IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v8y2015i5p4188-4215d49394.html
   My bibliography  Save this article

The Concept of EV’s Intelligent Integrated Station and Its Energy Flow

Author

Listed:
  • Da Xie

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Haoxiang Chu

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Yupu Lu

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Chenghong Gu

    (Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK)

  • Furong Li

    (Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK)

  • Yu Zhang

    (Research Institute of Electric Power, Shanghai Power Supply Company, Shanghai 200437, China)

Abstract

The increasing number of electric vehicles (EVs) connected to existing distribution networks as time-variant loads cause significant distortions in line current and voltage. A novel EV’s intelligent integrated station (IIS) making full use of retired batteries is introduced in this paper to offer a potential solution for accommodating the charging demand of EVs. It proposes the concept of generalized energy in IIS, based on the energy/power flow between IIS and EVs, and between IIS and the power grid, to systematically evaluate the energy capacity of IIS. In order to derive a unique and satisfactory operation mode, information from both the grid (in terms of load level) and IIS (in terms of its energy capacity and EVs battery charging/exchanging requests) is merged. Then, based on the generalized energy of different systems, a novel charging/discharging control strategy is presented and whereby the operating status of the grid and energy capacity of IIS are monitored to make reasonable operation plans for IIS. Simulation results suggest that the proposed IIS offers peak load shifting when EV battery charging/exchanging requests are satisfied compared to existing charging stations.

Suggested Citation

  • Da Xie & Haoxiang Chu & Yupu Lu & Chenghong Gu & Furong Li & Yu Zhang, 2015. "The Concept of EV’s Intelligent Integrated Station and Its Energy Flow," Energies, MDPI, vol. 8(5), pages 1-28, May.
  • Handle: RePEc:gam:jeners:v:8:y:2015:i:5:p:4188-4215:d:49394
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/8/5/4188/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/8/5/4188/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richardson, David B., 2013. "Electric vehicles and the electric grid: A review of modeling approaches, Impacts, and renewable energy integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 247-254.
    2. Guille, Christophe & Gross, George, 2009. "A conceptual framework for the vehicle-to-grid (V2G) implementation," Energy Policy, Elsevier, vol. 37(11), pages 4379-4390, November.
    3. Xiaosong Hu & Fengchun Sun & Yuan Zou, 2010. "Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer," Energies, MDPI, vol. 3(9), pages 1-18, September.
    4. Hongwen He & Rui Xiong & Jinxin Fan, 2011. "Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach," Energies, MDPI, vol. 4(4), pages 1-17, March.
    5. João Soares & Bruno Canizes & Cristina Lobo & Zita Vale & Hugo Morais, 2012. "Electric Vehicle Scenario Simulator Tool for Smart Grid Operators," Energies, MDPI, vol. 5(6), pages 1-19, June.
    6. Jingyu Yan & Guoqing Xu & Huihuan Qian & Yangsheng Xu, 2010. "Robust State of Charge Estimation for Hybrid Electric Vehicles: Framework and Algorithms," Energies, MDPI, vol. 3(10), pages 1-19, September.
    7. Delucchi, Mark & Lipman, Timothy, 2001. "An Analysis of the Retail and Lifecycle Cost of Battery-Powered Electric Vehicles," Institute of Transportation Studies, Working Paper Series qt50q9060k, Institute of Transportation Studies, UC Davis.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zuhaib Ashfaq Khan & Hafiz Husnain Raza Sherazi & Mubashir Ali & Muhammad Ali Imran & Ikram Ur Rehman & Prasun Chakrabarti, 2021. "Designing a Wind Energy Harvester for Connected Vehicles in Green Cities," Energies, MDPI, vol. 14(17), pages 1-18, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chaouachi, Aymen & Bompard, Ettore & Fulli, Gianluca & Masera, Marcelo & De Gennaro, Michele & Paffumi, Elena, 2016. "Assessment framework for EV and PV synergies in emerging distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 719-728.
    2. Kley, Fabian & Lerch, Christian & Dallinger, David, 2011. "New business models for electric cars--A holistic approach," Energy Policy, Elsevier, vol. 39(6), pages 3392-3403, June.
    3. Jean-Michel Clairand & Paulo Guerra-Terán & Xavier Serrano-Guerrero & Mario González-Rodríguez & Guillermo Escrivá-Escrivá, 2019. "Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies," Energies, MDPI, vol. 12(16), pages 1-22, August.
    4. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    5. Bizhong Xia & Zizhou Lao & Ruifeng Zhang & Yong Tian & Guanghao Chen & Zhen Sun & Wei Wang & Wei Sun & Yongzhi Lai & Mingwang Wang & Huawen Wang, 2017. "Online Parameter Identification and State of Charge Estimation of Lithium-Ion Batteries Based on Forgetting Factor Recursive Least Squares and Nonlinear Kalman Filter," Energies, MDPI, vol. 11(1), pages 1-23, December.
    6. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    7. Woo-Yong Kim & Pyeong-Yeon Lee & Jonghoon Kim & Kyung-Soo Kim, 2019. "A Nonlinear-Model-Based Observer for a State-of-Charge Estimation of a Lithium-Ion Battery in Electric Vehicles," Energies, MDPI, vol. 12(17), pages 1-20, September.
    8. Hota, Ashish Ranjan & Juvvanapudi, Mahesh & Bajpai, Prabodh, 2014. "Issues and solution approaches in PHEV integration to smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 217-229.
    9. Keumju Lim & Justine Jihyun Kim & Jongsu Lee, 2020. "Forecasting the future scale of vehicle to grid technology for electric vehicles and its economic value as future electric energy source: The case of South Korea," Energy & Environment, , vol. 31(8), pages 1350-1366, December.
    10. Xian Zhao & Siqi Wang & Xiaoyue Wang, 2018. "Characteristics and Trends of Research on New Energy Vehicle Reliability Based on the Web of Science," Sustainability, MDPI, vol. 10(10), pages 1-25, October.
    11. Niesten, Eva & Alkemade, Floortje, 2016. "How is value created and captured in smart grids? A review of the literature and an analysis of pilot projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 629-638.
    12. Schwarz, Marius & Auzépy, Quentin & Knoeri, Christof, 2020. "Can electricity pricing leverage electric vehicles and battery storage to integrate high shares of solar photovoltaics?," Applied Energy, Elsevier, vol. 277(C).
    13. Ruifeng Zhang & Bizhong Xia & Baohua Li & Libo Cao & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang, 2018. "State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles," Energies, MDPI, vol. 11(7), pages 1-36, July.
    14. Shifei Yuan & Hongjie Wu & Chengliang Yin, 2013. "State of Charge Estimation Using the Extended Kalman Filter for Battery Management Systems Based on the ARX Battery Model," Energies, MDPI, vol. 6(1), pages 1-27, January.
    15. Yang, Zhile & Li, Kang & Foley, Aoife, 2015. "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 396-416.
    16. Zhongyue Zou & Jun Xu & Chris Mi & Binggang Cao & Zheng Chen, 2014. "Evaluation of Model Based State of Charge Estimation Methods for Lithium-Ion Batteries," Energies, MDPI, vol. 7(8), pages 1-18, August.
    17. Seyfettin Vadi & Ramazan Bayindir & Alperen Mustafa Colak & Eklas Hossain, 2019. "A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies," Energies, MDPI, vol. 12(19), pages 1-27, September.
    18. Tan, Kang Miao & Ramachandaramurthy, Vigna K. & Yong, Jia Ying, 2016. "Integration of electric vehicles in smart grid: A review on vehicle to grid technologies and optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 720-732.
    19. Zheng, Fangdan & Xing, Yinjiao & Jiang, Jiuchun & Sun, Bingxiang & Kim, Jonghoon & Pecht, Michael, 2016. "Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 183(C), pages 513-525.
    20. Prina, Matteo Giacomo & Groppi, Daniele & Nastasi, Benedetto & Garcia, Davide Astiaso, 2021. "Bottom-up energy system models applied to sustainable islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:8:y:2015:i:5:p:4188-4215:d:49394. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.