Date of Award

1-1-2016

Document Type

Dissertation

Degree Name

Ph.D.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science

First Advisor

David Wenzhong Gao, Ph.D.

Second Advisor

Andrew Linshaw

Third Advisor

Jun Zhang

Fourth Advisor

Amin Khodaei

Keywords

Economic dispatch, Microgrid, Plug-in hybrid electric vehicle, Stochastic model, Transportation electrification, Vehicle to grid

Abstract

In this dissertation, an integrated Plug-in Electric Vehicle (PHEV) charging loads forecasting model is developed for regular distribution level system and microgrid system. For regular distribution system, charging schedule optimization is followed up. The objectives are 1. Better cooperation with renewable energy sources (especially wind). 2. Relieving the pressure of current distribution transformers in condition of high penetration level PHEVs. As for microgrid, renewable energy power plants (wind, solar) plays a more important role than regular system. Due to the fluctuation of solar and wind plants' output, an empirical probabilistic model is developed to predict their hourly output. On the other hand, PHEVs are not only considered at the charging loads, but also the discharging output via Vehicle to Grid (V2G) method which can greatly affect the economic dispatch for all the micro energy sources in microgrid. Optimization is performed for economic dispatch considering conventional, renewable power plants, and PHEVs. The simulation in both cases results reveal that there is a great potential for optimization of PHEVs' charging schedule. Furthermore, PHEVs with V2G capability can be an indispensable supplement in modern microgrid.

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

131 p.

Discipline

Electrical Engineering

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