Data-driven intelligent location of public charging stations for electric vehicles

Liu, Qi; Liu, Jiahao; Le, Wei Wei; Guo, Zhaoxia; He, Zhenggang

doi:10.1016/j.jclepro.2019.05.388

Cited by 73 publications

(29 citation statements)

References 28 publications

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“…Compared with similar sea-going ship, this RSDT ship leads to the reduction of about 10% in the total shipping cost, the increase of about 13% in the load capacity and the reduction of about 12% in the energy consumption. This RSDT model is in line with the green and low-carbon development trend [15][16][17][18][19] nowadays. China plans to establish a safe, efficient and green direct transportation system by 2030 and to complete the construction of the RSDT system from the Yangtze River and Yangtze River delta region to Ningbo-Zhoushan port and Shanghai-Yangshan port in 2020 [20].…”

Section: Introductionsupporting

confidence: 60%

A Multi-Step Approach Framework for Freight Forecasting of River-Sea Direct Transport without Direct Historical Data

Guo

You-kai

et al. 2019

Sustainability

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The freight forecasting of river-sea direct transport (RSDT) is crucial for the policy making of river-sea transportation facilities and the decision-making of relevant port and shipping companies. This paper develops a multi-step approach framework for freight volume forecasting of RSDT in the case that direct historical data are not available. First, we collect publicly available shipping data, including ship traffic flow, speed limit of each navigation channel, free-flow running time, channel length, channel capacity, etc. The origin–destination (O–D) matrix estimation method is then used to obtain the matrix of historical freight volumes among all O–D pairs based on these data. Next, the future total freight volumes among these O–D pairs are forecasted by using the gray prediction model, and the sharing rate of RSDT is estimated by using the logit model. The freight volume of RSDT is thus determined. The effectiveness of the proposed approach is validated by forecasting the RSDT freight volume on a shipping route of China.

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Section: Introductionsupporting

confidence: 60%

A Multi-Step Approach Framework for Freight Forecasting of River-Sea Direct Transport without Direct Historical Data

Guo

You-kai

et al. 2019

Sustainability

Self Cite

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“…Additionally, much attention has been paid to hybrid and electric vehicles due to their low emission factors and high energy efficiency (García et al, 2019;Liu et al, 2019;Luin et al, 2019;. However, the technologies of electric vehicles need to be further improved to meet customers' requirements, especially for the energy density of batteries, charging duration, and low temperature performance (Fischer et al, 2009;Hamut et al, 2014;Kwade et al, 2018;Schmuch et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Intake characteristics and pumping loss in the intake stroke of a novel small scale opposed rotary piston engine

Gao

Tian

Jenner

et al. 2020

Journal of Cleaner Production

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“…Location planning of EVCSs is a decision-making problem and there are many researchers using decisionmaking method to find optimal sites [5][6][7][8][9][10] .…”

Section: Literature Reviewmentioning

confidence: 99%

Site selection for EVCSs by GIS-based AHP method

Sun

2020

E3S Web Conf.

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As an alternative to fossil-fuelled vehicles, electric vehicles (EVs) are eco-friendly which can reduce carbon emissions and improve energy efficiency. However, there are still some barriers to the development of EVs. One of the main problems is lacking scientific planning of charging stations considering social, technological and environmental factors. To solve the problem, our paper proposes a Geographic Information System (GIS)-based AHP method to find optimal locations of electric vehicle charging stations (EVCSs) in Nanshan District, Shenzhen City. From the experimental result, the middle and southeast are more suitable to locate charging stations than other areas.18 alternative stations are selected considering the reality and existed charging stations.

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Data-driven intelligent location of public charging stations for electric vehicles

Cited by 73 publications

References 28 publications

A Multi-Step Approach Framework for Freight Forecasting of River-Sea Direct Transport without Direct Historical Data

A Multi-Step Approach Framework for Freight Forecasting of River-Sea Direct Transport without Direct Historical Data

Intake characteristics and pumping loss in the intake stroke of a novel small scale opposed rotary piston engine

Site selection for EVCSs by GIS-based AHP method

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