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Supply and Demand Relationship of Taxi Battery Exchange Based on Big Data: A Case Study of Beijing, China

机译:基于大数据的出租车电池交换的供需关系 - 以北京,中国为例

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The power exchange mode is widely applied in the rental field as an efficient energy supply method for new energy vehicles.The power supply-demand relationship analysis swaps.In particular, the quantitative spatial analysis of sub-regions is of great significance for optimizing the spatial layout of power swapping stations, better operation of taxis, and more efficient power swapping stations.Therefore, this paper analyzes the correlation between the ten states of taxis and the corresponding power exchange.The present analysis targets the limitations in the existing methods to analyze the power exchange supply and demand and utilizing the big data pertaining to real-time taxi operation, order-taking mode, and station-swapping operation.As per the correlations, a calculation method is established to determine the power exchange demand based on the location where the orders are received and the matching method of the power exchange supply and demand.Besides verifying the scientific nature and feasibility of the method empirically, this study also ensured its great flexibility, which allows it to adapt to more complicated social scenarios.The big data analysis indicates that determining the spatial distribution of demand based on the location from where the taxi orders are received is far more rational and practical.Thus, this study has a vital role in guiding the location and layout of interchange stations.
机译:电力交换模式广泛应用于租赁领域,作为新能源车辆的有效能量供应方法。电源需求关系分析互换。特别地,子区域的定量空间分析对于优化空间的重要性具有重要意义电力交换站的布局,出租车的操作更好,更有效的功率交换站。因此,本文分析了出租车的十个州和相应的电源交换之间的相关性。目前的分析针对现有方法分析的限制电源交换供需并利用与实时出租车操作相关的大数据,订购模式和站交换操作。根据相关性,建立了基于位置的电源交换需求来确定电源交换需求。收到订单以及电源交换供需的匹配方法。验证科学Natur的基础e并对方法的可行性凭经验,本研究还确保了它的巨大灵活性,这使得它可以适应更复杂的社会场景。大数据分析表明基于收到出租车订单的地点确定需求的空间分布更加合理和实用。本研究在指导交汇站的位置和布局方面具有至关重要的作用。

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