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A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles

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  • He, Lifu
  • Yang, Jun
  • Yan, Jun
  • Tang, Yufei
  • He, Haibo

Abstract

Electric vehicle (EV) is a promising, environmental friendly technique for its potential to reduce the using of fossil fuels. Massive EVs pose both opportunities and challenges for power systems, especially with the growing amount of wind-power integration. This paper investigates the problem of collaborative optimization scheduling of generators, EVs and wind power. A novel bi-layer optimization of transmission and distribution system is proposed to solve the scheduling problem of EVs charging and discharging load from respective time and space domain in the presence of wind-power. The upper layer optimization in transmission grid coordinates EVs with thermal generators, base load, with the consideration of wind power, to optimize load periods of EVs in the time domain. The lower layer optimization in distribution grid then spatially schedules the location of EVs load. Based on a power system benchmark with a 10-unit transmission grid and an IEEE 33-bus distribution grid, the performance of the proposed bi-layer optimization strategy is evaluated. The impacts of electricity price profile, EVs penetration and EVs load location are analyzed. Simulation results show that the proposed bi-layer optimization strategy can accommodate wind power and improve both the economics of grid operation and benefits of EV users by scheduling EVs charging and discharging temporally and spatially. Also, the results have shown that the location of EVs charging and discharging load is critical for the distribution network planning.

Suggested Citation

  • He, Lifu & Yang, Jun & Yan, Jun & Tang, Yufei & He, Haibo, 2016. "A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles," Applied Energy, Elsevier, vol. 168(C), pages 179-192.
    • Handle: RePEc:eee:appene:v:168:y:2016:i:c:p:179-192
    DOI: 10.1016/j.apenergy.2016.01.089
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    1. Fernandes, Camila & Frías, Pablo & Latorre, Jesús M., 2012. "Impact of vehicle-to-grid on power system operation costs: The Spanish case study," Applied Energy, Elsevier, vol. 96(C), pages 194-202.
    2. Yagcitekin, Bunyamin & Uzunoglu, Mehmet, 2016. "A double-layer smart charging strategy of electric vehicles taking routing and charge scheduling into account," Applied Energy, Elsevier, vol. 167(C), pages 407-419.
    3. Amirioun, Mohammad Hassan & Kazemi, Ahad, 2014. "A new model based on optimal scheduling of combined energy exchange modes for aggregation of electric vehicles in a residential complex," Energy, Elsevier, vol. 69(C), pages 186-198.
    4. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
    5. Jian, Linni & Zheng, Yanchong & Xiao, Xinping & Chan, C.C., 2015. "Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid," Applied Energy, Elsevier, vol. 146(C), pages 150-161.
    6. Foley, Aoife & Tyther, Barry & Calnan, Patrick & Ó Gallachóir, Brian, 2013. "Impacts of Electric Vehicle charging under electricity market operations," Applied Energy, Elsevier, vol. 101(C), pages 93-102.
    7. Honarmand, Masoud & Zakariazadeh, Alireza & Jadid, Shahram, 2014. "Optimal scheduling of electric vehicles in an intelligent parking lot considering vehicle-to-grid concept and battery condition," Energy, Elsevier, vol. 65(C), pages 572-579.
    8. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    9. Yang, Jun & He, Lifu & Fu, Siyao, 2014. "An improved PSO-based charging strategy of electric vehicles in electrical distribution grid," Applied Energy, Elsevier, vol. 128(C), pages 82-92.
    10. Yang, Zhile & Li, Kang & Foley, Aoife, 2015. "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 396-416.
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    2. Zhang, Yachao & Le, Jian & Liao, Xiaobing & Zheng, Feng & Liu, Kaipei & An, Xueli, 2018. "Multi-objective hydro-thermal-wind coordination scheduling integrated with large-scale electric vehicles using IMOPSO," Renewable Energy, Elsevier, vol. 128(PA), pages 91-107.
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