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  • Energy Research
  • 11. Sustainability
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Tao Xu;
    Tao Xu
    ORCID
    Harvested from ORCID Public Data File

    Tao Xu in OpenAIRE
    Jianxin You; Hui Li; Luning Shao;

    The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2020 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2020
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2020 . Peer-reviewed
      License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2020
      Data sources: DOAJ
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    Authors: orcid Tao Xu;
    Tao Xu
    ORCID
    Harvested from ORCID Public Data File

    Tao Xu in OpenAIRE
    Jianxin You; Hui Li; Luning Shao;

    The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2020 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article
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    Data sources: UnpayWall
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    Energies
    Article . 2020
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2020 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2020
      Data sources: DOAJ
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Juan Liu; Feng Wang; Wenna Fan; Mengnan Gao;

    Under the “new normal”, China is facing more severe carbon emissions reduction targets. This paper estimates the carbon emission data of various provinces in China from 2008 to 2014, constructs a revised gravity model, and analyzes the network structure and effects of carbon emissions in various provinces by using social network analysis (SNA) and quadratic assignment procedure (QAP) analysis methods. The conclusions show that there are obvious spatial correlations between China’s provinces and regions in terms of carbon emissions: Tianjin, Shanghai, Zhejiang, Jiangsu and Guangdong are in the center of the carbon emission network, and play the role of “bridges”. Carbon emissions can be divided into four blocks: “bidirectional spillover block”, “net beneficial block”, “net spillover block” and “broker block”. The differences in the energy consumption, economic level and geographical location of the provinces have a significant impact on the spatial correlation relationship of carbon emissions. Finally, the improvement of the robustness of the overall network structure and the promotion of individual network centrality can significantly reduce the intensity of carbon emissions.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2018 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article
    License: CC BY
    Data sources: UnpayWall
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    Energies
    Article . 2018
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    addClaim
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    citations47
    popularityTop 10%
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    impulseTop 10%
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Energies
      Article . 2018 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Energies
      Article . 2018
      Data sources: DOAJ
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Juan Liu; Feng Wang; Wenna Fan; Mengnan Gao;

    Under the “new normal”, China is facing more severe carbon emissions reduction targets. This paper estimates the carbon emission data of various provinces in China from 2008 to 2014, constructs a revised gravity model, and analyzes the network structure and effects of carbon emissions in various provinces by using social network analysis (SNA) and quadratic assignment procedure (QAP) analysis methods. The conclusions show that there are obvious spatial correlations between China’s provinces and regions in terms of carbon emissions: Tianjin, Shanghai, Zhejiang, Jiangsu and Guangdong are in the center of the carbon emission network, and play the role of “bridges”. Carbon emissions can be divided into four blocks: “bidirectional spillover block”, “net beneficial block”, “net spillover block” and “broker block”. The differences in the energy consumption, economic level and geographical location of the provinces have a significant impact on the spatial correlation relationship of carbon emissions. Finally, the improvement of the robustness of the overall network structure and the promotion of individual network centrality can significantly reduce the intensity of carbon emissions.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2018 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article
    License: CC BY
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    Energies
    Article . 2018
    Data sources: DOAJ
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      Energies
      Article . 2018 . Peer-reviewed
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      Energies
      Article
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      Energies
      Article . 2018
      Data sources: DOAJ
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Bing Bu;
    Bing Bu
    ORCID
    Harvested from ORCID Public Data File

    Bing Bu in OpenAIRE
    Guoying Qin; Ling Li; Guojie Li;

    With the rapid development of urban rail transit, the energy consumption of trains is increasing dramatically. The shortage of electrical energy is becoming more and more serious. In this paper, a novel method is proposed to better use regenerative braking energy for energy saving. A ‘time slot and energy grid’ model is set up to analyze the utilization of regenerative energy among trains. Based on this model, an energy efficient strategy that integrates train dispatch with train control is designed. The running time of trains in sections, the dwell time of trains at stations and the headway can be adjusted to find the global optimal solution for energy saving. The operational data of Beijing Changping subway line and Beijing Yizhuang subway line are used in simulation to illustrate the effectiveness of the proposed method in different scenarios. Simulation results show that our approach can significantly improve the utilization of regenerative braking energy and minimize the energy consumption in different scenarios when compared with the existing method.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Energiesarrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Energies
    Article . 2018 . Peer-reviewed
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      Energies
      Article . 2018 . Peer-reviewed
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      Energies
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    Authors: orcid Bing Bu;
    Bing Bu
    ORCID
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    Bing Bu in OpenAIRE
    Guoying Qin; Ling Li; Guojie Li;

    With the rapid development of urban rail transit, the energy consumption of trains is increasing dramatically. The shortage of electrical energy is becoming more and more serious. In this paper, a novel method is proposed to better use regenerative braking energy for energy saving. A ‘time slot and energy grid’ model is set up to analyze the utilization of regenerative energy among trains. Based on this model, an energy efficient strategy that integrates train dispatch with train control is designed. The running time of trains in sections, the dwell time of trains at stations and the headway can be adjusted to find the global optimal solution for energy saving. The operational data of Beijing Changping subway line and Beijing Yizhuang subway line are used in simulation to illustrate the effectiveness of the proposed method in different scenarios. Simulation results show that our approach can significantly improve the utilization of regenerative braking energy and minimize the energy consumption in different scenarios when compared with the existing method.

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    Energies
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      Energies
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    Authors: orcid bw Yongsheng Cao;
    Yongsheng Cao
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Yongsheng Cao in OpenAIRE
    orcid Guanglin Zhang;
    Guanglin Zhang
    ORCID
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    Guanglin Zhang in OpenAIRE
    Demin Li; Lin Wang; +1 Authors

    With the development of renewable energy technology and communication technology in recent years, many residents now utilize renewable energy devices in their residences with energy storage systems. We have full confidence in the promising prospects of sharing idle energy with others in a community. However, it is a great challenge to share residents’ energy with others in a community to minimize the total cost of all residents. In this paper, we study the problem of energy management and task scheduling for a community with renewable energy and residential cogeneration, such as residential combined heat and power system (resCHP) to pay the least electricity bill. We take elastic and inelastic load demands into account which are delay intolerant and delay tolerant tasks in the community. The minimum cost problem of a non-cooperative community is extracted into a random non-convex optimization problem with some physical constraints. Our objective is to minimize the time-average cost for each resident in the community, including the cost of the external grid and natural gas. The Lyapunov optimization theory and a primal-dual gradient method are adopted to tackle this problem, which needs no future data and has low computational complexity. Furthermore, we design a cooperative renewable energy sharing algorithm based on State-action-reward-state-action (Sarsa) Algorithm, in the condition that each residence in the community is able to communicate with its neighbors by a central controller. Finally, extensive simulations are presented to validate the proposed algorithms by using practical data.

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    Energies
    Article . 2018 . Peer-reviewed
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    Energies
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    Energies
    Article . 2018
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    Authors: orcid bw Yongsheng Cao;
    Yongsheng Cao
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Yongsheng Cao in OpenAIRE
    orcid Guanglin Zhang;
    Guanglin Zhang
    ORCID
    Harvested from ORCID Public Data File

    Guanglin Zhang in OpenAIRE
    Demin Li; Lin Wang; +1 Authors

    With the development of renewable energy technology and communication technology in recent years, many residents now utilize renewable energy devices in their residences with energy storage systems. We have full confidence in the promising prospects of sharing idle energy with others in a community. However, it is a great challenge to share residents’ energy with others in a community to minimize the total cost of all residents. In this paper, we study the problem of energy management and task scheduling for a community with renewable energy and residential cogeneration, such as residential combined heat and power system (resCHP) to pay the least electricity bill. We take elastic and inelastic load demands into account which are delay intolerant and delay tolerant tasks in the community. The minimum cost problem of a non-cooperative community is extracted into a random non-convex optimization problem with some physical constraints. Our objective is to minimize the time-average cost for each resident in the community, including the cost of the external grid and natural gas. The Lyapunov optimization theory and a primal-dual gradient method are adopted to tackle this problem, which needs no future data and has low computational complexity. Furthermore, we design a cooperative renewable energy sharing algorithm based on State-action-reward-state-action (Sarsa) Algorithm, in the condition that each residence in the community is able to communicate with its neighbors by a central controller. Finally, extensive simulations are presented to validate the proposed algorithms by using practical data.

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    Energies
    Article . 2018 . Peer-reviewed
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    Energies
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    Energies
    Article . 2018
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      Energies
      Article . 2018 . Peer-reviewed
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      Energies
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      Energies
      Article . 2018
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    Authors: orcid Yuancheng Lin;
    Yuancheng Lin
    ORCID
    Harvested from ORCID Public Data File

    Yuancheng Lin in OpenAIRE
    orcid bw Chinhao Chong;
    Chinhao Chong
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Chinhao Chong in OpenAIRE
    orcid Linwei Ma;
    Linwei Ma
    ORCID
    Harvested from ORCID Public Data File

    Linwei Ma in OpenAIRE
    orcid Zheng Li;
    Zheng Li
    ORCID
    Harvested from ORCID Public Data File

    Zheng Li in OpenAIRE
    +1 Authors

    Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.

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    Energies
    Article . 2021 . Peer-reviewed
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    Energies
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      Energies
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      Energies
      Article . 2021
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    Authors: orcid Yuancheng Lin;
    Yuancheng Lin
    ORCID
    Harvested from ORCID Public Data File

    Yuancheng Lin in OpenAIRE
    orcid bw Chinhao Chong;
    Chinhao Chong
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Chinhao Chong in OpenAIRE
    orcid Linwei Ma;
    Linwei Ma
    ORCID
    Harvested from ORCID Public Data File

    Linwei Ma in OpenAIRE
    orcid Zheng Li;
    Zheng Li
    ORCID
    Harvested from ORCID Public Data File

    Zheng Li in OpenAIRE
    +1 Authors

    Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.

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    Energies
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    Energies
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    Authors: orcid Lung-Chien Chen;
    Lung-Chien Chen
    ORCID
    Harvested from ORCID Public Data File

    Lung-Chien Chen in OpenAIRE
    orcid Ching-Ho Tien;
    Ching-Ho Tien
    ORCID
    Harvested from ORCID Public Data File

    Ching-Ho Tien in OpenAIRE
    Sin-Liang Ou; Kun-Yi Lee; +5 Authors

    Perovskite CsPbBr3 quantum dot (CsPbBr3-QD) recovery was performed using lead scrap from lead storage batteries. The perovskite CsPbBr3-QD characteristics were analyzed using different PbO/recycled PbO2 ratios. Scanning electron microscopy (SEM) was used to observe the film surface morphology and cross-section. High-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) were used to observe the perovskite CsPbBr3-QDs’ structural characteristics. A photoluminescence (PL) measurement system was used to analyze the optical properties. The results show that lead scrap from lead–acid batteries as a material for perovskite CsPbBr3-QD production can be successfully synthesized. This saves material and also proves that recycling is valuable. The proposed approach is helpful for future material shortages and materials not easily accessible. Although the efficiency is not very high, this process will be purified using recycled lead in the future to achieve higher quantum yield.

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    Energies
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    Energies
    Article . 2019
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    Authors: orcid Lung-Chien Chen;
    Lung-Chien Chen
    ORCID
    Harvested from ORCID Public Data File

    Lung-Chien Chen in OpenAIRE
    orcid Ching-Ho Tien;
    Ching-Ho Tien
    ORCID
    Harvested from ORCID Public Data File

    Ching-Ho Tien in OpenAIRE
    Sin-Liang Ou; Kun-Yi Lee; +5 Authors

    Perovskite CsPbBr3 quantum dot (CsPbBr3-QD) recovery was performed using lead scrap from lead storage batteries. The perovskite CsPbBr3-QD characteristics were analyzed using different PbO/recycled PbO2 ratios. Scanning electron microscopy (SEM) was used to observe the film surface morphology and cross-section. High-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) were used to observe the perovskite CsPbBr3-QDs’ structural characteristics. A photoluminescence (PL) measurement system was used to analyze the optical properties. The results show that lead scrap from lead–acid batteries as a material for perovskite CsPbBr3-QD production can be successfully synthesized. This saves material and also proves that recycling is valuable. The proposed approach is helpful for future material shortages and materials not easily accessible. Although the efficiency is not very high, this process will be purified using recycled lead in the future to achieve higher quantum yield.

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    Energies
    Article . 2019 . Peer-reviewed
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    Authors: Tobias Erhart; Jürgen Gölz; Ursula Eicker; orcid Martijn Van den Broek;
    Martijn Van den Broek
    ORCID
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    Martijn Van den Broek in OpenAIRE

    The results in this work show the influence of long-term operation on the decomposition of working fluids in eight different organic rankine cycle (ORC) power plants (both heat-led and electricity-led) in a range of 900 kW el to 2 MW el . All case study plants are using octamethyltrisiloxane (MDM) as a working fluid; the facilities are between six to 12 years old. Detailed analyses, including the fluid distribution throughout the cycle, are conducted on one system. All presented fluid samples are analyzed via head space gas chromatography mass spectrometry (HS-GC-MS). Besides the siloxane composition, the influence of contaminants, such as mineral oil-based lubricants (and their components), is examined. In most cases, the original working fluid degrades to fractions of siloxanes with a lower boiling point (low boilers) and fractions with a higher boiling point (high boilers). As a consequence of the analyses, a new fluid recycling and management system was designed and tested in one case study plant (Case Study #8). Pre-post comparisons of fluid samples prove the effectiveness of the applied methods. The results show that the recovery of used working fluid offers an alternative to the purchase of fresh fluid, since operating costs can be significantly reduced. For large facilities, the prices for new fluid range from € 15 per liter (in 2006) to € 22 per liter (in 2013), which is a large reinvestment, especially in light of filling volumes of 4000 liters to 7000 liters per unit. Using the aforementioned method, a price of € 8 per liter of recovered MDM can be achieved.

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      Energies
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      Energies
      Article . 2016
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    Authors: Tobias Erhart; Jürgen Gölz; Ursula Eicker; orcid Martijn Van den Broek;
    Martijn Van den Broek
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    Harvested from ORCID Public Data File

    Martijn Van den Broek in OpenAIRE

    The results in this work show the influence of long-term operation on the decomposition of working fluids in eight different organic rankine cycle (ORC) power plants (both heat-led and electricity-led) in a range of 900 kW el to 2 MW el . All case study plants are using octamethyltrisiloxane (MDM) as a working fluid; the facilities are between six to 12 years old. Detailed analyses, including the fluid distribution throughout the cycle, are conducted on one system. All presented fluid samples are analyzed via head space gas chromatography mass spectrometry (HS-GC-MS). Besides the siloxane composition, the influence of contaminants, such as mineral oil-based lubricants (and their components), is examined. In most cases, the original working fluid degrades to fractions of siloxanes with a lower boiling point (low boilers) and fractions with a higher boiling point (high boilers). As a consequence of the analyses, a new fluid recycling and management system was designed and tested in one case study plant (Case Study #8). Pre-post comparisons of fluid samples prove the effectiveness of the applied methods. The results show that the recovery of used working fluid offers an alternative to the purchase of fresh fluid, since operating costs can be significantly reduced. For large facilities, the prices for new fluid range from € 15 per liter (in 2006) to € 22 per liter (in 2013), which is a large reinvestment, especially in light of filling volumes of 4000 liters to 7000 liters per unit. Using the aforementioned method, a price of € 8 per liter of recovered MDM can be achieved.

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    Energies
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    Energies
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    Energies
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    Energies
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      Energies
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      Energies
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    Authors: Jun Yang; Jiejun Chen; orcid Lei Chen;
    Lei Chen
    ORCID
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    Lei Chen in OpenAIRE
    Feng Wang; +2 Authors

    With the popularization of electric vehicles (EVs), the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU) electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU) electricity price.

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    Energies
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    Energies
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    Energies
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    Energies
    Article . 2016
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      Energies
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      Energies
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      Energies
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    Authors: Jun Yang; Jiejun Chen; orcid Lei Chen;
    Lei Chen
    ORCID
    Harvested from ORCID Public Data File

    Lei Chen in OpenAIRE
    Feng Wang; +2 Authors

    With the popularization of electric vehicles (EVs), the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU) electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU) electricity price.

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    Energies
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    Energies
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    Energies
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    Energies
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      Energies
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      Energies
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      Energies
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    Authors: Bongsuk Sung; Cui Wen;

    This study explores how political–economic forces could affect export performance in the renewable energy technologies market. We conduct panel framework analyses to verify the characteristics of panel data for 19 countries before establishing the panel estimator meant to test the effects of political–economic forces on export specialization. We consider the results of the panel framework analyses and develop an empirical model to test casual dynamic relationships between political–economic forces and export performance. The results from the least squares dummy variable-corrected estimation indicate that the major factors promoting the export specialization of renewable energy technologies are, in order of decreasing importance, public pressure, market size, and government demand-pull policy. However, the traditional energy industry has no significant effect on export performance. Finally, this study finds that dynamic effects exist in all estimations.

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    Authors: Bongsuk Sung; Cui Wen;

    This study explores how political–economic forces could affect export performance in the renewable energy technologies market. We conduct panel framework analyses to verify the characteristics of panel data for 19 countries before establishing the panel estimator meant to test the effects of political–economic forces on export specialization. We consider the results of the panel framework analyses and develop an empirical model to test casual dynamic relationships between political–economic forces and export performance. The results from the least squares dummy variable-corrected estimation indicate that the major factors promoting the export specialization of renewable energy technologies are, in order of decreasing importance, public pressure, market size, and government demand-pull policy. However, the traditional energy industry has no significant effect on export performance. Finally, this study finds that dynamic effects exist in all estimations.

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    Authors: orcid Jingjing Liu;
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    Hongwei Ge; orcid Jiajie Li;
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    Jiajie Li in OpenAIRE
    Pengcheng He; +2 Authors

    Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport.

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    Authors: orcid Jingjing Liu;
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    Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport.

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