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Coordination of Multiple Electric Vehicle Aggregators for Peak Shaving and Valley Filling in Distribution Feeders

Author

Listed:
  • Saad Ullah Khan

    (Department of Electrical and Computer Engineering, Air University, Islamabad 44000, Pakistan)

  • Khawaja Khalid Mehmood

    (Department of Electrical Engineering, The University of Azad Jammu and Kashmir, Muzaffarabad 13100, Pakistan)

  • Zunaib Maqsood Haider

    (Department of Electrical Engineering, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan)

  • Muhammad Kashif Rafique

    (Department of Electrical Engineering, Balochistan University of Engineering and Technology, Khuzdar 89100, Pakistan)

  • Muhammad Omer Khan

    (Department of Electrical Engineering & Technology, Riphah International University, Faisalabad Campus, Punjab 38000, Pakistan)

  • Chul-Hwan Kim

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

Abstract

In this paper, a coordination method of multiple electric vehicle (EV) aggregators has been devised to flatten the system load profile. The proposed scheme tends to reduce the peak demand by discharging EVs and fills the valley gap through EV charging in the off-peak period. Upper level fair proportional power distribution to the EV aggregators is exercised by the system operator which provides coordination among the aggregators based on their aggregated energy demand or capacity. The lower level min max objective function is implemented at each aggregator to distribute power to the EVs. Each aggregator ensures that the EV customers’ driving requirements are not relinquished in spite of their employment to support the grid. The scheme has been tested on IEEE 13-node distribution system and an actual distribution system situated in Seoul, Republic of Korea whilst utilizing actual EV mobility data. The results show that the system load profile is smoothed by the coordination of aggregators under peak shaving and valley filling goals. Also, the EVs are fully charged before departure while maintaining a minimum energy for emergency travel.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:2:p:352-:d:478155
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    References listed on IDEAS

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    1. 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.
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    3. Shi You & Junjie Hu & Charalampos Ziras, 2016. "An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †," Energies, MDPI, vol. 9(11), pages 1-18, November.
    4. Shareef, Hussain & Islam, Md. Mainul & Mohamed, Azah, 2016. "A review of the stage-of-the-art charging technologies, placement methodologies, and impacts of electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 403-420.
    5. Xu, Zhiwei & Hu, Zechun & Song, Yonghua & Zhao, Wei & Zhang, Yongwang, 2014. "Coordination of PEVs charging across multiple aggregators," Applied Energy, Elsevier, vol. 136(C), pages 582-589.
    6. Jia, Hongjie & Li, Xiaomeng & Mu, Yunfei & Xu, Chen & Jiang, Yilang & Yu, Xiaodan & Wu, Jianzhong & Dong, Chaoyu, 2018. "Coordinated control for EV aggregators and power plants in frequency regulation considering time-varying delays," Applied Energy, Elsevier, vol. 210(C), pages 1363-1376.
    7. 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.
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    Cited by:

    1. Daud Mustafa Minhas & Josef Meiers & Georg Frey, 2022. "Electric Vehicle Battery Storage Concentric Intelligent Home Energy Management System Using Real Life Data Sets," Energies, MDPI, vol. 15(5), pages 1-29, February.
    2. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    3. Robert Pietracho & Christoph Wenge & Przemyslaw Komarnicki & Leszek Kasprzyk, 2022. "Multi-Criterial Assessment of Electric Vehicle Integration into the Commercial Sector—A Case Study," Energies, MDPI, vol. 16(1), pages 1-29, December.
    4. 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.
    5. Qiushi Zhang & Jian Zhao & Xiaoyu Wang & Li Tong & Hang Jiang & Jinhui Zhou, 2021. "Distribution Network Hierarchically Partitioned Optimization Considering Electric Vehicle Orderly Charging with Isolated Bidirectional DC-DC Converter Optimal Efficiency Model," Energies, MDPI, vol. 14(6), pages 1-20, March.
    6. Muhammad Azhar Hassan & Saad Ullah Khan & Muhammad Fahad Zia & Azka Sardar & Khawaja Khalid Mehmood & Fiaz Ahmad, 2023. "Demand-Side Management and Its Impact on the Growing Circular Debt of Pakistan’s Energy Sector," Energies, MDPI, vol. 16(15), pages 1-20, July.

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