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Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid

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  • Jian, Linni
  • Zheng, Yanchong
  • Xiao, Xinping
  • Chan, C.C.

Abstract

Vehicle-to-grid (V2G) operation of plug-in electric vehicles (PEVs) is attracting increasing attention since it can assist to improve the efficiency and reliability of power grid, as well as reduce the operating cost and greenhouse gas emission of electric vehicles. Within the scheme of V2G operation, PEVs are expected to serve as a novel distributed energy storage system (ESS) to help achieve the balance between supply and demand of power grid. One of the key difficulties concerning its practical implementation lies in that the availability of PEVs as ESS for grid remains highly uncertain due to their mobility as transportation tools. To address this issue, a novel event-triggered scheduling scheme for V2G operation based on the scenario of stochastic PEV connection to smart grid is proposed in this paper. Firstly, the mathematical model is formulated. Secondly, the preparation of input data for systematic evaluation is introduced and the case study is conducted. Finally, statistic analysis results demonstrate that our proposed V2G scheduling scheme can dramatically smooth out the fluctuation in power load profiles.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:146:y:2015:i:c:p:150-161
    DOI: 10.1016/j.apenergy.2015.02.030
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    as
    1. Noel, Lance & McCormack, Regina, 2014. "A cost benefit analysis of a V2G-capable electric school bus compared to a traditional diesel school bus," Applied Energy, Elsevier, vol. 126(C), pages 246-255.
    2. Guille, Christophe & Gross, George, 2009. "A conceptual framework for the vehicle-to-grid (V2G) implementation," Energy Policy, Elsevier, vol. 37(11), pages 4379-4390, November.
    3. Dallinger, David & Gerda, Schubert & Wietschel, Martin, 2013. "Integration of intermittent renewable power supply using grid-connected vehicles – A 2030 case study for California and Germany," Applied Energy, Elsevier, vol. 104(C), pages 666-682.
    4. 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.
    5. Doucette, Reed T. & McCulloch, Malcolm D., 2011. "Modeling the prospects of plug-in hybrid electric vehicles to reduce CO2 emissions," Applied Energy, Elsevier, vol. 88(7), pages 2315-2323, July.
    6. Perujo, Adolfo & Ciuffo, Biagio, 2010. "The introduction of electric vehicles in the private fleet: Potential impact on the electric supply system and on the environment. A case study for the Province of Milan, Italy," Energy Policy, Elsevier, vol. 38(8), pages 4549-4561, August.
    7. Di Giorgio, Alessandro & Liberati, Francesco, 2014. "Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models," Applied Energy, Elsevier, vol. 128(C), pages 119-132.
    8. García-Villalobos, J. & Zamora, I. & San Martín, J.I. & Asensio, F.J. & Aperribay, V., 2014. "Plug-in electric vehicles in electric distribution networks: A review of smart charging approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 717-731.
    9. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    10. Zhong, Jin & He, Lina & Li, Canbing & Cao, Yijia & Wang, Jianhui & Fang, Baling & Zeng, Long & Xiao, Guoxuan, 2014. "Coordinated control for large-scale EV charging facilities and energy storage devices participating in frequency regulation," Applied Energy, Elsevier, vol. 123(C), pages 253-262.
    11. Weis, Allison & Jaramillo, Paulina & Michalek, Jeremy, 2014. "Estimating the potential of controlled plug-in hybrid electric vehicle charging to reduce operational and capacity expansion costs for electric power systems with high wind penetration," Applied Energy, Elsevier, vol. 115(C), pages 190-204.
    12. 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.
    13. Broeer, Torsten & Fuller, Jason & Tuffner, Francis & Chassin, David & Djilali, Ned, 2014. "Modeling framework and validation of a smart grid and demand response system for wind power integration," Applied Energy, Elsevier, vol. 113(C), pages 199-207.
    14. 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.
    15. Khayyam, Hamid & Abawajy, Jemal & Javadi, Bahman & Goscinski, Andrzej & Stojcevski, Alex & Bab-Hadiashar, Alireza, 2013. "Intelligent battery energy management and control for vehicle-to-grid via cloud computing network," Applied Energy, Elsevier, vol. 111(C), pages 971-981.
    16. Millo, Federico & Rolando, Luciano & Fuso, Rocco & Mallamo, Fabio, 2014. "Real CO2 emissions benefits and end user’s operating costs of a plug-in Hybrid Electric Vehicle," Applied Energy, Elsevier, vol. 114(C), pages 563-571.
    17. 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.
    18. Bishop, Justin D.K. & Axon, Colin J. & Bonilla, David & Tran, Martino & Banister, David & McCulloch, Malcolm D., 2013. "Evaluating the impact of V2G services on the degradation of batteries in PHEV and EV," Applied Energy, Elsevier, vol. 111(C), pages 206-218.
    19. Han, Sekyung & Han, Soohee & Aki, Hirohisa, 2014. "A practical battery wear model for electric vehicle charging applications," Applied Energy, Elsevier, vol. 113(C), pages 1100-1108.
    20. Deihimi, Ali & Orang, Omid & Showkati, Hemen, 2013. "Short-term electric load and temperature forecasting using wavelet echo state networks with neural reconstruction," Energy, Elsevier, vol. 57(C), pages 382-401.
    21. Sorrentino, Marco & Rizzo, Gianfranco & Sorrentino, Luca, 2014. "A study aimed at assessing the potential impact of vehicle electrification on grid infrastructure and road-traffic green house emissions," Applied Energy, Elsevier, vol. 120(C), pages 31-40.
    22. Liu, Nian & Tang, Qingfeng & Zhang, Jianhua & Fan, Wei & Liu, Jie, 2014. "A hybrid forecasting model with parameter optimization for short-term load forecasting of micro-grids," Applied Energy, Elsevier, vol. 129(C), pages 336-345.
    23. Arslan, Okan & Karasan, Oya Ekin, 2013. "Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks," Energy, Elsevier, vol. 60(C), pages 116-124.
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