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Dynamic liquefied natural gas (LNG) processing with energy storage applications.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Dynamic liquefied natural gas (LNG) processing with energy storage applications./
作者:	Fazlollahi, Farhad.
面頁冊數:	1 online resource (159 pages)
附註:	Source: Dissertation Abstracts International, Volume: 77-12(E), Section: B.
標題:	Chemical oceanography. -
電子資源:	click for full text (PQDT)
ISBN:	9781339927411

Dynamic liquefied natural gas (LNG) processing with energy storage applications.
Fazlollahi, Farhad.

Dynamic liquefied natural gas (LNG) processing with energy storage applications. - 1 online resource (159 pages)

Source: Dissertation Abstracts International, Volume: 77-12(E), Section: B.

Thesis (Ph.D.)--Brigham Young University, 2016.

Includes bibliographical references

The cryogenic carbon capture(TM) (CCC) process provides energy- and cost-efficient carbon capture and can be configured to provide an energy storage system using an open-loop natural gas (NG) refrigeration system, which is called energy storing cryogenic carbon capture (CCC-ES(TM)). This investigation focuses on the transient operation and especially on the dynamic response of this energy storage system and explores its efficiency, effectiveness, design, and operation. This investigation included four tasks. The first task explores the steady-state design of four different natural gas liquefaction processes simulated by Aspen HYSYS. These processes differ from traditional LNG process in that the CCC process vaporizes the LNG and the cold vapors return through the LNG heat exchangers, exchanging sensible heat with the incoming flows. The comparisons include costs and energy performance with individually optimized processes, each operating at three operating conditions: energy storage, energy recovery, and balanced operation. The second task examines steady-state and transient models and optimization of natural gas liquefaction using Aspen HYSYS. Steady-state exergy and heat exchanger efficiency analyses characterize the performance of several potential systems. Transient analyses of the optimal steady-state model produced most of the results discussed here. The third task explores transient Aspen HYSYS modeling and optimization of two natural gas liquefaction processes and identifies the rate-limiting process components during load variations. Novel flowrate variations included in this investigation drive transient responses of all units, especially compressors and heat exchangers. Model-predictive controls (MPC) effectively manages such heat exchangers and compares favorably with results using traditional controls. The last task shows how an unprocessed natural gas (NG) pretreatment system can remove more than 90% of the CO2 from NG with CCC technology using Aspen Plus simulations and experimental data. This task shows how CCC-based technology can treat NG streams to prepare them for LNG use. Data from an experimental bench-scale apparatus verify simulation results. Simulated results on carbon (CO2) capture qualitatively and quantitatively agree with experimental results as a function of feedstock properties.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781339927411Subjects--Topical Terms:

642003
Chemical oceanography.
Index Terms--Genre/Form:

554714
Electronic books.

Dynamic liquefied natural gas (LNG) processing with energy storage applications.
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520 $a The cryogenic carbon capture(TM) (CCC) process provides energy- and cost-efficient carbon capture and can be configured to provide an energy storage system using an open-loop natural gas (NG) refrigeration system, which is called energy storing cryogenic carbon capture (CCC-ES(TM)). This investigation focuses on the transient operation and especially on the dynamic response of this energy storage system and explores its efficiency, effectiveness, design, and operation. This investigation included four tasks. The first task explores the steady-state design of four different natural gas liquefaction processes simulated by Aspen HYSYS. These processes differ from traditional LNG process in that the CCC process vaporizes the LNG and the cold vapors return through the LNG heat exchangers, exchanging sensible heat with the incoming flows. The comparisons include costs and energy performance with individually optimized processes, each operating at three operating conditions: energy storage, energy recovery, and balanced operation. The second task examines steady-state and transient models and optimization of natural gas liquefaction using Aspen HYSYS. Steady-state exergy and heat exchanger efficiency analyses characterize the performance of several potential systems. Transient analyses of the optimal steady-state model produced most of the results discussed here. The third task explores transient Aspen HYSYS modeling and optimization of two natural gas liquefaction processes and identifies the rate-limiting process components during load variations. Novel flowrate variations included in this investigation drive transient responses of all units, especially compressors and heat exchangers. Model-predictive controls (MPC) effectively manages such heat exchangers and compares favorably with results using traditional controls. The last task shows how an unprocessed natural gas (NG) pretreatment system can remove more than 90% of the CO2 from NG with CCC technology using Aspen Plus simulations and experimental data. This task shows how CCC-based technology can treat NG streams to prepare them for LNG use. Data from an experimental bench-scale apparatus verify simulation results. Simulated results on carbon (CO2) capture qualitatively and quantitatively agree with experimental results as a function of feedstock properties.
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