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Evaluating grid-interactive electric bus operation and demand response with load management tariff

Author

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  • Wu, Z.
  • Guo, F.
  • Polak, J.
  • Strbac, G.

Abstract

Electric Vehicles are expected to play a vital role in the transition of smart energy systems. Lots of recent research has explored numerous underlying mechanisms to achieve the synergetic interactions in the electricity balancing process. In this paper, the grid-interactive operation of electric buses is first time integrated within a dynamic market frame using the Distribution Locational Marginal Price algorithm for load congestion management. Since the defined problem correlates the opportunity charging flexibility with the bus mobility over a network, the tempo-spatial distribution of energy needs can be reflected in the dynamic of service planning. The interactions between bus operators and suppliers are quantitatively modelled by a bi-level optimisation process to represent the electric bus service planning and electricity market clearing separately. The effectiveness of the proposed load management has been demonstrated using data collected from an integrated real-world bus network. Experiments show that engagement of electric bus charging load in demand response is helpful to alleviate the network congestion and to reduce the power loss by 7.2% in the distribution network. However, alleviated charging loads have exhibited counter-intuitive capability for load shifting. The restricted electric bus operational requirements leads to a 8.17% loss of charging demand, while the reliance on large batteries has increased by 10.57%. However, the sensitivity analysis also shows that as the battery cost declines, the such discourage implications on grid-interactive electric bus operation will decrease once the battery cost below 190/kWh. The optimal grid-ebus integration have to consider the trade-off between range add-up, reduced battery cost and additional benefits.

Suggested Citation

  • Wu, Z. & Guo, F. & Polak, J. & Strbac, G., 2019. "Evaluating grid-interactive electric bus operation and demand response with load management tariff," Applied Energy, Elsevier, vol. 255(C).
  • Handle: RePEc:eee:appene:v:255:y:2019:i:c:s0306261919314850
    DOI: 10.1016/j.apenergy.2019.113798
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    Citations

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    Cited by:

    1. Kristián Čulík & Vladimíra Štefancová & Karol Hrudkay & Ján Morgoš, 2021. "Interior Heating and Its Influence on Electric Bus Consumption," Energies, MDPI, vol. 14(24), pages 1-19, December.
    2. Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2024. "Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges," Energy, Elsevier, vol. 300(C).
    3. Dwi Novirani & Hari Adianto, 2020. "Relation of Service Quality, Load Factors and Tariff on Bus City of Bandung," International Review of Management and Marketing, Econjournals, vol. 10(4), pages 152-160.
    4. Tang, Chong & Liu, Mingbo & Xie, Min & Dong, Ping & Zhu, Jianquan & Lin, Shunjiang, 2021. "A single-leader and multiple-follower stackelberg model for the look-ahead dispatch of plug-in electric buses in multiple microgrids," Energy, Elsevier, vol. 214(C).
    5. Zeng, Bo & Luo, Yangfan, 2022. "Potential of harnessing operational flexibility from public transport hubs to improve reliability and economic performance of urban multi-energy systems: A holistic assessment framework," Applied Energy, Elsevier, vol. 322(C).
    6. Boud Verbrugge & Mohammed Mahedi Hasan & Haaris Rasool & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2021. "Smart Integration of Electric Buses in Cities: A Technological Review," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    7. Ruengwit Khwanrit & Saher Javaid & Yuto Lim & Chalie Charoenlarpnopparut & Yasuo Tan, 2024. "Optimal Vehicle-to-Grid Strategies for Energy Sharing Management Using Electric School Buses," Energies, MDPI, vol. 17(16), pages 1-25, August.
    8. Lv, Si & Wei, Zhinong & Chen, Sheng & Sun, Guoqiang & Wang, Dan, 2021. "Integrated demand response for congestion alleviation in coupled power and transportation networks," Applied Energy, Elsevier, vol. 283(C).
    9. Manzolli, Jônatas Augusto & Trovão, João Pedro F. & Henggeler Antunes, Carlos, 2022. "Electric bus coordinated charging strategy considering V2G and battery degradation," Energy, Elsevier, vol. 254(PA).
    10. Meng, Yan & Fan, Shuai & Shen, Yu & Xiao, Jucheng & He, Guangyu & Li, Zuyi, 2023. "Transmission and distribution network-constrained large-scale demand response based on locational customer directrix load for accommodating renewable energy," Applied Energy, Elsevier, vol. 350(C).
    11. Xuewen Geng & Fengbin An & Chengmin Wang & Xi He, 2023. "Battery Swapping Station Pricing Optimization Considering Market Clearing and Electric Vehicles’ Driving Demand," Energies, MDPI, vol. 16(8), pages 1-14, April.
    12. Manzolli, Jônatas Augusto & Trovão, João Pedro & Antunes, Carlos Henggeler, 2022. "A review of electric bus vehicles research topics – Methods and trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    13. Kayhan Alamatsaz & Sadam Hussain & Chunyan Lai & Ursula Eicker, 2022. "Electric Bus Scheduling and Timetabling, Fast Charging Infrastructure Planning, and Their Impact on the Grid: A Review," Energies, MDPI, vol. 15(21), pages 1-39, October.
    14. Amra Jahic & Felix Heider & Maik Plenz & Detlef Schulz, 2022. "Flexibility Quantification and the Potential for Its Usage in the Case of Electric Bus Depots with Unidirectional Charging," Energies, MDPI, vol. 15(10), pages 1-18, May.
    15. Wenz, Klaus-Peter & Serrano-Guerrero, Xavier & Barragán-Escandón, Antonio & González, L.G. & Clairand, Jean-Michel, 2021. "Route prioritization of urban public transportation from conventional to electric buses: A new methodology and a study of case in an intermediate city of Ecuador," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).

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