Computational Frameworks for Integrated Design and Operation of Carbon Capture, Renewables and Energy Storage Systems

Abstract

As the demand for energy grows, there is a substantial push to adopt sustainable and inherently carbon-neutral renewable energy sources. However, the intermittency and non-dispatchability of renewables requires measures to improve grid flexibility. These measures include the frequent cycling of the conventional, fossil-based generating units and energy storage. While conventional plant cycling reduces its efficiency and plant lifetimes, grid-scale energy storage is capital-intensive with only a limited number of suitable candidate technologies. Due to these integration challenges associated with renewables, it is difficult to completely replace the dispatchable fossil generators. CO₂ capture, utilization and storage provides a means to reduce emissions from fossil power plants, but its large-scale deployment is currently limited by high cost and high energy requirement.

In this Ph.D. work, the limitations of these decarbonization technologies are addressed through the development of computational frameworks and methodologies. To begin with, a flexible operation strategy is proposed for CO₂ capture in dynamic, uncertain pricing-driven electricity markets to reduce its high energy consumption. This framework is then extended to leverage the operational synergies between renewables and CO₂ capture to address their individual challenges together. A decentralized scheme is further proposed for the integration of energy storage with individual fossil power plants to reduce the costs associated with power plant cycling as well as grid-scale energy storage while accommodating renewable energy. A comprehensive software prototype, THESEUS, is presented to enable the optimal design and operation of the decentralized system, as well as the systematic downselection and comparison of energy storage technologies for different clean energy applications. Using THESEUS, one can determine the best-suited storage technology from a suite of nine technologies at different technology maturity levels, perform detailed techno-economic analysis and determine the optimal integration configuration with both renewable and fossil power plants. The utility of the developed computational frameworks is demonstrated through extensive nationwide and statewide case studies across the US.