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An Electric Bus Power Consumption Model and Optimization of Charging Scheduling Concerning Multi-External Factors

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  • Yajing Gao

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China)

  • Shixiao Guo

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China)

  • Jiafeng Ren

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China)

  • Zheng Zhao

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Ali Ehsan

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Yanan Zheng

    (Energy Research Institute, Academy of Macroeconomic Research, NDRC, Beijing 100038, China)

Abstract

With the large scale operation of electric buses (EBs), the arrangement of their charging optimization will have a significant impact on the operation and dispatch of EBs as well as the charging costs of EB companies. Thus, an accurate grasp of how external factors, such as the weather and policy, affect the electric consumption is of great importance. Especially in recent years, haze is becoming increasingly serious in some areas, which has a prominent impact on driving conditions and resident travel modes. Firstly, the grey relational analysis (GRA) method is used to analyze the various external factors that affect the power consumption of EBs, then a characteristic library of EBs concerning similar days is established. Then, the wavelet neural network (WNN) is used to train the power consumption factors together with power consumption data in the feature library, to establish the power consumption prediction model with multiple factors. In addition, the optimal charging model of EBs is put forward, and the reasonable charging time for the EB is used to achieve the minimum operating cost of the EB company. Finally, taking the electricity consumption data of EBs in Baoding and the data of relevant factors as an example, the power consumption prediction model and the charging optimization model of the EB are verified, which provides an important reference for the optimal charging of the EB, the trip arrangement of the EB, and the maximum profit of the electric public buses.

Suggested Citation

  • Yajing Gao & Shixiao Guo & Jiafeng Ren & Zheng Zhao & Ali Ehsan & Yanan Zheng, 2018. "An Electric Bus Power Consumption Model and Optimization of Charging Scheduling Concerning Multi-External Factors," Energies, MDPI, vol. 11(8), pages 1-17, August.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2060-:d:162604
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    References listed on IDEAS

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    Cited by:

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    2. 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.
    3. Orhan Topal & İsmail Nakir, 2018. "Total Cost of Ownership Based Economic Analysis of Diesel, CNG and Electric Bus Concepts for the Public Transport in Istanbul City," Energies, MDPI, vol. 11(9), pages 1-17, September.
    4. Izabela Zoltowska & Jeremy Lin, 2021. "Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids," Energies, MDPI, vol. 14(16), pages 1-18, August.
    5. 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.
    6. Zhao, Li & Ke, Hanchen & Huo, Weiwei, 2023. "A frequency item mining based energy consumption prediction method for electric bus," Energy, Elsevier, vol. 263(PD).
    7. Papa, Gregor & Santo Zarnik, Marina & Vukašinović, Vida, 2022. "Electric-bus routes in hilly urban areas: Overview and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    8. Eckard Helmers & Johannes Dietz & Martin Weiss, 2020. "Sensitivity Analysis in the Life-Cycle Assessment of Electric vs. Combustion Engine Cars under Approximate Real-World Conditions," Sustainability, MDPI, vol. 12(3), pages 1-31, February.
    9. Li, Pengshun & Zhang, Yi & Zhang, Yi & Zhang, Kai & Jiang, Mengyan, 2021. "The effects of dynamic traffic conditions, route characteristics and environmental conditions on trip-based electricity consumption prediction of electric bus," Energy, Elsevier, vol. 218(C).
    10. Jean-Michel Clairand & Paulo Guerra-Terán & Xavier Serrano-Guerrero & Mario González-Rodríguez & Guillermo Escrivá-Escrivá, 2019. "Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies," Energies, MDPI, vol. 12(16), pages 1-22, August.
    11. Adnane Houbbadi & Rochdi Trigui & Serge Pelissier & Eduardo Redondo-Iglesias & Tanguy Bouton, 2019. "Optimal Scheduling to Manage an Electric Bus Fleet Overnight Charging," Energies, MDPI, vol. 12(14), pages 1-17, July.
    12. Junpeng Cai & Dewang Chen & Shixiong Jiang & Weijing Pan, 2020. "Dynamic-Area-Based Shortest-Path Algorithm for Intelligent Charging Guidance of Electric Vehicles," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    13. Andrzej Łebkowski, 2019. "Studies of Energy Consumption by a City Bus Powered by a Hybrid Energy Storage System in Variable Road Conditions," Energies, MDPI, vol. 12(5), pages 1-39, March.
    14. Foda, Ahmed & Abdelaty, Hatem & Mohamed, Moataz & El-Saadany, Ehab, 2023. "A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling," Energy, Elsevier, vol. 277(C).
    15. Zeng, Ziling & Wang, Shuaian & Qu, Xiaobo, 2022. "On the role of battery degradation in en-route charge scheduling for an electric bus system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    16. Ali Saadon Al-Ogaili & Ali Q. Al-Shetwi & Hussein M. K. Al-Masri & Thanikanti Sudhakar Babu & Yap Hoon & Khaled Alzaareer & N. V. Phanendra Babu, 2021. "Review of the Estimation Methods of Energy Consumption for Battery Electric Buses," Energies, MDPI, vol. 14(22), pages 1-28, November.
    17. Jean-Michel Clairand & Javier Rodríguez-García & Carlos Álvarez-Bel, 2018. "Electric Vehicle Charging Strategy for Isolated Systems with High Penetration of Renewable Generation," Energies, MDPI, vol. 11(11), pages 1-21, November.
    18. 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.
    19. Brinkel, Nico & Zijlstra, Marle & van Bezu, Ronald & van Twuijver, Tim & Lampropoulos, Ioannis & van Sark, Wilfried, 2023. "A comparative analysis of charging strategies for battery electric buses in wholesale electricity and ancillary services markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
    20. Teresa Pamuła & Wiesław Pamuła, 2020. "Estimation of the Energy Consumption of Battery Electric Buses for Public Transport Networks Using Real-World Data and Deep Learning," Energies, MDPI, vol. 13(9), pages 1-17, May.
    21. Li, Pengshun & Zhang, Yuhang & Zhang, Yi & Zhang, Yi & Zhang, Kai, 2021. "Prediction of electric bus energy consumption with stochastic speed profile generation modelling and data driven method based on real-world big data," Applied Energy, Elsevier, vol. 298(C).
    22. Feifeng Zheng & Zhaojie Wang & Ming Liu, 2022. "Overnight charging scheduling of battery electric buses with uncertain charging time," Operational Research, Springer, vol. 22(5), pages 4865-4903, November.

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