Polygeneration process design to recover waste cold energy in LNG regasification terminals: simulation-based optimization approach

Abstract Liquefied Natural Gas (LNG) has emerged as a key energy vector owing to its lower carbon footprint. Calorific value specifications at regasification terminals necessitates pre-processing of LNG prior to regasification. Cryogenic distillation for heavy hydrocarbon removal (HHR) from LNG to lower the calorific value utilizes a portion of the available LNG cold energy. However, substantial amount of cold energy remains unutilized in HHR process. To reverse this wastage, a polygeneration process encompassing Organic Rankine Cycle (ORC) for power generation along with diverse refrigeration strategies is proposed following the HHR process. A simulation-based optimization framework is developed to maximize the net present value (NPV) of the proposed polygeneration process and investigate its performance across different LNG feed conditions. Irrespective of LNG feed conditions, the proposed process is found to be technoeconomically feasible resulting in a positive NPV. The optimal process not only generates electricity but also refrigeration sufficient to cool 1,200 data center racks at <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:mrow> <m:mo>−</m:mo> <m:mn>10</m:mn> </m:mrow> </m:math> ${-}10$ °C and a cryogenic warehouse of 2,000 m 3 at <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:mrow> <m:mo>−</m:mo> <m:mn>50</m:mn> </m:mrow> </m:math> ${-}50$ °C. The polygeneration process recovers substantial amount of the remaining cold energy after the HHR process resulting in a CO 2 avoidance of 12.8 kg-CO 2 /ton-LNG, thereby significantly augmenting the technoeconomics and sustainability of LNG value chain.

Institutions

Publication Details

Journal
Chemical Product and Process Modeling
Published
2025-10-24
DOI
https://doi.org/10.1515/cppm-2025-0138
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Polygeneration process design to recover waste cold energy in LNG regasification terminals: simulation-based optimization approach

Chemical Product and Process Modeling
Prenatal Screening and Diagnostics
article

Polygeneration process design to recover waste cold energy in LNG regasification terminals: simulation-based optimization approach

article en

Abstract

Abstract Liquefied Natural Gas (LNG) has emerged as a key energy vector owing to its lower carbon footprint. Calorific value specifications at regasification terminals necessitates pre-processing of LNG prior to regasification. Cryogenic distillation for heavy hydrocarbon removal (HHR) from LNG to lower the calorific value utilizes a portion of the available LNG cold energy. However, substantial amount of cold energy remains unutilized in HHR process. To reverse this wastage, a polygeneration process encompassing Organic Rankine Cycle (ORC) for power generation along with diverse refrigeration strategies is proposed following the HHR process. A simulation-based optimization framework is developed to maximize the net present value (NPV) of the proposed polygeneration process and investigate its performance across different LNG feed conditions. Irrespective of LNG feed conditions, the proposed process is found to be technoeconomically feasible resulting in a positive NPV. The optimal process not only generates electricity but also refrigeration sufficient to cool 1,200 data center racks at <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:mrow> <m:mo>−</m:mo> <m:mn>10</m:mn> </m:mrow> </m:math> ${-}10$ °C and a cryogenic warehouse of 2,000 m 3 at <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:mrow> <m:mo>−</m:mo> <m:mn>50</m:mn> </m:mrow> </m:math> ${-}50$ °C. The polygeneration process recovers substantial amount of the remaining cold energy after the HHR process resulting in a CO 2 avoidance of 12.8 kg-CO 2 /ton-LNG, thereby significantly augmenting the technoeconomics and sustainability of LNG value chain.

Chemical Product and Process Modeling
Birla Institute of Technology and Science - Hyderabad Campus (IN)
Openalex Percentile: Top 26%
Prenatal Screening and Diagnostics
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.