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EV smart charging: How tariff selection influences grid stress and carbon reduction

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  • Daneshzand, Farzaneh
  • Coker, Phil J
  • Potter, Ben
  • Smith, Stefan T

Abstract

With the rapid increase in ownership of Electric Vehicles (EVs), widespread concern has been raised regarding the potential for EV charging demand to overload electricity grids. Smart control of charging is advocated as a solution, gaining attention from business and support from policymakers. However, the ultimate grid benefits (or disbenefits) of smart charging will follow from a combination of user behaviour and pricing arrangements / tariffs. Local clustering of vehicle uptake can lead to unintended consequences as national incentives fail to align with local pressures. In this paper, we describe a simulation of the dynamic electricity demand pattern arising from a fleet of grid connected EVs. The model developed for this study combines stochastic sampling of data from a UK-based smart charging trial (Western Power Distribution’s Electric Nation project) with a set of plausible tariffs, including a strategy which specifically seeks to minimize grid carbon emissions. This provides insights into the potential impacts of EV charging by encompassing a wider range of tariffs than previously assessed, while also separating the control actions of optimising cost and managing capacity. We examine the carbon implications of tariff choice and introduce a range of grid overload metrics that reveal nuances in the tariff implications and evolution of impacts as EV penetration increases. The results show that smart charging is not necessarily a better solution for the grid compared to on-demand charging. Stepwise tariffs, currently favoured by UK energy suppliers, present a particular risk. Such tariffs can tend to increase load synchronization by shifting load towards periods where more cars are connected and awaiting charge. This can lead to an increased peak load even at moderate EV uptake levels. Dynamic tariffs proved preferable but still increase peak demand at higher vehicle uptakes. All smart tariffs offer a strong carbon benefit, but, again, current stepwise tariffs are failing to realise the full potential that could be realized by targeting low carbon time periods. Separate local capacity management was able to eliminate overload at the secondary substation, even with very high EV uptake, with only rare, very small levels of unserved demand.

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  • Daneshzand, Farzaneh & Coker, Phil J & Potter, Ben & Smith, Stefan T, 2023. "EV smart charging: How tariff selection influences grid stress and carbon reduction," Applied Energy, Elsevier, vol. 348(C).
    • Handle: RePEc:eee:appene:v:348:y:2023:i:c:s0306261923008462
    DOI: 10.1016/j.apenergy.2023.121482
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    References listed on IDEAS

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    1. Hussain, Shahid & Irshad, Reyazur Rashid & Pallonetto, Fabiano & Hussain, Ihtisham & Hussain, Zakir & Tahir, Muhammad & Abimannan, Satheesh & Shukla, Saurabh & Yousif, Adil & Kim, Yun-Su & El-Sayed, H, 2023. "Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles," Applied Energy, Elsevier, vol. 352(C).
    2. Leonardo Nogueira Fontoura da Silva & Marcelo Bruno Capeletti & Alzenira da Rosa Abaide & Luciano Lopes Pfitscher, 2024. "A Stochastic Methodology for EV Fast-Charging Load Curve Estimation Considering the Highway Traffic and User Behavior," Energies, MDPI, vol. 17(7), pages 1-27, April.

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