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A decentralized, non-iterative smart protocol for workplace charging of battery electric vehicles

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  • Ramos Muñoz, Edgar
  • Jabbari, Faryar

Abstract

Battery electric vehicles can help reduce fossil fuel consumption and greenhouse gas emissions. Specifically, workplace charging can alleviate the curtailment of renewable resources, while providing charging opportunities to long-range commuters. In this work, a comprehensive smart-charging protocol for workplace charging is proposed. The protocol first uses an ordering strategy, based on each vehicle’s load shifting flexibility, to develop a queue. Next, a decentralized smart-charging strategy is used that allows battery electric vehicles to generate their own charging profile via linear programming. By using an appropriate cost signal, the proposed smart-charging strategy can generate a parking structure demand load with desirable characteristics. Finally, an assignment algorithm is proposed to assign battery electric vehicles to octopus chargers. Driving patterns from the National Household Travel Survey are used to simulate workplace charging for parking structures under various charging scenarios. The proposed ordering strategy resulted in improved peak reductions for all simulated charging scenarios, when compared with chronological ordering. Furthermore, monthly electricity costs and the number of required chargers were both reduced in all cases where smart charging was combined with the proposed ordering strategy, compared to uncontrolled charging. Thus, the proposed protocol can reduce electricity and charging infrastructure costs associated with workplace charging.

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  • Ramos Muñoz, Edgar & Jabbari, Faryar, 2020. "A decentralized, non-iterative smart protocol for workplace charging of battery electric vehicles," Applied Energy, Elsevier, vol. 272(C).
    • Handle: RePEc:eee:appene:v:272:y:2020:i:c:s0306261920306991
    DOI: 10.1016/j.apenergy.2020.115187
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    References listed on IDEAS

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    Cited by:

    1. Erdogan, Nuh & Kucuksari, Sadik & Murphy, Jimmy, 2022. "A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies," Energy, Elsevier, vol. 254(PA).
    2. Edgar Ramos Muñoz & Faryar Jabbari, 2022. "An Octopus Charger-Based Smart Protocol for Battery Electric Vehicle Charging at a Workplace Parking Structure," Energies, MDPI, vol. 15(17), pages 1-25, September.
    3. 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).
    4. Erdogan, Nuh & Pamucar, Dragan & Kucuksari, Sadik & Deveci, Muhammet, 2021. "An integrated multi-objective optimization and multi-criteria decision-making model for optimal planning of workplace charging stations," Applied Energy, Elsevier, vol. 304(C).
    5. Prahaladh Paniyil & Vishwas Powar & Rajendra Singh, 2021. "Sustainable Intelligent Charging Infrastructure for Electrification of Transportation," Energies, MDPI, vol. 14(17), pages 1-23, August.
    6. Yong, Jin Yi & Tan, Wen Shan & Khorasany, Mohsen & Razzaghi, Reza, 2023. "Electric vehicles destination charging: An overview of charging tariffs, business models and coordination strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).

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