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Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit

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  • Nimalsiri, Nanduni I.
  • Ratnam, Elizabeth L.
  • Mediwaththe, Chathurika P.
  • Smith, David B.
  • Halgamuge, Saman K.

Abstract

Increased worldwide uptake of Electric Vehicles (EVs) accentuates the need for developing coordinated EV charging and discharging methods that mitigate detrimental and sustained under-voltage and over-voltage conditions in distribution networks. In this paper, a centrally coordinated EV charge-discharge scheduling method is proposed, referred to as Network-aware EV Charging (and Discharging) N-EVC(D), that takes into account both EV customer economics and distribution grid constraints. Specifically, N-EVC(D) is designed to maintain quasi-steady-state feeder voltages within statutory power quality limits, while minimizing EV customer operational costs associated with: (1) purchasing (or otherwise being compensated for delivering) electricity on a time-of-use tariff; and (2) battery degradation due to frequent charging and discharging. The optimization problem for N-EVC(D) is formulated as a quadratic program, with voltage constraints to limit voltage variability across a radial distribution feeder, and individual EV constraints to satisfy heterogeneous EV charge requirements. In N-EVC(D), each grid-connected EV follows an operator-specified battery schedule that is obtained by solving the proposed quadratic program. A receding horizon implementation is also proposed to support near-real-time N-EVC(D) operations while accommodating non-deterministic EV arrivals and departures. The benefits of N-EVC(D) are assessed by means of numerical simulations carried out on an IEEE test feeder populated with a real-world dataset of residential load collected from households within an Australian distribution network. The simulation results confirm that N-EVC(D) mitigates non-compliant voltage deviations that would otherwise occur when voltage constraints are not enforced. Compared to uncoordinated EV charging, N-EVC(D) offers a 92% – 111% reduction in the operational costs incurred by EV customers.

Suggested Citation

  • Nimalsiri, Nanduni I. & Ratnam, Elizabeth L. & Mediwaththe, Chathurika P. & Smith, David B. & Halgamuge, Saman K., 2021. "Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit," Applied Energy, Elsevier, vol. 291(C).
    • Handle: RePEc:eee:appene:v:291:y:2021:i:c:s0306261921003470
    DOI: 10.1016/j.apenergy.2021.116857
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    5. Ming, Fangzhu & Gao, Feng & Liu, Kun & Li, Xingqi, 2023. "A constrained DRL-based bi-level coordinated method for large-scale EVs charging," Applied Energy, Elsevier, vol. 331(C).
    6. Zeynali, Saeed & Nasiri, Nima & Marzband, Mousa & Ravadanegh, Sajad Najafi, 2021. "A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets," Applied Energy, Elsevier, vol. 300(C).
    7. 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.
    8. Aghajan-Eshkevari, Saleh & Ameli, Mohammad Taghi & Azad, Sasan, 2023. "Optimal routing and power management of electric vehicles in coupled power distribution and transportation systems," Applied Energy, Elsevier, vol. 341(C).
    9. Afaq Ahmad & Muhammad Khalid & Zahid Ullah & Naveed Ahmad & Mohammad Aljaidi & Faheem Ahmed Malik & Umar Manzoor, 2022. "Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging," Energies, MDPI, vol. 15(24), pages 1-32, December.
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    11. Meng, Weiqi & Song, Dongran & Huang, Liansheng & Chen, Xiaojiao & Yang, Jian & Dong, Mi & Talaat, M., 2024. "A Bi-level optimization strategy for electric vehicle retailers based on robust pricing and hybrid demand response," Energy, Elsevier, vol. 289(C).

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