Bo Sun
ABSTRACT
There is an increasing need for spatial and temporal schedule tailored to the requests and preferences of electric vehicles (EVs) in a network of charging stations. From the perspective of a charging network operator, this paper considers an online decision-making problem that recommends charging stations and the corresponding energy prices to sequential EV arrivals, and schedules the charging allocation to maximize the expected total revenue. To address the uncertainties from future EV arrivals and EVs' choices with respective to recommendations, we propose an Online Recommendation and Charging schedule algorithm (ORC) that is parameterized by a value function for customized designs. Under the competitive analysis framework, we provide a sufficient condition on the value function that can guarantee ORC to be online competitive. Moreover, we design a customized value function based on the sufficient conditions in an asymptotic case, and then rigorously prove the competitive ratio of ORC in the general case. Through extensive experiments, we show that ORC achieves significant increase of revenues compared to benchmark online algorithms.
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Index Terms
- ORC: An Online Competitive Algorithm for Recommendation and Charging Schedule in Electric Vehicle Charging Network
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