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A cooperative game theoretic analysis of electric vehicles parking lot in smart grid

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  • Aghajani, Saemeh
  • Kalantar, Mohsen

Abstract

Plug-in Hybrid Electric Vehicles (PHEVs) play a major role in decreasing amount of fossil fuels led by transportation system. PHEVs in both Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) modes can effect on the power market. In order to diminish potential challenges related to these effects, various methods like developing optimal charging strategies for the connected PHEVs and managing energy exchange between the PHEVs’ parking lots can be taken into consideration. In this paper, a cooperative game model has been proposed in order to determine charging/discharging price adaptively. Simulation results show how this model leads to the maximization of utilities’ profit and minimization of the parking lots’ cost. Furthermore, a stochastic analysis has been done over the proposed model in order to well understand how much the deviation of profit and expected value of profit are in different levels of uncertainty. The numerical results prove that higher deviation over spot market price leads to both higher mean and deviation over profit for utilities, and the owner of utilities should consider the effect of price’s uncertainty whenever it is considerable.

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  • Aghajani, Saemeh & Kalantar, Mohsen, 2017. "A cooperative game theoretic analysis of electric vehicles parking lot in smart grid," Energy, Elsevier, vol. 137(C), pages 129-139.
    • Handle: RePEc:eee:energy:v:137:y:2017:i:c:p:129-139
    DOI: 10.1016/j.energy.2017.07.006
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    1. Schuller, Alexander & Flath, Christoph M. & Gottwalt, Sebastian, 2015. "Quantifying load flexibility of electric vehicles for renewable energy integration," Applied Energy, Elsevier, vol. 151(C), pages 335-344.
    2. Zhang, Qi & Ishihara, Keiichi N. & Mclellan, Benjamin C. & Tezuka, Tetsuo, 2012. "Scenario analysis on future electricity supply and demand in Japan," Energy, Elsevier, vol. 38(1), pages 376-385.
    3. Neuhoff, Karsten & Barquin, Julian & Boots, Maroeska G. & Ehrenmann, Andreas & Hobbs, Benjamin F. & Rijkers, Fieke A.M. & Vazquez, Miguel, 2005. "Network-constrained Cournot models of liberalized electricity markets: the devil is in the details," Energy Economics, Elsevier, vol. 27(3), pages 495-525, May.
    4. Shafie-khah, Miadreza & Parsa Moghaddam, Mohsen & Sheikh-El-Eslami, Mohamad Kazem & Rahmani-Andebili, Mehdi, 2012. "Modeling of interactions between market regulations and behavior of plug-in electric vehicle aggregators in a virtual power market environment," Energy, Elsevier, vol. 40(1), pages 139-150.
    5. Su, Wencong & Chow, Mo-Yuen, 2012. "Computational intelligence-based energy management for a large-scale PHEV/PEV enabled municipal parking deck," Applied Energy, Elsevier, vol. 96(C), pages 171-182.
    6. Rangaraju, Surendraprabu & De Vroey, Laurent & Messagie, Maarten & Mertens, Jan & Van Mierlo, Joeri, 2015. "Impacts of electricity mix, charging profile, and driving behavior on the emissions performance of battery electric vehicles: A Belgian case study," Applied Energy, Elsevier, vol. 148(C), pages 496-505.
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    5. Li, Shuangqi & Zhao, Pengfei & Gu, Chenghong & Huo, Da & Zeng, Xianwu & Pei, Xiaoze & Cheng, Shuang & Li, Jianwei, 2022. "Online battery-protective vehicle to grid behavior management," Energy, Elsevier, vol. 243(C).
    6. Subramanian, Vignesh & Das, Tapas K., 2019. "A two-layer model for dynamic pricing of electricity and optimal charging of electric vehicles under price spikes," Energy, Elsevier, vol. 167(C), pages 1266-1277.
    7. Li, Shuangqi & Gu, Chenghong & Zeng, Xianwu & Zhao, Pengfei & Pei, Xiaoze & Cheng, Shuang, 2021. "Vehicle-to-grid management for multi-time scale grid power balancing," Energy, Elsevier, vol. 234(C).
    8. Aghajani, Saemeh & Kalantar, Mohsen, 2017. "Operational scheduling of electric vehicles parking lot integrated with renewable generation based on bilevel programming approach," Energy, Elsevier, vol. 139(C), pages 422-432.
    9. Tao, Ye & Huang, Miaohua & Yang, Lan, 2018. "Data-driven optimized layout of battery electric vehicle charging infrastructure," Energy, Elsevier, vol. 150(C), pages 735-744.
    10. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2017. "Integrating renewable energy sources by electric vehicle fleets under uncertainty," Energy, Elsevier, vol. 141(C), pages 2145-2153.
    11. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2019. "Two-stage stochastic optimization for cost-minimal charging of electric vehicles at public charging stations with photovoltaics," Applied Energy, Elsevier, vol. 242(C), pages 769-781.
    12. Mohammadi Landi, Meysam & Mohammadi, Mohammad & Rastegar, Mohammad, 2018. "Simultaneous determination of optimal capacity and charging profile of plug-in electric vehicle parking lots in distribution systems," Energy, Elsevier, vol. 158(C), pages 504-511.
    13. Varone, Alberto & Heilmann, Zeno & Porruvecchio, Guido & Romanino, Alessandro, 2024. "Solar parking lot management: An IoT platform for smart charging EV fleets, using real-time data and production forecasts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    14. Tang, Juan & Ji, Guan-Qun & Liu, Zhi & Sheu, Jiuh-Biing, 2024. "Electric vehicle battery-charging service and operations managing under different charging station construction modes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    15. Homa Rashidizadeh-Kermani & Hamid Reza Najafi & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2018. "Optimal Decision-Making Strategy of an Electric Vehicle Aggregator in Short-Term Electricity Markets," Energies, MDPI, vol. 11(9), pages 1-20, September.
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