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Impact of Dynamic Electricity Tariff and Home PV System Incentives on Electric Vehicle Charging Behavior: Study on Potential Grid Implications and Economic Effects for Households

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  • Michael von Bonin

    (Fraunhofer Institute for Energy Economics and Energy System Technology IEE Königstor 59, 34119 Kassel, Germany
    Department of Energy Management and Power System Operation, University of Kassel, 34121 Kassel, Germany
    These authors contributed equally to this work.)

  • Elias Dörre

    (Fraunhofer Institute for Energy Economics and Energy System Technology IEE Königstor 59, 34119 Kassel, Germany
    These authors contributed equally to this work.)

  • Hadi Al-Khzouz

    (Fraunhofer Institute for Energy Economics and Energy System Technology IEE Königstor 59, 34119 Kassel, Germany
    These authors contributed equally to this work.)

  • Martin Braun

    (Fraunhofer Institute for Energy Economics and Energy System Technology IEE Königstor 59, 34119 Kassel, Germany
    Department of Energy Management and Power System Operation, University of Kassel, 34121 Kassel, Germany)

  • Xian Zhou

    (Fraunhofer Institute for Energy Economics and Energy System Technology IEE Königstor 59, 34119 Kassel, Germany)

Abstract

The rapid increase of electric vehicles (EVs) would lead to a rise in load demand on power grids but create different potential benefits as well. Those benefits comprise EVs serving as a mobile energy storage system to participate in adjusting the load on the power grids and helping manage renewable energy resources. This paper evaluates the effect of dynamic electricity prices and home photovoltaic (PV) system incentives on users’ EVs charging behavior and potential impacts on grid load and household economy. This has been done by establishing and assessing three different optimized charging configurations and comparing them to an uncontrolled charging strategy. In this study, the charging incentives are applied to a representative sample of 100 households with EVs and PV systems in a metropolitan area. The results show that an optimized charging strategy based on the dynamic electricity tariff can reduce charging costs by 18.5%, while a PV-based optimized strategy can reduce the costs by 33.7%. Moreover, the PV-integrated optimization strategies significantly increase the utilization of PV energy by almost 46% on average, compared to uncontrolled charging. In addition, the simulations of this research have depicted the capability of using home PV systems’ incentives to smoothen the charging profiles and hence significantly reduce the maximum grid load. However, the electricity price optimization strategy increases the aggregated charging peaks, which can only be slightly reduced by peak shaving. Therefore, an identical price signal for all households might be critical. Further analyses have shown that direct charging occurs simultaneously with household electricity assigned to a specific low-voltage grid while PV and price incentive charging configurations shift the charging peaks away from household load peaks.

Suggested Citation

  • Michael von Bonin & Elias Dörre & Hadi Al-Khzouz & Martin Braun & Xian Zhou, 2022. "Impact of Dynamic Electricity Tariff and Home PV System Incentives on Electric Vehicle Charging Behavior: Study on Potential Grid Implications and Economic Effects for Households," Energies, MDPI, vol. 15(3), pages 1-28, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:1079-:d:739999
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    References listed on IDEAS

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    1. Blasius, Erik & Wang, Zhenqi, 2018. "Effects of charging battery electric vehicles on local grid regarding standardized load profile in administration sector," Applied Energy, Elsevier, vol. 224(C), pages 330-339.
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    Cited by:

    1. Oussama Ouramdane & Elhoussin Elbouchikhi & Yassine Amirat & Franck Le Gall & Ehsan Sedgh Gooya, 2022. "Home Energy Management Considering Renewable Resources, Energy Storage, and an Electric Vehicle as a Backup," Energies, MDPI, vol. 15(8), pages 1-20, April.
    2. 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.
    3. Ali Jawad Alrubaie & Mohamed Salem & Khalid Yahya & Mahmoud Mohamed & Mohamad Kamarol, 2023. "A Comprehensive Review of Electric Vehicle Charging Stations with Solar Photovoltaic System Considering Market, Technical Requirements, Network Implications, and Future Challenges," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    4. Luis Gomes & António Coelho & Zita Vale, 2022. "Assessment of Energy Customer Perception, Willingness, and Acceptance to Participate in Smart Grids—A Portuguese Survey," Energies, MDPI, vol. 16(1), pages 1-16, December.
    5. Sharda, S. & Garikapati, V.M. & Goulias, K.G. & Reyna, J.L. & Sun, B. & Spurlock, C.A. & Needell, Z., 2024. "The electric vehicles-solar photovoltaics Nexus: Driving cross-sectoral adoption of sustainable technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    6. Zaidi, I. & Oulamara, A. & Idoumghar, L. & Basset, M., 2024. "Maximizing the number of satisfied charging demands of electric vehicles on identical chargers," Omega, Elsevier, vol. 127(C).
    7. Mohammad Kamrul Hasan & AKM Ahasan Habib & Shayla Islam & Mohammed Balfaqih & Khaled M. Alfawaz & Dalbir Singh, 2023. "Smart Grid Communication Networks for Electric Vehicles Empowering Distributed Energy Generation: Constraints, Challenges, and Recommendations," Energies, MDPI, vol. 16(3), pages 1-20, January.

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