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Charging Control Strategy of Electric Vehicles Based on Particle Swarm Optimization

  • Boo, Chang-Jin (Dept. of Electrical Engineering, Jeju International University)
  • Received : 2018.06.25
  • Accepted : 2018.06.29
  • Published : 2018.06.30

Abstract

In this paper, proposed a multi-channel charging control strategy for electric vehicle. This control strategy can adjust the charging power according to the calculated state-of-charge (SOC). Electric vehicle (EV) charging system using Particle Swarm Optimization (PSO) algorithm is proposed. A stochastic optimization algorithm technique such as PSO in the time-of-use (TOU) price used for the energy cost minimization. Simulation results show that the energy cost can be reduced using proposed method.

Keywords

References

  1. Jeju Special Self-governing Province, "Carbon Free Island Jeju by 2030" Policy Report 2012.
  2. Cao, Y., Tang, S., Li, C., Zhang, P., Tan, Y., Zhang, Z., Li, J., "An optimized EV charging model considering TOU price and SOC curve," IEEE Trans. on Smart Grid. 3, pp. 388-393, 2012. DOI: 10.1109/TSG.2011.2159630
  3. Kennedy, J., Eberhart, R., "Swarm Intelligence,"Morgan Kaufmann Publishers, Inc. 2001.
  4. Park, J.B., Lee, K.S., Lee, K.Y., "A Particle Swarm Optimization for Economic Dispatch with Nonsmooth Cost Functions," IEEE Trans. on Power Systems 20, pp. 34-42, 2005. DOI: 10.1109/TPWRS.2004.831275
  5. Hong, K.D., Son, Y., "A Study on the Smart Virtual Machine for Executing Virtual Machine Codes on Smart Platforms," Oxford University Press, pp. 93-106, 2012.