Thermodynamic modeling and techno-economic assessment of hydrogen fuelled diabatic compressed air energy storage configurations

• Systematic thermodynamic and techno-economic assessment of diabatic CAES. • Maximum roundtrip efficiencies: 47.4 % (non-recuperative) and 60% (recuperative). • Thermodynamic optimization yields best economic performance. • For hydrogen price of 1.23 €/kg: payback at 16.7 years. • Base case scenario: levelized cost of storage equal to 66.9 to 90.7 €/kWh e.. This work provides a combined thermodynamic and techno-economic assessment framework of hydrogen-fuelled diabatic CAES (D-CAES) systems as a solution to enhance performance and enable decarbonized energy storage. The central hypothesis is that optimizing compression and expansion subsystem designs-particularly through the use of recuperation and high-temperature hydrogen combustion-can significantly improve both thermodynamic and techno-economic outcomes. Steady-state modelling is performed in AspenPlus for various D-CAES configurations featuring two to four compressors and either non-recuperative or recuperative expansion. A parametric analysis explores the effects of intermediate discharge/expansion pressures and combustion temperatures on system performance. Results show that expansion design strongly influences roundtrip efficiency, with values reaching 47.4% for non-recuperative and 60.0% for recuperative systems. In contrast, the number of compressors and intermediate pressures has a negligible impact on efficiency. A techno-economic assessment is conducted assuming energy arbitrage under European market conditions, using a bottom-up approach to estimate capital investment and storage cavern costs. Despite higher capital expenditure, the configuration with four compressors, high combustion/turbine inlet temperatures, and recuperative expansion delivers the best economic performance. Under a base-case scenario with green hydrogen priced at 1.23 €/kg, the system achieves a 16.7-year payback period, a 9.4% internal rate of return, and a levelized cost of electricity ( LCOE ) between 66.9 and 90.7 €/MWh e . However, at current hydrogen prices, the investment does not achieve payback and the LCOE ranges from 190 to 325 €/MWh e , being significantly higher than the LCOE of pumped hydro storage and batteries.

Authors

Institutions

Publication Details

Journal
Applied Thermal Engineering
Published
2025-06-27
DOI
https://doi.org/10.1016/j.applthermaleng.2025.127325
Citations
3
Primary Topic
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Type
article
Field-Weighted Citation Impact
2.14
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Thermodynamic modeling and techno-economic assessment of hydrogen fuelled diabatic compressed air energy storage configurations

Konstantinos Braimakis, Sotiriοs Karellas, Tryfon C. Roumpedakis, Haris Avgerinou
3 citations
Applied Thermal Engineering
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
2.14
article

Thermodynamic modeling and techno-economic assessment of hydrogen fuelled diabatic compressed air energy storage configurations

Konstantinos Braimakis, Sotiriοs Karellas, Tryfon C. Roumpedakis, Haris Avgerinou
article en
3 citations

Abstract

• Systematic thermodynamic and techno-economic assessment of diabatic CAES. • Maximum roundtrip efficiencies: 47.4 % (non-recuperative) and 60% (recuperative). • Thermodynamic optimization yields best economic performance. • For hydrogen price of 1.23 €/kg: payback at 16.7 years. • Base case scenario: levelized cost of storage equal to 66.9 to 90.7 €/kWh e.. This work provides a combined thermodynamic and techno-economic assessment framework of hydrogen-fuelled diabatic CAES (D-CAES) systems as a solution to enhance performance and enable decarbonized energy storage. The central hypothesis is that optimizing compression and expansion subsystem designs-particularly through the use of recuperation and high-temperature hydrogen combustion-can significantly improve both thermodynamic and techno-economic outcomes. Steady-state modelling is performed in AspenPlus for various D-CAES configurations featuring two to four compressors and either non-recuperative or recuperative expansion. A parametric analysis explores the effects of intermediate discharge/expansion pressures and combustion temperatures on system performance. Results show that expansion design strongly influences roundtrip efficiency, with values reaching 47.4% for non-recuperative and 60.0% for recuperative systems. In contrast, the number of compressors and intermediate pressures has a negligible impact on efficiency. A techno-economic assessment is conducted assuming energy arbitrage under European market conditions, using a bottom-up approach to estimate capital investment and storage cavern costs. Despite higher capital expenditure, the configuration with four compressors, high combustion/turbine inlet temperatures, and recuperative expansion delivers the best economic performance. Under a base-case scenario with green hydrogen priced at 1.23 €/kg, the system achieves a 16.7-year payback period, a 9.4% internal rate of return, and a levelized cost of electricity ( LCOE ) between 66.9 and 90.7 €/MWh e . However, at current hydrogen prices, the investment does not achieve payback and the LCOE ranges from 190 to 325 €/MWh e , being significantly higher than the LCOE of pumped hydro storage and batteries.

Applied Thermal EngineeringVol. 278
National Technical University of Athens (GR)
Affordable and clean energy
Openalex Percentile: Top 13%
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
2.14
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.