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Aggregator-Based Interactive Charging Management System for Electric Vehicle Charging

Author

Listed:
  • Mingchao Xia

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Qingying Lai

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Yajiao Zhong

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Canbing Li

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Hsiao-Dong Chiang

    (Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853, USA)

Abstract

With the ongoing large-scale implementation of electric vehicles (EVs), the exploration of a more flexible approach to maintain fair interaction between EVs and the power grid is urgently required. This paper presents an aggregator-based interactive charging management scheme adopting interruptible load (IL) pricing, in which the EV aggregator will respond to the load control command of the grid in an EV interactive mode. Charging managements are carried out according to battery state-of-charge and the EV departure time in EV charging stations. A power-altering charging (PAC) control method is proposed to dispatch the EVs charging fairly in a station and guarantee EV owners’ preferences. The method does not require classical iterative procedures or heavy computations; furthermore, it is beneficial for EVs to depart earlier than expected for reasons beyond keeping homeostatic charging. The proposed scheme, which is tested to charge individual EVs well according to its preference, was implemented as part of an “EV Beijing” project. The proposed management scheme provides new insight into EV charging strategy and provides another choice to EV users.

Suggested Citation

  • Mingchao Xia & Qingying Lai & Yajiao Zhong & Canbing Li & Hsiao-Dong Chiang, 2016. "Aggregator-Based Interactive Charging Management System for Electric Vehicle Charging," Energies, MDPI, vol. 9(3), pages 1-14, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:159-:d:65059
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    References listed on IDEAS

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    Cited by:

    1. Rosario Miceli & Fabio Viola, 2017. "Designing a Sustainable University Recharge Area for Electric Vehicles: Technical and Economic Analysis," Energies, MDPI, vol. 10(10), pages 1-24, October.
    2. Su Su & Yong Hu & Tiantian Yang & Shidan Wang & Ziqi Liu & Xiangxiang Wei & Mingchao Xia & Yutaka Ota & Koji Yamashita, 2018. "Research on an Electric Vehicle Owner-Friendly Charging Strategy Using Photovoltaic Generation at Office Sites in Major Chinese Cities," Energies, MDPI, vol. 11(2), pages 1-19, February.
    3. Saad Ullah Khan & Khawaja Khalid Mehmood & Zunaib Maqsood Haider & Muhammad Kashif Rafique & Chul-Hwan Kim, 2018. "A Bi-Level EV Aggregator Coordination Scheme for Load Variance Minimization with Renewable Energy Penetration Adaptability," Energies, MDPI, vol. 11(10), pages 1-28, October.
    4. Yajing Gao & Yanping Sun & Xiaodan Wang & Feifan Chen & Ali Ehsan & Hongmei Li & Hong Li, 2017. "Multi-Objective Optimized Aggregation of Demand Side Resources Based on a Self-organizing Map Clustering Algorithm Considering a Multi-Scenario Technique," Energies, MDPI, vol. 10(12), pages 1-20, December.
    5. Yunfeng Jiang & Xin Zhao & Amir Valibeygi & Raymond A. De Callafon, 2016. "Dynamic Prediction of Power Storage and Delivery by Data-Based Fractional Differential Models of a Lithium Iron Phosphate Battery," Energies, MDPI, vol. 9(8), pages 1-17, July.
    6. Saad Ullah Khan & Khawaja Khalid Mehmood & Zunaib Maqsood Haider & Muhammad Kashif Rafique & Muhammad Omer Khan & Chul-Hwan Kim, 2021. "Coordination of Multiple Electric Vehicle Aggregators for Peak Shaving and Valley Filling in Distribution Feeders," Energies, MDPI, vol. 14(2), pages 1-16, January.
    7. Shubo Hu & Hui Sun & Feixiang Peng & Wei Zhou & Wenping Cao & Anlong Su & Xiaodong Chen & Mingze Sun, 2018. "Optimization Strategy for Economic Power Dispatch Utilizing Retired EV Batteries as Flexible Loads," Energies, MDPI, vol. 11(7), pages 1-21, June.
    8. Parinaz Aliasghari & Behnam Mohammadi-Ivatloo & Mehdi Abapour & Ali Ahmadian & Ali Elkamel, 2020. "Goal Programming Application for Contract Pricing of Electric Vehicle Aggregator in Join Day-Ahead Market," Energies, MDPI, vol. 13(7), pages 1-12, April.
    9. Homa Rashidizadeh-Kermani & Hamid Reza Najafi & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2018. "Optimal Decision-Making Strategy of an Electric Vehicle Aggregator in Short-Term Electricity Markets," Energies, MDPI, vol. 11(9), pages 1-20, September.
    10. Lixing Chen & Xueliang Huang & Hong Zhang & Yinsheng Luo, 2018. "A Study on Coordinated Optimization of Electric Vehicle Charging and Charging Pile Selection," Energies, MDPI, vol. 11(6), pages 1-16, May.
    11. Ivana Semanjski & Sidharta Gautama, 2016. "Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices," Energies, MDPI, vol. 9(12), pages 1-17, December.
    12. Morteza Nazari-Heris & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
    13. Zhu, Xianwen & Xia, Mingchao & Chiang, Hsiao-Dong, 2018. "Coordinated sectional droop charging control for EV aggregator enhancing frequency stability of microgrid with high penetration of renewable energy sources," Applied Energy, Elsevier, vol. 210(C), pages 936-943.
    14. Lixing Chen & Zhong Chen & Xueliang Huang & Long Jin, 2016. "A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways," Energies, MDPI, vol. 9(5), pages 1-18, May.

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