Design and optimization of integrated water, energy, and transportation infrastructure for urban sustainability

Urban areas cover a small portion of the earth, yet they accommodate a majority of the world population and are associated with a majority of the global energy use and greenhouse gas emissions. These facts make cities the forefront of combating climate change, with transportation, buildings (residential and commercial), and electricity generation sectors being the foci of this effort due to their significant environmental footprints. Thus, improving the efficiency of these sectors can play an essential role in reducing the environmental footprint of urban districts. Coordinated design of infrastructure has shown to be an effective approach to create more sustainable urban systems. Such coordination leads to integrated municipal supply systems (e.g., water and energy supply, and EV charging infrastructure) with improved overall performance when compared to the simple superposition of individual supply systems. This coordination can be most feasibly achieved at a neighborhood scale, i.e., 100-1000 adjacent buildings, where the supply and demand of the integrated infrastructure can be designed and optimized simultaneously. Since building mix largely determines the demand profile of urban neighborhoods, simultaneously optimizing the building mix and integrating infrastructure represents a potential opportunity for designing more sustainable urban districts. To investigate and understand this opportunity, this dissertation focuses on the design and optimization of the energy system (including EV charging infrastructure), wastewater treatment system, and building mix of urban neighborhoods. Typically, urban energy and water infrastructure systems are designed after the demands of the community are determined. At that late stage, improving the environmental and economic performance of the system is difficult. However, if the supply and demand of municipal services are optimized simultaneously, especially at the early stages of the design when such coordination is more feasible, the resulting urban system has proven to outperform the isolated design using several sustainability metrics. This dissertation proposes a novel method to design and optimize the hourly demand and supply of integrated energy and water system in an urban district for environmental and economic sustainability. The increasing electricity demand from the growing number of EVs on the road will impose pressure on local and regional electricity grids. Hence, considering the influence of EVs will be essential for designing future urban energy systems. This dissertation proposes a new method for integrating the design of energy system and building mix with the EV charging infrastructure in urban neighborhoods, and for optimizing these infrastructure systems for economic and environmental targets. The spatial configuration of urban infrastructure systems is essential in modeling the performance and minimizing the impacts of these systems, especially for the urban water and energy systems. However, integrating the design and optimization of the supply, demand, and network layout across multiple infrastructure systems at the neighborhood scale gives rise to highly complex optimization problems. Traditional optimization algorithms cannot properly explore the optimal solutions in the vast solution space of these problems in a reasonable amount of time. This dissertation develops a new method that facilitates concurrent optimization of the supply, demand, and spatial configuration of integrated infrastructure at a neighborhood scale for multiple objective functions. Keywords: Sustainable Urban Systems, Integrated Infrastructure, Water-Energy Nexus, EV Charging Infrastructure, Multiobjective Optimization, Mixed Integer Nonlinear Programming, Conditional Generative Adversarial Networks

Advisor: Lepech Michael
Brandt Adam (Adam R.)
Criddle Craig