Computational Optimization of Solar Thermal and Natural Gas Power Systems

In order to facilitate the rapid adoption of renewable energy, it is necessary to identify low cost renewable-based systems to compete with fossil-based electricity generation. In this dissertation, computational optimization is used to explore the integration of solar thermal energy into new or existing fossil energy systems through combined optimization of system design and operations. Two distinct systems are explored with the Hybrid Power Plant Optimization (HyPPO) model: a solar thermal/natural gas supported carbon capture retrofit to a coal-fired power plant, and an integrated solar combined cycle (ISCC).

Speaker: Phil Broderick (Thesis defense)