Date of Award

December 2012

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Engineering

First Advisor

Chris Y. Yuan

Committee Members

Junhong Chen, Ying Li, Zhen He, Vishnuteja Nanduri

Abstract

This dissertation develops a systematic approach to comprehensively investigate the application potential of Solar PV, wind and fuel cells in reducing GHGs emissions for energy intensive global manufacturing industry. This systematic approach is developed by integrating the technological and economic characteristics of the clean energy technologies, as well as the local geographic conditions where the clean energy technologies may be deployed. This approach consists of the investigation on such aspects as: technological feasibility, capacity factor, FIT strength, Levelized energy cost, cost benefit and sensitivity.

In this dissertation, the systematic approach developed is applied on the application potential analyses of solar PV, wind and fuel cells technologies in reducing GHGs for the global automotive manufacturers, at six global locations including Detroit, Mexico City, Sao Paulo, Shanghai, Cairo and Bochum. For the application potential of these three clean energy technologies in reducing GHGs emissions, the technological feasibility, capacity factor, Levelized energy cost, cost benefit and sensitivity analysis are conducted with different geographic and economic parameters. The cost benefit trends of solar PV, wind and fuel cells in reducing GHGs emissions from 2010-2035 are projected by using this developed approach, with the assumptions of two virtual cost cases. This approach is applied on the cost benefit range analysis in six selected countries to investigate the uncertainty of the GHGs reduction cost benefit due to the geographic difference. Potential cost benefit maps on GHGs emission reduction in the nationwide of the US lower 48 states are generated by using this systematic approach. The sensitivity analysis is applied for the solar PV and wind energies to investigate the linear relevance of different geographic and economic parameters with the cost benefit performance. In the FIT strength analysis of the case study, different geographic locations are selected due to the lack of data.

This dissertation concludes with discussions on the application potential of three clean energy technologies at different global locations in reducing GHGs emission for global manufacturing industry. As there is lack of information support on the selection of appropriate clean energy technologies at specific locations to achieve GHGs emission reduction, this approach developed provides a comprehensive support for decision making.

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