Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniques
Green hydrogen (H₂) is a leading enabler for the decarbonization of hard-to-abate industries where electrification is either uneconomical or infeasible. Establishing an adequate and cost-effective infrastructure for hydrogen distribution remains one of the primary barriers to its widespread adoption...
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Elsevier
2025-06-01
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| Series: | Digital Chemical Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772508125000183 |
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| author | Homa Hamedi Torsten Brinkmann |
| author_facet | Homa Hamedi Torsten Brinkmann |
| author_sort | Homa Hamedi |
| collection | DOAJ |
| description | Green hydrogen (H₂) is a leading enabler for the decarbonization of hard-to-abate industries where electrification is either uneconomical or infeasible. Establishing an adequate and cost-effective infrastructure for hydrogen distribution remains one of the primary barriers to its widespread adoption. A promising short-term solution to this challenge involves H₂ storage and co-transportation via existing gas grids. For H₂ extraction from distribution gas grids, standalone pressure swing adsorption systems are considered the most viable option, whereas a hybrid process is suggested in the literature for transmission gas networks. This article presents a comprehensive techno-economic model for the proposed hybrid process, developed using an integrated platform based on Aspen Adsorption and Aspen Custom Modeler. The system consists of a single-stage hollow fiber Matrimid membrane module, followed by a 4-bed adsorption process operating in 8 sequential steps to meet H₂ market purity requirements with an acceptable recovery rate. Since the performances of these two separation modules, as an integrated system, significantly influence each other, the study identifies a unique opportunity to minimize separation costs through process optimization. To reduce computational time, a cyclic steady-state approach was employed to simulate the PSA process. Bayesian optimization, facilitated by the integration of Python with Aspen Adsorption, was used to efficiently identify the optimal solution with a minimal number of objective function evaluations. The levelized cost of H₂ separation (99.0 % purity at 10 bar) from natural gas containing 10 % H2 at pressures of 35 bar and 60 bar is estimated to be 2.7310 and, $2.5116/kg-H2, respectively. These estimates correspond to a scenario with 10 identical trains, each handling a feed flowrate of 200 kmol/hr. Increasing the number of trains keeps the cost contribution of PSA constant; however, the total cost decreases as the compression fixed cost is distributed across more trains. |
| format | Article |
| id | doaj-art-ee4b83d979f24a6b81ed24e190bda3ea |
| institution | DOAJ |
| issn | 2772-5081 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Digital Chemical Engineering |
| spelling | doaj-art-ee4b83d979f24a6b81ed24e190bda3ea2025-08-20T03:07:58ZengElsevierDigital Chemical Engineering2772-50812025-06-011510023410.1016/j.dche.2025.100234Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniquesHoma Hamedi0Torsten Brinkmann1Helmholtz-Zentrum Hereon, Institute of Membrane Research, Max-Planck-Straße 1, 21502 Geesthacht, GermanyCorresponding author.; Helmholtz-Zentrum Hereon, Institute of Membrane Research, Max-Planck-Straße 1, 21502 Geesthacht, GermanyGreen hydrogen (H₂) is a leading enabler for the decarbonization of hard-to-abate industries where electrification is either uneconomical or infeasible. Establishing an adequate and cost-effective infrastructure for hydrogen distribution remains one of the primary barriers to its widespread adoption. A promising short-term solution to this challenge involves H₂ storage and co-transportation via existing gas grids. For H₂ extraction from distribution gas grids, standalone pressure swing adsorption systems are considered the most viable option, whereas a hybrid process is suggested in the literature for transmission gas networks. This article presents a comprehensive techno-economic model for the proposed hybrid process, developed using an integrated platform based on Aspen Adsorption and Aspen Custom Modeler. The system consists of a single-stage hollow fiber Matrimid membrane module, followed by a 4-bed adsorption process operating in 8 sequential steps to meet H₂ market purity requirements with an acceptable recovery rate. Since the performances of these two separation modules, as an integrated system, significantly influence each other, the study identifies a unique opportunity to minimize separation costs through process optimization. To reduce computational time, a cyclic steady-state approach was employed to simulate the PSA process. Bayesian optimization, facilitated by the integration of Python with Aspen Adsorption, was used to efficiently identify the optimal solution with a minimal number of objective function evaluations. The levelized cost of H₂ separation (99.0 % purity at 10 bar) from natural gas containing 10 % H2 at pressures of 35 bar and 60 bar is estimated to be 2.7310 and, $2.5116/kg-H2, respectively. These estimates correspond to a scenario with 10 identical trains, each handling a feed flowrate of 200 kmol/hr. Increasing the number of trains keeps the cost contribution of PSA constant; however, the total cost decreases as the compression fixed cost is distributed across more trains.http://www.sciencedirect.com/science/article/pii/S2772508125000183Pressure swing adsorptionMatrimid membrane separationHybrid processH2 purificationBayesian optimizationSector coupling |
| spellingShingle | Homa Hamedi Torsten Brinkmann Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniques Digital Chemical Engineering Pressure swing adsorption Matrimid membrane separation Hybrid process H2 purification Bayesian optimization Sector coupling |
| title | Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniques |
| title_full | Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniques |
| title_fullStr | Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniques |
| title_full_unstemmed | Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniques |
| title_short | Green hydrogen extraction from natural gas transmission grids using hybrid membrane and PSA processes optimized via bayesian techniques |
| title_sort | green hydrogen extraction from natural gas transmission grids using hybrid membrane and psa processes optimized via bayesian techniques |
| topic | Pressure swing adsorption Matrimid membrane separation Hybrid process H2 purification Bayesian optimization Sector coupling |
| url | http://www.sciencedirect.com/science/article/pii/S2772508125000183 |
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