Chen L.
    Ouyang H.
    1600, Electric Power Automation Equipment Press (40): : 62 - 69
  • [10] Probabilistic Energy Management Strategy for EV Charging Stations Using Randomized Algorithms
    Pflaum, Peter
    Alamir, Mazen
    Lamoudi, Mohamed Yacine
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2018, 26 (03) : 1099 - 1106