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Optimal Charge Scheduling of Electric Vehicles in Smart Homes

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Electric Vehicles in Energy Systems

Abstract

For decades, fossil fuels are the main source of energy in the world, but concerns caused by price fluctuations, energy security, and environmental issues such as greenhouse gas emissions from burning these fuels have led that various industries to seek to replace fossil fuels. Transportation is one of the main consumers of fossil fuels, especially oil. The transportation share of the world’s total oil consumed in 2012 was 63.7%. Also, 23% of carbon dioxide produced by fossil fuels in 2012 was related to this sector. Replacing conventional vehicles with hybrid electric vehicles is among the best solutions for environmental and economic issues in the transportation sector. Considering the advantages of electric vehicles, their number is expected to increase rapidly over the next few decades. In 2022, more than 35 million electric cars are expected to be on the road. Electric vehicles must be connected to the power grid to charge their batteries. Therefore, with the widespread presence of these cars, the performance of the power system will change especially in the distribution network. Uncontrolled battery charging can cause undesirable effects such as overload, overvoltage, loss increase, unbalanced load, harmonic, and instability. Demand side management can prevent these problems, and it also flattens the demand curve. In order to solve the problems caused by the use of gasoline cars, it is expected that electric vehicles will gradually replace these cars. Lack of control in charging process will have adverse effects on the network. In this study, after modeling the electric car charging curve, its influence on network demand has been investigated in two uncontrolled charging and controlled charging scenarios. In this study, the controlled charge with the goal of minimizing household electricity consumption costs is investigated. The results show that the lack of control on the car charging time increases the peak demand, while the controllable charge does not increase the peak, and flattens the demand curve. The current chapter will discuss the application of electric vehicles in power grid and its role in demand response in order to improve the demand curve especially in smart homes.

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Acknowledgments

Authors would like to thank the research council of Islamic Azad University, Damavand, Iran for financial support of this research project.

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Authors and Affiliations

  1. Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA

    Arezoo Hasankhani

  2. Department of Electrical Engineering and Renewable Energy Research Center, Damavand Branch, Islamic Azad University, Damavand, Iran

    Seyed Mehdi Hakimi

Authors
  1. Arezoo Hasankhani
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  2. Seyed Mehdi Hakimi
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Correspondence to Seyed Mehdi Hakimi .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Bonab, Bonab, Iran

    Ali Ahmadian

  2. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Behnam Mohammadi-ivatloo

  3. University of Waterloo, Department of Chemical Engineering, College of Engineering, Khalifa University of Science and Technology, The Petroleum Institute Abu Dhabi, UAE, Waterloo, ON, Canada

    Ali Elkamel

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Hasankhani, A., Hakimi, S.M. (2020). Optimal Charge Scheduling of Electric Vehicles in Smart Homes. In: Ahmadian, A., Mohammadi-ivatloo, B., Elkamel, A. (eds) Electric Vehicles in Energy Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-34448-1_15

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  • DOI: https://doi.org/10.1007/978-3-030-34448-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34447-4

  • Online ISBN: 978-3-030-34448-1

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