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Robust optimization strategy for intelligent parking lot of electric vehicles

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  • Guo, Jianwei
  • Lv, Yongbo
  • Zhang, Han
  • Nojavan, Sayyad
  • Jermsittiparsert, Kittisak

Abstract

In this paper the concept of intelligent parking lot (IPL) is proposed to csolve various challenges of electric vehicles (EVs) integration into the power system. Robust optimization approach is proposed to model the power price uncertainty and obtain the optimal bidding curves of IPL for each hour in order to submit to the power market. Using the provided optimal bidding curves, system operator can get required power to satisfy demand of the system with economical price under power price uncertainty. Optimal scheduling of each component of the system is studied in three different strategies as optimistic, deterministic, and pessimistic to consider all possible cases raised by the power price uncertainty. Each strategy has been solved in two cases as with and without demand response program (DRP). The applied DRP has reduced system operating cost through flattening the load curve. By comparing ROA results with the deterministic case, the total operating cost of the system is decreased from $1029 to $995 about 17.85% decrease while in pessimistic strategy, it is increased from $1209 to $1333 indicating about 9.85% increase. The problem has been solved using GAMS optimization software with the CPLEX solver.

Suggested Citation

  • Guo, Jianwei & Lv, Yongbo & Zhang, Han & Nojavan, Sayyad & Jermsittiparsert, Kittisak, 2020. "Robust optimization strategy for intelligent parking lot of electric vehicles," Energy, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:energy:v:200:y:2020:i:c:s0360544220306629
    DOI: 10.1016/j.energy.2020.117555
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    References listed on IDEAS

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    Cited by:

    1. Daryabari, Mohamad K. & Keypour, Reza & Golmohamadi, Hessam, 2020. "Stochastic energy management of responsive plug-in electric vehicles characterizing parking lot aggregators," Applied Energy, Elsevier, vol. 279(C).
    2. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).
    3. Najafi, Arsalan & Pourakbari-Kasmaei, Mahdi & Jasinski, Michal & Lehtonen, Matti & Leonowicz, Zbigniew, 2021. "A hybrid decentralized stochastic-robust model for optimal coordination of electric vehicle aggregator and energy hub entities," Applied Energy, Elsevier, vol. 304(C).
    4. Najafi, Arsalan & Jasiński, Michał & Leonowicz, Zbigniew, 2022. "A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem," Energy, Elsevier, vol. 249(C).

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