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Utility-transit nexus: Leveraging intelligently charged electrified transit to support a renewable energy grid

Author

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  • Wellik, T.K.
  • Griffin, J.R.
  • Kockelman, K.M.
  • Mohamed, M.

Abstract

The transportation sector is a major greenhouse gas emitter. Concurrent electrification of vehicles and investment in renewable energy sources (RESs) is required to mitigate these emissions. The introduction of intermittent RESs such as solar and wind at a large scale presents challenges to utility operators. This study quantifies the opportunity a Vehicle-to-Grid (V2G) Battery Electric Bus (BEB) fleet offers in overcoming these challenges. A Gurobi optimization model was developed to simulate the reaction of grid operators to changing load and production values by seeking the lowest operational cost at each timestep. The optimization model is integrated with a BEB energy consumption model. The two models interact to optimally maintain necessary charge for the BEB fleet and support the grid load. An Austin, Texas case study is analyzed to investigate the role of BEB charging in buffering sharp changes in RES production to help smooth power demands from traditional energy sources of coal, natural gas, and nuclear power. A V2G BEB “smart charging” (SC) scenario is compared in cost and emissions to a BEB “charge-as-needed” and a diesel bus scenario. Without any SC strategies, the total external cost of the electricity grid and bus emissions falls by 3.42%, and with SC strategies these costs fall by 5.64%. Further, with SC strategies, the utility manager saved 22% of their daily cost in this case study. Overall, the study provides practical avenues for jointly utilizing renewable energy sources and electric mobility alternatives.

Suggested Citation

  • Wellik, T.K. & Griffin, J.R. & Kockelman, K.M. & Mohamed, M., 2021. "Utility-transit nexus: Leveraging intelligently charged electrified transit to support a renewable energy grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:rensus:v:139:y:2021:i:c:s1364032120309412
    DOI: 10.1016/j.rser.2020.110657
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    References listed on IDEAS

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    Cited by:

    1. Avenali, Alessandro & Catalano, Giuseppe & Giagnorio, Mirko & Matteucci, Giorgio, 2024. "Factors influencing the adoption of zero-emission buses: A review-based framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 197(C).
    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. Hatem Abdelaty & Moataz Mohamed, 2021. "A Prediction Model for Battery Electric Bus Energy Consumption in Transit," Energies, MDPI, vol. 14(10), pages 1-26, May.
    4. Foda, Ahmed & Mohamed, Moataz, 2024. "The impacts of optimization approaches on BEB system configuration in transit," Transport Policy, Elsevier, vol. 151(C), pages 12-23.
    5. 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).
    6. Yuan Chen & Seok Swoo Cho, 2024. "Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis," Sustainability, MDPI, vol. 16(17), pages 1-27, September.
    7. Shehabeldeen, Ali & Foda, Ahmed & Mohamed, Moataz, 2024. "A multi-stage optimization of battery electric bus transit with battery degradation," Energy, Elsevier, vol. 299(C).
    8. 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.

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