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Transforming public transport depots into profitable energy hubs

Nature Energy (2024)Cite this article

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Abstract

Transportation is undergoing rapid electrification, with electric buses at the forefront of public transport, especially in China. This transition, however, could strain electricity grids. Using a large-scale dataset with over 200 million global positioning system records from 20,992 buses in Beijing, we explore the technical, economic and environmental implications of transforming public transport depots into renewable energy hubs. Here we show that solar photovoltaic reduces the grid’s net charging load by 23% during electricity generation periods and lowers the net charging peak load by 8.6%. Integrating energy storage amplifies these reductions to 28% and 37.4%, respectively. Whereas unsubsidized solar photovoltaic yields profit 64% above costs, adding battery storage cuts profits to 31% despite offering grid benefits. Negative marginal abatement gains for CO2 emissions underscore the economic sustainability. Our findings provide a model for cities worldwide to accelerate their commitments towards sustainable transport and energy systems.

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Fig. 1: Data-driven framework for analysing comprehensive implications of transforming public transport depots into energy hubs.
Fig. 2: Bus fleet electrification results in the baseline scenario.
Fig. 3: Electric public transport network integrated with rooftop solar PV and energy storage.
Fig. 4: Net-load impacts on the grid under each market scenario at energy hubs.
Fig. 5: Economic analysis of solar PV and energy storage.

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Data availability

The geolocation and rooftop area data of bus depots in Beijing are available from AMAP (Gaode Map) (https://www.amap.com/). The sampling data of historical energy consumption and charging profiles for battery electric buses in Beijing are available via an existing research article (https://www.pnas.org/doi/10.1073/pnas.2017318118) (ref. 41). The Beijing weekday load data for different months are available at https://www.ndrc.gov.cn/xxgk/zcfb/tz/201912/t20191230_1216857_ext.html. The projected global electricity generation and the corresponding carbon emissions from 2020 to 2050 are available at https://www.iea.org/reports/net-zero-by-2050. The two-part tariff of electricity price scheme for sizeable industrial electricity consumption in Beijing is available at https://www.beijing.gov.cn/zhengce/zhengcefagui/201905/W020190522525837842583.pdf. The datasets of air temperature, direct normal irradiance and diffuse horizontal irradiance are available from the China Meteorological Administration, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. The data are, however, available from the authors upon reasonable request and with the permission of the China Meteorological Administration. The GPS trajectory data of 1,000 buses are available at https://github.com/Lejin99/GPS-data-of-1000-buses-in-Beijing. The source file for ref. 32 can be accessed via https://github.com/Lejin99/2022-Beijing-Public-Transport-Statistics-Report. The other datasets that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The vehicle GPS trajectory data were processed using SQL Server and Python. The mixed integer linear programming models were solved using Gurobi. All the codes are available on request from the corresponding author.

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Acknowledgements

X.M. acknowledges funding from Beijing Nova Program (20230484432) and National Key R&D Program of China (2023YFB2604600). S.Y. and P.P. gratefully acknowledge support by the EU STORM project funded from the European Union’s Horizon 2020 programme (grant agreement number 101006700). P.P. has been supported within the project HOLA (FKZ 03EMF0404A) funded by the German Federal Ministry for Digital and Transport. S.Y. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 821124 and Mistra Carbon Exit.

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Authors and Affiliations

  1. School of Transportation Science and Engineering, Beihang University, Beijing, China

    Xiaohan Liu, Zhengke Liu & Xiaolei Ma

  2. Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, Sweden

    Xiaohan Liu

  3. Fraunhofer Institute for Systems and Innovation Research ISI, Karlsruhe, Germany

    Patrick Plötz

  4. Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Sweden

    Sonia Yeh

  5. Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, UT, USA

    Xiaoyue Cathy Liu

  6. Key Laboratory of Intelligent Transportation Technology and System, Ministry of Education, Beijing, China

    Xiaolei Ma

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Contributions

X.L. and X.M. conceived and designed the study in consultation with P.P., S.Y. and X.C.L. X.L. collected the data, implemented the model and created the visualizations. Z.L. processed the bus GPS data. P.P., S.Y., X.L. and X.M. wrote the original manuscript with contributions from all co-authors.

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Correspondence to Xiaolei Ma.

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Nature Energy thanks Kelvin Say and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Notes 1 and 2, Tables 1–7, Figs. 1–14 and refs. 1–20.

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Liu, X., Plötz, P., Yeh, S. et al. Transforming public transport depots into profitable energy hubs. Nat Energy (2024). https://doi.org/10.1038/s41560-024-01580-0

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