Screening and property targeting of thermochemical energy storage materials in concentrated solar power using thermodynamics-based insights and mathematical optimization

We propose a computational framework to systematically identify promising solid-gas reaction candidates for thermochemical energy storage (TCES) in concentrating solar power (CSP) plants. The framework is based on four steps that include the generation of reaction candidates, screening based on thermodynamic criteria, solving a process model to estimate the levelized cost of electricity (LCOE) and thermal energy storage (TES) costs, and selection of the promising reactions. Our approach identifies twelve reactions from a pool of three hundred and sixty-four possible reactions. Furthermore, we develop an optimization model to simultaneously optimize the material properties, design, and operating conditions while considering the limitations on thermodynamic properties and the correlation between different material properties. The solution of the model yields a target (best possible) LCOE for a range of material prices. By comparing the LCOE of the systems employing the top-performing materials with the target LCOE, we discover that the LCOE of the systems is 9.7% to 15.9% higher than the target LCOE. Finally, we provide insights into the desired material properties to attain the target LCOE. We propose a computational framework to systematically identify promising solid-gas reaction candidates for thermochemical energy storage (TCES) in concentrating solar power (CSP) plants.