IEEE Access (Jan 2024)
Research on Location and Capacity of Electric Taxi Charging Station Based on Floating Car Data
Abstract
As the electric vehicle industry continues to grow on a large scale, the challenges related to the locating and sizing of charging stations are becoming more apparent. This paper utilizes floating car data from Urumqi, considering factors such as battery SoC, usage time, and the diverse preferences of electric vehicle drivers when making charging decisions. Through this approach, this paper predicts the charging demands of electric vehicles and formulates a model for optimal locating and sizing based on these predicted needs. The research findings indicate that by simulating charging decisions made by electric vehicle drivers, a total of 10,766 charging demands were identified. In comparison, there were 14,759 parking events extracted from the floating car data. This approach reduced redundancy in charging demand predictions compared to directly using the floating car data for extracting parking events. When considering the locating of charging stations, the strategy of exclusively installing fast-charging stations showed better results than the approach involving a mix of fast and slow charging stations. When the decision of locating prioritized minimizing unmet charging demands, it successfully addressed a minimum of 130 additional charging demands. Similarly, when minimizing the idle time for electric taxi drivers was the primary concern, this approach led to a reduction of at least 109 hours in idle time; through a reallocating and sizing adjustment of charging piles within the charging station based on the locating plan, it was possible to meet an additional 83 charging demands. This modification also significantly reduced the average idle time for users, decreasing from an average of 4.26 minutes to 2.63 minutes. Moreover, the charging piles’ average usage time increased, going up from 10.31 hours to 10.42 hours, thus improving the overall efficiency of the charging piles. These findings provide valuable insights for the locating and sizing of charging stations tailored to urban electric taxis.
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