Open Access
ITM Web Conf.
Volume 32, 2020
International Conference on Automation, Computing and Communication 2020 (ICACC-2020)
Article Number 01003
Number of page(s) 5
Section Automation
Published online 29 July 2020
  1. S. Soheil, S. Filizadeh, and E. Bibeau, “Profile of charging load on the grid due to plug-in vehicles,” IEEE Trans. Smart Grid, 3, 135-141 (2012) [Google Scholar]
  2. J. Zazo, S. Zazo, and S.V. Macua, “Robust worst case analysis of demand-side management in smart grids,” IEEE Trans. Smart Grid, 8, 662-673 (2017) [Google Scholar]
  3. Mou, Yuting, Hao Xing, Zhiyun Lin, and Minyue Fu. “Decentralized optimal demand-side management for PHEV charging in a smart grid.” IEEE Transactions on Smart Grid, 6, 726-736 (2014) [Google Scholar]
  4. Quirós-Tortós, Jairo, Luis F. Ochoa, and Becky Lees. “A statistical analysis of EV charging behavior in the UK.” In 2015 IEEE PES Innovative Smart Grid Technologies Latin America (ISGT LATAM), 445-449 (2015) [Google Scholar]
  5. J.T. Salihi, “Energy requirements for electric cars and their impact on electric generation and distribution systems,” IEEE Trans. Ind. Appl. 5, 516-531 (1973) [Google Scholar]
  6. J.C. Gomez and M.M. Morcos, “Impact of EV battery chargers on the power quality of distribution systems,” IEEE Trans. Power Del., 18, 975-981 (2003) [Google Scholar]
  7. Kaur, Sachpreet, Tarlochan Kaur, Rintu Khanna, and Parampal Singh. “A state of the art of DC microgrids for electric vehicle charging.” In 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC), 381-386 (2017). [Google Scholar]
  8. M.C. Falvo, G. Graditi, and P. Siano, “Electric vehicles integration in demand response programs,” in Proc. Int. Symp. Power Electron. Elect. Drives Autom. Motion, 548-553 (2014) [Google Scholar]
  9. Falahati, Saber, Seyed Abbas Taher, and Mohammad Shahidehpour. “Grid frequency control with electric vehicles by using of an optimized fuzzy controller.” Applied energy, 178, 918-928 (2016). [Google Scholar]
  10. Kaur, Sachpreet, Tarlochan Kaur, and Rintu Khanna. “ANFIS Based Frequency Control in an Autonomous Microgrid Integrated with PV and Battery Storage.” In 2019 9th International Conference on Power and Energy Systems (ICPES), 1-4 (2019) [Google Scholar]
  11. Schuller, Alexander. “Charging coordination paradigms of electric vehicles.” In Plug in Electric Vehicles in Smart Grids, Springer, Singapore,1-21 (2015). [Google Scholar]
  12. L. Jia and L. Tong, “Dynamic pricing and distributed energy management for demand response,” IEEE Trans. Smart Grid, 7, 1128-1136 (2016). [Google Scholar]
  13. S. Sarabi and L. Kefsi, “Electric vehicle charging strategy based on a dynamic programming algorithm,” in Proc. Int. Conf. Intell. Energy Power Syst. (IEPS), 1-5 (2014) [Google Scholar]
  14. Hutson, Chris, Ganesh Kumar Venayagamoorthy, and Keith A. Corzine. “Intelligent scheduling of hybrid and electric vehicle storage capacity in a parking lot for profit maximization in grid power transactions.” In 2008 IEEE Energy 2030 Conference, 1-8 (2008) [Google Scholar]
  15. D. Linden and T.B. Reddy, Handbook of Batteries, 3rd ed. New York, McGraw-Hill, (2001) [Google Scholar]
  16. Qian, Kejun, Chengke Zhou, Malcolm Allan, and Yue Yuan. “Modeling of load demand due to EV battery charging in distribution systems.” IEEE transactions on power systems 26, 802-810 (2010) [Google Scholar]
  17. López, Karol Lina, Christian Gagné, and Marc-André Gardner. “Demand-side management using deep learning for smart charging of electric vehicles.” IEEE Transactions on Smart Grid 10, 2683-2691 (2018) [Google Scholar]
  18. Madrid, Christopher, Juan Argueta, and Jordan Smith. “Performance characterization—1999 Nissan Altra-EV with lithium-ion battery.” Southern California EDISON (1999). [Google Scholar]
  19. System Advisory Model (SAM) [On-line](2018) Website: [Google Scholar]

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