Date of Award

1-1-2012

Document Type

Masters Thesis

Degree Name

M.S.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science

First Advisor

Wenzhong Gao, Ph.D.

Second Advisor

Yun-Bo Yi

Third Advisor

Mohammad Matin

Fourth Advisor

Jun Zhang

Keywords

Demand side response, Plug-in hybrid electric vehicle, Renewable energy, Stochastic model

Abstract

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.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Yin Yao

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

109 p.

Discipline

Electrical engineering

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