Bi-directional coordination of plug-in electric vehicles with economic model predictive control

SHA'ABAN, Yusuf A, IKPEHAI, Augustine, ADEBISI, Bamidele and RABIE, Khaled M (2017). Bi-directional coordination of plug-in electric vehicles with economic model predictive control. Energies, 10 (10), p. 1507.

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Official URL: https://www.mdpi.com/1996-1073/10/10/1507
Open Access URL: https://www.mdpi.com/1996-1073/10/10/1507/pdf (Published version)
Link to published version:: https://doi.org/10.3390/en10101507
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    Abstract

    © 2017 by the authors. Licensee MDPI, Basel, Switzerland. The emergence of plug-in electric vehicles (PEVs) is unveiling new opportunities to de-carbonise the vehicle parcs and promote sustainability in different parts of the globe. As battery technologies and PEV efficiency continue to improve, the use of electric cars as distributed energy resources is fast becoming a reality. While the distribution network operators (DNOs) strive to ensure grid balancing and reliability, the PEV owners primarily aim at maximising their economic benefits. However, given that the PEV batteries have limited capacities and the distribution network is constrained, smart techniques are required to coordinate the charging/discharging of the PEVs. Using the economic model predictive control (EMPC) technique, this paper proposes a decentralised optimisation algorithm for PEVs during the grid-To-vehicle (G2V) and vehicle-To-grid (V2G) operations. To capture the operational dynamics of the batteries, it considers the state-of-charge (SoC) at a given time as a discrete state space and investigates PEVs performance in V2G and G2V operations. In particular, this study exploits the variability in the energy tariff across different periods of the day to schedule V2G/G2V cycles using real data from the university's PEV infrastructure. The results show that by charging/discharging the vehicles during optimal time partitions, prosumers can take advantage of the price elasticity of supply to achieve net savings of about 63%.

    Item Type: Article
    Uncontrolled Keywords: plug-in electric vehicle; economic model predictive control (EMPC); vehicle-to-grid (V2G); grid-to-vehicle (G2V); optimisation; smart grid; vehicle-to-grid (V2G); 09 Engineering; 02 Physical Sciences
    Identification Number: https://doi.org/10.3390/en10101507
    Page Range: p. 1507
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 01 Mar 2019 11:52
    Last Modified: 01 Mar 2019 12:00
    URI: http://shura.shu.ac.uk/id/eprint/23917

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