Hybrid sCO2 and ORC Integration for Enhanced Waste Heat Recovery and Power Generation Efficiency

Abstract The integration of hybrid supercritical carbon dioxide and Organic Rankine Cycle systems offers a novel approach to enhance waste heat recovery and power generation efficiency. This study evaluates the thermodynamic performance of a hybrid sCO2 and ORC system, focusing on heat recovery across a wide temperature range. The high-temperature recuperator achieved an effectiveness of 98.35%, preheating the sCO2 stream to 491.97°C, while the low-temperature recuperator maintained an effectiveness of 91.92%. The ORC subsystem further captured low-grade waste heat, generating an additional 11.85 MW at an efficiency of 17.66%. Machine learning models were employed to optimize key parameters, including pressure ratios and temperature differences, achieving a cycle efficiency of 60%. The results underline the synergistic operation of the hybrid system, ensuring cascade utilization of heat and minimizing exergy losses. The study demonstrates the system potential to significantly improve the efficiency and sustainability of waste heat recovery processes, making it a promising solution for advanced energy systems. This approach provides critical insights into optimizing thermodynamic cycles for diverse industrial and power generation applications, promoting the adoption of sustainable energy technologies.

Authors

Institutions

Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1115/gt2025-151616
Citations
1
Primary Topic
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hybrid sCO2 and ORC Integration for Enhanced Waste Heat Recovery and Power Generation Efficiency

Babras Khan, Jan Štěpánek, Václav Dostál
1 citations
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
0.71
article

Hybrid sCO2 and ORC Integration for Enhanced Waste Heat Recovery and Power Generation Efficiency

Babras Khan, Jan Štěpánek, Václav Dostál
article en
1 citations

Abstract

Abstract The integration of hybrid supercritical carbon dioxide and Organic Rankine Cycle systems offers a novel approach to enhance waste heat recovery and power generation efficiency. This study evaluates the thermodynamic performance of a hybrid sCO2 and ORC system, focusing on heat recovery across a wide temperature range. The high-temperature recuperator achieved an effectiveness of 98.35%, preheating the sCO2 stream to 491.97°C, while the low-temperature recuperator maintained an effectiveness of 91.92%. The ORC subsystem further captured low-grade waste heat, generating an additional 11.85 MW at an efficiency of 17.66%. Machine learning models were employed to optimize key parameters, including pressure ratios and temperature differences, achieving a cycle efficiency of 60%. The results underline the synergistic operation of the hybrid system, ensuring cascade utilization of heat and minimizing exergy losses. The study demonstrates the system potential to significantly improve the efficiency and sustainability of waste heat recovery processes, making it a promising solution for advanced energy systems. This approach provides critical insights into optimizing thermodynamic cycles for diverse industrial and power generation applications, promoting the adoption of sustainable energy technologies.

University of Business in Prague (CZ), Czech Technical University in Prague (CZ)
Openalex Percentile: Top 29%
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
0.71
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.