Session: 09-01 Compressed / Liquid Air Energy Storage

Submission Number: 179133

Comparative Performance and Operating Strategies of Electric-Heating-Assisted Compressed Air Energy Storage 

Conventional diabatic compressed air energy storage (CAES) systems rely on fuel combustion to heat discharged air, leading to carbon emissions, while adiabatic CAES systems suffer from limited discharge temperature when only compression heat is recovered through intercooling. By recovering intercooling heat and supplementing it with electric heating, a CAES system can achieve higher discharge temperatures and reduce fuel consumption, enabling excess renewable electricity to be stored as high-quality thermal energy within a thermal energy storage (TES). Therefore, integrating electric heating offers a low-carbon means to boost stored thermal energy and turbine inlet temperature, especially when powered by surplus renewable energy. 
This study investigates the impact of electric heating on the overall performance and operation of CAES systems. In particular, we analyze the off-design performance with respect to local control parameters such as the electric heater set-point temperature and charging/discharging schedules. Building on this evaluation, the analysis extends from local control behavior to system-level energy management. Building on this evaluation, the analysis extends from local control behavior to system-level energy management. At the system level, we examine how variations in these parameters affect the power split between air compression and electric heating. This analysis allows us to identify suitable configurations and optimal capacities of the CAES, TES, and electric heating subsystems, providing a comprehensive framework for managing surplus renewable electricity across the power-to-heat-to-power pathway.

Presenting Author: Hyerim Kim University of Genova

Presenting Author Biography: Hyerim Kim received a Ph.D. in Mechanical Engineering from Inha University, Republic of Korea. Her research focuses on the design, modeling, and optimization of advanced energy systems, including gas turbines, fuel cells, and energy storages. She has extensive experience in thermodynamic and AI-based optimization for integrated energy systems. Her recent work explores low-carbon hybrid cycles and renewable-driven power-to-X pathways to enhance efficiency and sustainability in future energy conversion technologies.

Authors:

Hyerim Kim Korea Institute of Machinery & Materials
Andriy Vasylyev University of Genova
Alessandro Sorce University of Genova