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Willingness to delay charging of electric vehicles

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  • Daziano, Ricardo A.

Abstract

Coordinated electric-vehicle charging can produce optimal, flattened loads that would improve reliability of the power system as well as reduce system costs and emissions. Optimal deadline scheduling of residential charging would require customers to defer charging their vehicles and to accept less than a 100% target for battery charge. To analyze the necessary incentives for customers to accept giving up control of when charging of their vehicles takes place, we use data from a choice experiment implemented in an online survey of electric-vehicle owners and lessees in upstate New York (N=462). The choice microdata allowed us to make inference on the willingness to pay for features of hypothetical coordinated electric-vehicle charging programs, exploiting Variational Bayes (VB) inference. Our results show that individuals negatively perceive the duration of the timeframe in which the energy provider would be allowed to defer charging. A negative monetary valuation is evidenced by an expected average reduction in the annual fee of joining the coordinated charging program of $2.66 per hour of control yielded to the energy provider. Our results also provide evidence of substantial heterogeneity in preferences, probably due to early-stage attitudes toward coordinated charging. For example, the 25% quantile of the posterior distribution of the mean of the willingness to accept an additional hour of control yielded to the utility is $4.72. However, the negative valuation of the timeframe for deferring charging is compensated by positive valuation of emission savings coming from switching charging to periods of the day with a higher proportion of generation from renewable sources. Customers also positively valued discounts in the price of energy delivery.

Suggested Citation

  • Daziano, Ricardo A., 2022. "Willingness to delay charging of electric vehicles," Research in Transportation Economics, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:retrec:v:94:y:2022:i:c:s0739885921001487
    DOI: 10.1016/j.retrec.2021.101177
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    2. Singha Chaveesuk & Wornchanok Chaiyasoonthorn & Nayika Kamales & Zdzislawa Dacko-Pikiewicz & Wiesław Liszewski & Bilal Khalid, 2023. "Evaluating the Determinants of Consumer Adoption of Autonomous Vehicles in Thailand—An Extended UTAUT Model," Energies, MDPI, vol. 16(2), pages 1-22, January.

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