Date of Award
Daniel Felix Ritchie School of Engineering and Computer Science
Wenzhong Gao, Ph.D.
Demand side response, Plug-in hybrid electric vehicle, Renewable energy, Stochastic model
In this thesis, in order to investigate the impact of charging load from plug-in hybrid electric vehicles (PHEVs), a stochastic model is developed in Matlab. In this model, two main types of PHEVs are defined: public transportation vehicles and private vehicles. Different charging time schedule, charging speed and battery capacity are considered for each type of vehicles. The simulation results reveal that there will be two load peaks (at noon and in evening) when the penetration level of PHEVs increases continuously to 30% in 2030. Therefore, optimization tool is utilized to shift load peaks. This optimization process is based on real time pricing and wind power output data. With the help of smart grid, power allocated to each vehicle could be controlled. As a result, this optimization could fulfill the goal of shifting load peaks to valley areas where real time price is low or wind output is high.
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Received from ProQuest
Yao, Yin, "Plug-in Hybrid Electric Vehicle in Smart Grid" (2012). Electronic Theses and Dissertations. 723.