Data-driven optimized layout of battery electric vehicle charging infrastructure

Tao, Ye; Huang, Miaohua; Yang, Liang

doi:10.1016/j.energy.2018.03.018

Cited by 60 publications

(28 citation statements)

References 21 publications

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“…AI approaches have also been employed to assess the potential viability and impact of large-scale policy changes and other societal shifts. This includes top-down policy initiatives, such as carbon tax schemes (Abrell et al 2019 ) and carbon trading systems (Lu et al 2020 ), as well as detecting (Xiao et al 2019 ) and weighing the variables associated with different travel modes (Hagenauer and Helbich 2017 ), and optimising electric vehicle sharing (Miao et al 2019 ) and charging architecture (Tao et al 2018 ). Each of these could in turn boost the availability and uptake of more climate-friendly transportation options.…”

Section: Ai Against Climate Changementioning

confidence: 99%

The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations

et al. 2021

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In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment.

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Section: Ai Against Climate Changementioning

confidence: 99%

The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations

et al. 2021

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“…In cases where detailed Global Positioning System (GPS) data from vehicles are available, locations of charging demand can be estimated using a proxy, such as dwell time [32,33]. However, GPS based data are rarely available for research purposes; thus, the applicability of this methodology is limited.…”

Section: Methodologies Typically Applied In Researchmentioning

confidence: 99%

Location-Allocation of Electric Vehicle Fast Chargers—Research and Practice

Motoaki

2019

WEVJ

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This paper conducts a comparative analysis of academic research on location-allocation of electric vehicle fast chargers into the pattern of the actual fast-charger allocation in the United States. The work aims to highlight the gap between academic research and actual practice of charging-station placement and operation. It presents evidence that the node-serving approach is, in fact, applied in the actual location-allocation of fast charging stations. However, little evidence suggests that flow-capturing, which has been much more predominantly applied in research, is being applied in practice. The author argues that a large-scale location-allocation plan for public fast chargers should be formulated based on explicit consideration of stakeholders, the objective, practical constraints, and underlining assumptions.

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“…First, by strategically installing and managing the charging stations, the EVs can be an important source of flexibility for the energy balance, helping to prevent price spikes of electricity and to avoid the further upgrades of the grid capacity. For instance, Tao et al [7] optimised the layout of the battery-based EV charging infrastructure using real-world driving data. Their results show that compared to the current layout of the charging infrastructure, the overdischarging rate of the EVs can be reduced from 68.1% to 39.6% through the optimisation of the layout of EV charging infrastructures.…”

Section: ) Opportunities For Energy Interactions Between Buildings and Vehiclesmentioning

confidence: 99%

“…Recently, for battery-based EV integrated building systems, researchers have focused on multi-objective investigation and optimisation, including energy consumption, greenhouse gas (GHG) emission, annual matching capability, and annual operational cost. In the academic world, the research objectives and methodologies concerning battery-based EV integrated building systems can be classified into energy management strategy optimisation based on the uncertainty of both renewable generation and the driving schedule [3][4], economic performance enhancement by optimising the drivers' behaviour with respect to different building categories [5], an accurate sizing approach of the renewable capacity with high levels of EV integration [6], and optimisation of the layout of the EV charging infrastructure [7]. Meanwhile, integration of HVs with buildings has attracted increasing interest recently, especially with the availability of fourth-generation technologies such as the H2 storage tank with a maximum pressure of 700 bars [8][9] and fuel-cell technologies for the oxidation process of H2 [10][11].…”

Section: Introductionmentioning

confidence: 99%

Energy integration and interaction between buildings and vehicles: A state-of-the-art review

Zhou

Cao

Hensen

et al. 2019

Renewable and Sustainable Energy Reviews

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Clean power production, buildings, and transportation are key areas for climate change mitigation. Their tighter integration decreases not only the emissions, but also the energy consumption of buildings and transportation.Energy integration and interactions between buildings and vehicles are dependent on the type of building, vehicle, and renewable energy system, as well as the local climatic conditions. The current academic literature does not provide a systematic analysis of this topic. In the study, different energy management systems and advanced energy control strategies have been formulated to study such interactions both from a building and a vehicle perspective. Furthermore, technical solutions have been systematically reviewed in terms of the enhancement of energy interaction capabilities, in particular from the standpoint of renewable energy systems, energy/fuel charging facilities, and control strategies. Assessment criteria employed in the review of solutions include grid interaction, annual operational cost, annual net CO2 emissions, and annual matching capability. The literature review identifies several technical challenges that need further consideration such as capacity expansion and power fluctuation of the electric grid, low efficiency of heat recovered from electricity generation, and depreciation of vehicles. The future outlook and potential for the energy interaction networks between buildings and vehicles have also been presented.

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Data-driven optimized layout of battery electric vehicle charging infrastructure

Cited by 60 publications

References 21 publications

The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations

The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations

Location-Allocation of Electric Vehicle Fast Chargers—Research and Practice

Energy integration and interaction between buildings and vehicles: A state-of-the-art review

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