The Online Reservation Problem

Goyal, Shashank; Gupta, Diwakar

doi:10.2139/ssrn.3137745

Cited by 1 publication

(2 citation statements)

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“…Secondly, with the special case of homogeneous values, i.e., v n = v, ∀n, no energy cost, i.e., p t = 0, ∀t, and different duration of EVs, our problem degenerates to the online interval scheduling problem [12]. Let δ = D max /D min be the duration ratio.…”

Section: Resultsmentioning

confidence: 99%

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Near-optimal Online Algorithms for Joint Pricing and Scheduling in EV Charging Networks

Roozbeh¹,

Sun²,

Joe‐Wong³

et al. 2023

Preprint

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With the rapid acceleration of transportation electrification, public charging stations are becoming vital infrastructure in a smart sustainable city to provide on-demand electric vehicle (EV) charging services. As more consumers seek to utilize public charging services, the pricing and scheduling of such services will become vital, complementary tools to mediate competition for charging resources. However, determining the right prices to charge is difficult due to the online nature of EV arrivals. This paper studies a joint pricing and scheduling problem for the operator of EV charging networks with limited charging capacity and time-varying energy cost. Upon receiving a charging request, the operator offers a price, and the EV decides whether to admit the offer based on its own value and the posted price. The operator then schedules the real-time charging process to satisfy the charging request if the EV admits the offer. We propose an online pricing algorithm that can determine the posted price and EV charging schedule to maximize social welfare, i.e., the total value of EVs minus the energy cost of charging stations. Theoretically, we prove the devised algorithm can achieve the order-optimal competitive ratio under the competitive analysis framework. Practically, we show the empirical performance of our algorithm outperforms other benchmark algorithms in experiments using real EV charging data.

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Section: Resultsmentioning

confidence: 99%

“…Let δ = D max /D min be the duration ratio. It is known that the lower bound on the competitive ratio for any online algorithm for the online interval scheduling is Ω(ln(δ)) [12]. Now, with two special cases of the online knapsack problem and the online interval scheduling, the lower bound of any online algorithms for problem (1) is…”

Section: Resultsmentioning

confidence: 99%