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Evaluation of Optimization-Based EV Charging Scheduling with Load Limit in a Realistic Scenario

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  • Steffen Limmer

    (Honda Research Institute Europe GmbH, 63073 Offenbach, Germany)

Abstract

In the literature, optimization-based approaches are frequently proposed for the control of electric vehicle charging. However, they are usually evaluated under simplifying assumptions and are not compared to more simple approaches. The present work compares optimization-based approaches with rule-based ones in a simple but realistic scenario, in which a certain limit for the total load has to be satisfied. The scenario is based on the situation at an office building in Germany. In simulation experiments, different control approaches are evaluated not only in terms of pure performance but also from an economic perspective. The results indicate that, although the optimization-based approaches outperform the rule-based approaches, they are not always the right choice from an economic point of view.

Suggested Citation

  • Steffen Limmer, 2019. "Evaluation of Optimization-Based EV Charging Scheduling with Load Limit in a Realistic Scenario," Energies, MDPI, vol. 12(24), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4730-:d:296828
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    References listed on IDEAS

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    1. Christoph M. Flath & Jens P. Ilg & Sebastian Gottwalt & Hartmut Schmeck & Christof Weinhardt, 2014. "Improving Electric Vehicle Charging Coordination Through Area Pricing," Transportation Science, INFORMS, vol. 48(4), pages 619-634, November.
    2. Jinil Han & Jongyoon Park & Kyungsik Lee, 2017. "Optimal Scheduling for Electric Vehicle Charging under Variable Maximum Charging Power," Energies, MDPI, vol. 10(7), pages 1-15, July.
    3. Steffen Limmer, 2019. "Dynamic Pricing for Electric Vehicle Charging—A Literature Review," Energies, MDPI, vol. 12(18), pages 1-24, September.
    4. Tobias Rodemann & Tom Eckhardt & René Unger & Torsten Schwan, 2019. "Using Agent-Based Customer Modeling for the Evaluation of EV Charging Systems," Energies, MDPI, vol. 12(15), pages 1-16, July.
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    Cited by:

    1. Dongxu Guo & Geng Yang & Guangjin Zhao & Mengchao Yi & Xuning Feng & Xuebing Han & Languang Lu & Minggao Ouyang, 2020. "Determination of the Differential Capacity of Lithium-Ion Batteries by the Deconvolution of Electrochemical Impedance Spectra," Energies, MDPI, vol. 13(4), pages 1-14, February.
    2. Marija Zima-Bockarjova & Antans Sauhats & Lubov Petrichenko & Roman Petrichenko, 2020. "Charging and Discharging Scheduling for Electrical Vehicles Using a Shapley-Value Approach," Energies, MDPI, vol. 13(5), pages 1-21, March.

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