Techno-economic optimization and environmental life cycle assessment of microgrids using genetic algorithm and artificial neural networks

"This dissertation focuses primarily on techno-economic optimization and environmental life cycle assessment (LCA) of sustainable energy generation technologies. This work is divided into five papers. The first paper discusses the techno-economic optimization and environmental life cycle assessment of microgrids located in the USA using genetic algorithm. In this paper, a methodology was developed that assessed the techno-economic and environmental performance of a small scale microgrid located in US cities of Tucson, Lubbock and Dickinson. Providing uninterrupted power the microgrid was composed of seven components -- solar photovoltaics, wind-turbines, lead acid batteries, biodiesel generators, fuel cells, electrolyzers and H₂ tanks. The second paper is an extension of first paper and utilizes Artificial Neural Networks to predict energy demand while also incorporating social costs. With an aim to incorporate LCA methodology, the third paper discusses the upstream biodiesel production process which is a vital fuel source for the microgrid. In this paper, a supercritical biodiesel production process from waste cooking oil (WCO) using methanol in the presence of propane as a co-solvent was technically analyzed using Aspen Plus software. In the fourth paper, a system dynamics model of the cast iron foundry process was developed and validated with the actual energy consumption data based on which recommendations were made to reduce energy consumption by 26% or $2.6 million. In the fifth paper, an assessment of the threats to the aquatic resources due to rapid growth in the extraction of Shale gas in the US was performed with an application to the Kurdistan region of Iraq"--Abstract, page iv.

Name thesis:degree_name

Ph. D. in Chemical Engineering

Grantor

Missouri University of Science and Technology

Author dc:creator

• Nagapurkar, Prashant

• Artificial neural networks
• Genetic algorithm
• Life cycle assessment
• Microgrids
• Optimization
• Techno-economic
• Chemical Engineering

Repository record dc:identifier

https://scholarsmine.mst.edu/doctoral_dissertations/2787

OAI identifier oai:identifier

oai:scholarsmine.mst.edu:doctoral_dissertations-3792