Global warming and associated role of energy consumption across various sectors is a well-researched topic in recent years. Understanding current urban energy consumption patterns will allow us to understand how future energy consumption patterns will evolve. With electrification of vehicles and potentially altering culture of work from home, the energy usage at regional level would see a significant change in the future. The current PhD dissertation contributes to energy consumption analysis of a region by analyzing residential energy consumption, commercial energy consumption and transportation energy use by households. The aggregation of these energy consumption within a region contributes to the total energy consumption of a region. As the share of electric vehicles increases, the proposed modeling frameworks provides the current consumption that serves as a baseline estimate. Specifically, for the energy consumption, we examine the choice of energy sources and the energy consumption by source. The share of electrical vehicles is currently increasing. As the share of electric vehicles increases within our transportation infrastructure, the spatio-temporal nature of current electricity demand is likely to alter with increased household electricity consumption for vehicle charging. To develop a future estimate of urban demand with electric vehicles, a model system of current consumption serves as a baseline estimate. The analysis of energy use in residential buildings and commercial buildings is conducted using Residential Energy Consumption Survey (RECS) and Commercial Building Energy Consumption (CBECS) datasets. The transportation energy use is analyzed using National Household Travel Survey (NHTS) and MPG of the vehicles taken from Vehicle Fuel Economy Estimates. Multiple Discrete Continuous Extreme Value (MDCEV) model and Joint Binary Logit - Fractional Split Model (Joint BLFSM) are used to analyze residential energy consumption. While Bi level MDCEV is used for commercial energy use and spatial weighted regression models are used to analyze transportation energy use.
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Doctor of Philosophy (Ph.D.)
College of Engineering and Computer Science
Civil, Environmental and Construction Engineering
Length of Campus-only Access
Doctoral Dissertation (Campus-only Access)
Iraganaboina, Naveen Chandra, "Econometric Frameworks for Energy Prediction" (2021). Electronic Theses and Dissertations, 2020-. 955.
Restricted to the UCF community until November 2022; it will then be open access.