Title page for etd-1001113-154640


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URN etd-1001113-154640
Author Hung-Ju Liu
Author's Email Address lhl2327@gmail.com
Statistics This thesis had been viewed 5355 times. Download 601 times.
Department Electrical Engineering
Year 2013
Semester 1
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title A Study of Electric Vehicle Charging Station Planning Considering Distribution System Operations
Date of Defense 2013-08-16
Page Count 80
Keyword
  • markov chain
  • genetic algorithm
  • smart grid
  • distribution system
  • charging station planning
  • electric vehicle
  • Abstract Electric Vehicle will be a critical part of automobile market. Since the EV penetration rate is rising, there should be enough charging infrastructure to fulfill the EV charging demands. Charging load at home or at the charging station will both cause negative impacts to the existing distribution system operations. Therefore EV charging station planning must consider the users’ demand and operation constraints of power system. This thesis uses a non-homogeneous Markov Chains model to simulate random EV driving pattern and charging behavior. Then try to define the location of charging station where can maximize the service coverage rate to all the charging demands by applying a genetic algorithm. After the suitable locations are decided, the next step is to find an optimal number of charging poles at each charging station to provide adequate service level by a nonstationary Poisson process model based on M/M/c queueing theory. Study results show that with proper planning of the charging station, the EV charging impacts can be mitigated without sacrificing satisfaction of charging demands under different charging station layout
    Advisory Committee
  • Ching-Tsai Pan - chair
  • Chang-Huan Liu - co-chair
  • Sheng-Nian Yeh - co-chair
  • Chan-Nan Lu - advisor
  • Files
  • etd-1001113-154640.pdf
  • Indicate in-campus at 1 year and off-campus access at 1 year.
    Date of Submission 2013-11-01

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