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Design, Modeling and Optimization of Modified MEA Scrubbing Process for Post Combustion CO2 Capture : 모노에탄올아민을 이용한 연소 후 이산화탄소 포집 공정 개선안의 설계, 모델링 및 최적화

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dc.contributor.advisor한종훈-
dc.contributor.author정재흠-
dc.date.accessioned2017-07-13T08:43:45Z-
dc.date.available2017-07-13T08:43:45Z-
dc.date.issued2016-02-
dc.identifier.other000000132708-
dc.identifier.urihttps://hdl.handle.net/10371/119789-
dc.description학위논문 (박사)-- 서울대학교 대학원 : 화학생물공학부, 2016. 2. 한종훈.-
dc.description.abstractPost-combustion CO2 capture with aqueous monoethanolamine (MEA) scrubbing is a promising and well-proven technique for reducing atmospheric CO2 emissions. The MEA scrubbing process is suitable for treating flue gas from coal-fired power plants because of its high CO2 capture capacity and its ability to be retrofitted into existing power plant facilities. However, the MEA scrubbing process is not cost effective in terms of CO2 capture, in particular for the energy required for solvent regeneration. To overcome this issue, studies have been conducted to reduce the solvent regeneration energy through modifying the process configuration. However, the majority of these modified processes call for additional capital costs due to the requirement for additional equipment.
The objective of this study is therefore to determine the optimal configuration for reducing the cost of CO2 capture. The operating expenditure (OPEX) and capital expenditure (CAPEX) were considered together to reduce the total CO2 capture cost. Firstly, analysis of the conventional MEA scrubbing process energy system was carried out to determine the key variables for reducing the solvent regeneration energy. These key variables were the temperature at the stripper top, and the temperature approach at the cross heat exchanger. Analysis of the existing modified MEA scrubbing process was then carried out. The modified MEA scrubbing processes can be classified into three groups based on their energy reduction mechanism. The energy reduction mechanism of group I involves an increasing in the lean loading at the stripper bottom, while that of group II involves decreasing the solvent inlet temperature at the stripper top, and that of group III involves increasing the heat recovery. Combination of the multiple modified MEA scrubbing processes exhibiting positive interactions was then investigated. Absorber intercooling, cold solvent split, and rich vapor compression were selected as the optimal combination based on quantitative studies. For the combined configuration, the equivalent energy decreased 5.7%, from 1.22 GJe/ton CO2 to 1.15 GJe/ton CO2. Following energy consumption minimization, the additional CAPEX was calculated as a penalty term. Subsequently, the superstructure model of the modified configurations was prepared, involving six different modified configurations and various split flow configurations. As the cost model was built into the superstructure, the superstructure model calculated the OPEX and CAPEX terms simultaneously. Finally, optimization of the superstructure model of the modified MEA scrubbing configurations was carried out, simultaneously solving the process variables for six different modified configurations. The objective of scenario I was to minimize the equivalent energy without considering the CAPEX term. As a result, the equivalent energy for CO2 capture and compression decreased 22.1%, from 1.30 GJe/ton CO2 to 1.02 GJe/ton CO2. The objective of scenario II was to minimize the total cost, i.e., the sum of the OPEX and CAPEX terms. As a result, the total cost of CO2 capture and compression decreased 10.2%, from €54.7/ton CO2 to €51.0/ton CO2. The annualized cost reduction was therefore €25.7 M/yr for a 630 MWe power plant.
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dc.description.tableofcontentsChapter 1: Introduction 1
1.1 Research motivation 1
1.2 Research objectives 2
1.3 Outline of the thesis 4

Chapter 2: Conventional MEA Scrubbing Process 5
2.1 Overview 5
2.2 Process description 8
2.3 Energy system analysis 11
2.4 Parametric study 18

Chapter 3: Modified MEA Scrubbing Process 21
3.1 Overview 21
3.2 Modified configuration I: Increasing the CO2 lean loading 23
3.1.1 Absorber intercooling 23
3.1.2 Flue gas split 24
3.1.3 Flue gas precooling 25
3.1.4 Semi-lean/semi-rich loop 25
3.2 Modified configuration II: Decreasing the stripper top temperature 28
3.2.1 Stripper interheating 28
3.2.2 Staged feed of the stripper 29
3.2.3 Lean vapor compression 30
3.2.4 Rich vapor compression 31
3.3 Modified configuration III: Enhancing the waste heat recovery 37
3.3.1 Stripper overhead compression 37
3.3.2 Economizer 37
3.3.3 Heat integration 38
3.4 Parametric study 42

Chapter 4: Combination of the Modified MEA Scrubbing Process 46
4.1 Overview 46
4.2 Process description 49
4.3 Simulation specifications 52
4.4 Simulation results and discussions 57
4.4.1 Model validation 57
4.4.2 Effect of the cold solvent split 59
4.4.3 Effect of rich vapor recompression 63
4.4.4 Net equivalent energy reduction effect 66
4.4.5 Net annual cost saving effect 69

Chapter 5: Superstructure Modeling of the Modified MEA Scrubbing Process 71
5.1 Overview 71
5.2 Target process 72
5.3 Modeling procedure 74
5.3.1 Physical property model 74
5.3.2 Superstructure model 75
5.3.3 Cost model 79
5.4 Parametric study 83

Chapter 6: Superstructure Optimization of the Modified MEA Scrubbing Process 92
6.1 Overview 92
6.2 Optimization scenario I 95
6.2.1 Optimization procedure 95
6.2.2 Optimization results 96
6.3 Optimization scenario II 104
6.3.1 Optimization procedure 104
6.3.2 Optimization results 105

Chapter 7: Conclusions and Remark 114
7.1 Conclusions 114
7.2 Future work 115

Nomenclature 117

Literature cited 120

Abstract in Korean (요약) 126
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dc.formatapplication/pdf-
dc.format.extent4446508 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoko-
dc.publisher서울대학교 대학원-
dc.subjectPost-combustion CO2 Capture-
dc.subjectMEA Scrubbing-
dc.subjectSuperstructure Optimization-
dc.subject.ddc660-
dc.titleDesign, Modeling and Optimization of Modified MEA Scrubbing Process for Post Combustion CO2 Capture-
dc.title.alternative모노에탄올아민을 이용한 연소 후 이산화탄소 포집 공정 개선안의 설계, 모델링 및 최적화-
dc.typeThesis-
dc.description.degreeDoctor-
dc.citation.pages128-
dc.contributor.affiliation공과대학 화학생물공학부-
dc.date.awarded2016-02-
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