Computational modeling of dynamic phase change materials in thermal energy storage for concentrated solar power

Energy demand is rapidly growing on a global scale. Population growth, electrification, and the advent of artificial intelligence and other high-power computing functions are among the biggest drivers of this increasing demand. The design and implementation of reliable, modernized power systems such as modular, networked microgrids is essential to meet this growing demand. Thermal energy resources such as parabolic trough concentrated solar power (CSP) are commonly used in microgrids to support thermal power demands, but CSP power production is intermittent. Implementing thermal energy storage to modulate the power output of thermal energy systems can manage intermittence. Power system planning, however, involves uncertainty around the quantitative impact that power resource investments such as concentrated solar power (CSP) and thermal energy storage will have on the reliability and resilience of a microgrid. Conventional latent thermal energy storage technologies have shortcomings, such as migration of the melting front over time. This introduces additional conductive resistance during the charge cycle that negatively impacts heat flux into the energy storage phase change material (PCM). A new conceptual technology called dynamic phase change materials (dynPCMs) have been developed to address this shortcoming by applying mass or piston-based pressure to the solid state of the energy storage PCM to keep close contact between the heated boundary and the solid portion of the PCM as it melts. This technology theoretically improves the performance of thermal energy storage. This study introduces a computational model that calculates metrics for the expected performance of parabolic trough Concentrated Solar Power (CSP) systems with conventional latent thermal energy storage versus dynPCM thermal energy storage. The model includes a control system to modulate the CSP system’s power output and match a power demand profile as closely as possible. This study shows that, while latent thermal energy storage enables the example CSP system to achieve a power availability of 68.6%, dynPCM thermal energy storage enables the CSP system to achieve a higher power availability than latent thermal energy storage—as high as 79.5%. The study also involves a parametric analysis of the factors which influence the power availability of the system. This model is built for incorporation into a larger computational model which we term Analysis of Microgrid Performance, Reliability, and Resilience (AMPeRRe) to evaluate the performance impacts of incorporating CSP systems and thermal energy storage in larger microgrids. The stand-alone model and AMPeRRe will produce actionable analytics for decision-makers to inform their investment decisions around implementing CSP and thermal energy storage in varied applications. The results shown here can enable a better understanding of thermal energy storage-coupled intermittent energy resources that can meet the energy security needs of a growing world.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Nicholson, Jessica

Contributors dc:contributor

• Miljkovic, Nenad

• Thermal energy
• energy storage
• concentrated solar power
• phase change materials
• digital modeling
• computation
• analysis
• reliability
• resilience
• microgrids
• sustainability

Statement dc:rights

• Copyright 2025 Jessica Nicholson

Language dc:language

en

Handle dc:identifier

https://hdl.handle.net/2142/132640

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/132640