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Stochastic synergies of urban transportation system and smart grid in smart cities considering V2G and V2S concepts

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  • Jafari, Mina
  • Kavousi-Fard, Abdollah
  • Niknam, Taher
  • Avatefipour, Omid
Abstract
Serious challenges such as rapid growth in population, environmental pollution, and possibility of energy shortage have motivated researchers for designing optimal energy operation strategies through the concept of smart city. Buildings and electric transport systems, especially subway systems and Plug in Electric Vehicles (PEVs), are among the major energy consumption systems in a smart city. In this paper, a linear model is proposed for the co-optimization planning and operation of distributed energy resources and transportation systems in an interconnected system that analyzes the interactions of such an interconnected system. The idea of Regenerative Breaking Energy (RBE) is deployed to improve the operation of the subway system through the interconnected subway system in the smart city. For the optimal operation of the smart city, an optimization formulation is devised to minimize the total cost of the city in the presence of subway RBE. In this paper, the traffic and length of the routes are modeled considering Vehicle to Grid (V2G) and Vehicle to Subway (V2S) located in the parking lots. Furthermore, the degradation model is developed to increase the PEVs’ battery life. An unscented transformation (UT) approach is utilized to construct a stochastic framework based on the uncertainty method, to handle the uncertain behaviors of PEVs and distributed energy resource and loads in the smart city. Finally, the proposed model is implemented and its performance is analyzed in both the stochastic and deterministic frameworks.

Suggested Citation

  • Jafari, Mina & Kavousi-Fard, Abdollah & Niknam, Taher & Avatefipour, Omid, 2021. "Stochastic synergies of urban transportation system and smart grid in smart cities considering V2G and V2S concepts," Energy, Elsevier, vol. 215(PB).
    • Handle: RePEc:eee:energy:v:215:y:2021:i:pb:s0360544220321617
    DOI: 10.1016/j.energy.2020.119054
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    References listed on IDEAS

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    1. Lund, Henrik & Kempton, Willett, 2008. "Integration of renewable energy into the transport and electricity sectors through V2G," Energy Policy, Elsevier, vol. 36(9), pages 3578-3587, September.
    2. Mwasilu, Francis & Justo, Jackson John & Kim, Eun-Kyung & Do, Ton Duc & Jung, Jin-Woo, 2014. "Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 501-516.
    3. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J. & Martín, F., 2017. "Impact of EV penetration in the interconnected urban environment of a smart city," Energy, Elsevier, vol. 141(C), pages 2218-2233.
    4. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J., 2016. "Energy management and planning in smart cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 273-287.
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    Cited by:

    1. Zhou, Yuekuan, 2022. "A regression learner-based approach for battery cycling ageing prediction―advances in energy management strategy and techno-economic analysis," Energy, Elsevier, vol. 256(C).
    2. Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    3. Ben Arab, Marwa & Rekik, Mouna & Krichen, Lotfi, 2023. "A priority-based seven-layer strategy for energy management cooperation in a smart city integrated green technology," Applied Energy, Elsevier, vol. 335(C).
    4. Yin, Linfei & Luo, Shikui & Ma, Chenxiao, 2021. "Expandable depth and width adaptive dynamic programming for economic smart generation control of smart grids," Energy, Elsevier, vol. 232(C).

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