The renewable energy systems for residential, commercial, and transportation sectors need to be designed to minimize cost and environmental impacts. Key considerations in energy systems' design are energy demand estimation and inclusion of location-specific electricity pricing structures. Due to different energy demand patterns, electricity pricing, and location, designing renewable systems for each sector is complex. In the residential sector, microgrid systems capacity design is based on deterministic loads assuming that all individual houses have an identical appliance usage throughout the year. Also, residential photovoltaic (PV) systems with second-life batteries are designed based on the in-vehicle degradation behavior of the second-life batteries. Therefore, an alternate stochastic load modeling strategy and optimization algorithm to design PV and battery systems with reduced cost and carbon footprint for the residential sector is proposed in this work. In commercial and utility sectors, renewable energy systems need to provide energy, cost, and environmental benefits considering different constraints. For commercial buildings, producing electricity and reducing peak demand are key objectives of renewable energy systems without compromising the aesthetics. The agricultural sector is another commercial sector where land use of energy systems needs to be minimized to avoid food security issues. In utility-level applications, large battery capacities can be required to improve grid stability by minimizing the impact of PV variability. Depending on the specific energy challenge, the PV and battery-based renewable energy solutions will differ in terms of materials and systems design. In this work, we analyze thecost and energy benefits of novel PV and battery-based solutions such as transparent organic photovoltaics and second-life batteries for commercial and utility sectors. In the transportation sector, using battery electric vehicles and generating conventional hydrocarbon fuels from atmosphere-captured carbon dioxide (e-fuels) are two ways to reduce vehicle carbon emissions. However, both these technologies have high electricity demand that should be supplied from renewable energy resources like solar PV and wind turbines. No study has yet analyzed the feasibility of solar PV and wind energy in terms of land and material requirements to support battery electric vehicles and refueling infrastructure for e-fuel. Therefore in this work, the land use and material requirements for solar PV and wind turbines required to decarbonize the light-duty vehicle fleet are analyzed. Overall, the results of this dissertation highlight the importance of energy demand estimation for designing renewable energy systems at both micro and macro levels. At the micro or individual level, the systems' design can target specific characteristics of the hourly demand, like peak intensity and duration, for reduced cost and environmental impacts. At the macro or national level, forecasting the energy demand can lead to selecting renewable energy solutions which avoid material and supply chain constraints.
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