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A Feasibility Study of Profiting from System Imbalance Using Residential Electric Vehicle Charging Infrastructure

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  • Marián Tomašov

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Power Electrical Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Milan Straka

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Mathematical Methods and Operations Research, Faculty of Management Science and Informatics, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Dávid Martinko

    (Department of Electric Power Engineering, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00 Košice, Slovakia)

  • Peter Braciník

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Power Electrical Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Ľuboš Buzna

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Mathematical Methods and Operations Research, Faculty of Management Science and Informatics, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia
    Department of International Research Projects-ERADIATE+, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

Abstract

Residential chargers are going to become the standard in the near future. Their operational cycles are closely tied to users’ daily routines, and the power consumption fluctuates between zero and peak levels. These types of installations are particularly challenging for the grid, especially concerning the balance of electricity production and consumption. Using battery storage in conjunction with renewable sources (e.g., photovoltaic power plants) represents a flexible solution for grid stabilization, but it is also associated with additional costs. Nowadays, grid authorities penalize a destabilization of the grid resulting from an increased imbalance between electricity generation and consumption and reward contributions to the system balance. Hence, there is a motivation for larger prosumers to make use of this mechanism to reduce their operational costs by better aligning their energy needs with the grid. This study explores the possibility of utilizing battery storage when it is not needed to fulfil its primary function of supporting charging electric vehicles, to generate some additional profit from providing a counter-imbalance. To test this idea, we develop an optimization model that maximizes the economic profit, considering system imbalance penalties/rewards, photovoltaic production, electric vehicle charging demand, and battery storage utilization. By means of computer simulation, we assess the overall operational costs while varying key installation parameters such as battery capacity and power, the installed power of photovoltaic panels and the prediction model’s accuracy. We identify conditions when counter-imbalance has proven to be a viable way to reduce installation costs. These conditions include temporal distribution of charging demand, electricity prices and photovoltaic production. For the morning time window, with a suitable setting of the installation parameters, the cost reduction reaches up to 14% compared to the situation without counter-imbalance.

Suggested Citation

  • Marián Tomašov & Milan Straka & Dávid Martinko & Peter Braciník & Ľuboš Buzna, 2023. "A Feasibility Study of Profiting from System Imbalance Using Residential Electric Vehicle Charging Infrastructure," Energies, MDPI, vol. 16(23), pages 1-27, November.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:23:p:7820-:d:1289479
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    References listed on IDEAS

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    1. Eicke, Anselm & Ruhnau, Oliver & Hirth, Lion, 2021. "Electricity balancing as a market equilibrium: An instrument-based estimation of supply and demand for imbalance energy," Energy Economics, Elsevier, vol. 102(C).
    2. Hafez, Omar & Bhattacharya, Kankar, 2017. "Optimal design of electric vehicle charging stations considering various energy resources," Renewable Energy, Elsevier, vol. 107(C), pages 576-589.
    3. Jiao, Feixiang & Zou, Yuan & Zhang, Xudong & Zhang, Bin, 2022. "Online optimal dispatch based on combined robust and stochastic model predictive control for a microgrid including EV charging station," Energy, Elsevier, vol. 247(C).
    4. Carlo Corinaldesi & Georg Lettner & Daniel Schwabeneder & Amela Ajanovic & Hans Auer, 2020. "Impact of Different Charging Strategies for Electric Vehicles in an Austrian Office Site," Energies, MDPI, vol. 13(22), pages 1-17, November.
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    Cited by:

    1. Md Jamal Ahmed Shohan & Md Maidul Islam & Sophia Owais & Md Omar Faruque, 2024. "Optimal Energy Management of EVs at Workplaces and Residential Buildings Using Heuristic Graph-Search Algorithm," Energies, MDPI, vol. 17(21), pages 1-20, October.

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