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    μ—°λ£Œμ „μ§€ μ‹œμŠ€ν…œμ— λŒ€ν•œ λͺ¨λΈλ§, κ²½μ œμ„± 뢄석 및 λͺ¨λ‹ˆν„°λ§μ— κ΄€ν•œ 연ꡬ

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    ν•™μœ„λ…Όλ¬Έ (박사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 화학생물곡학뢀, 2012. 8. ν•œμ’…ν›ˆ.μ„μœ  κ³ κ°ˆμ— λŒ€ν•œ μš°λ €μ™€ ν™˜κ²½ 문제의 증가에 따라 μ—°λ£Œ 전지 기술의 κ°€μΉ˜κ°€ λ†’κ²Œ 평가 λ°›κ³  μžˆλ‹€. ν™”ν•™ κ³΅λ‹¨μ—μ„œ μƒμ‚°λ˜λŠ” 뢀생 μˆ˜μ†ŒλŠ” λ‹€λ₯Έ ν™”ν•™ κ³΅μ •μ΄λ‚˜ μ •μœ  κ³΅μ •μ—μ„œ μ‚¬μš©λ˜κ±°λ‚˜ 보일러의 μ—°λ£Œλ‘œ 쓰이고 μžˆλ‹€. 뢀생 μˆ˜μ†Œλ₯Ό 쒀더 효율적으둜 μ‚¬μš©ν•˜λŠ” κΈ°μˆ μ— λŒ€ν•œ ν•„μš”μ„±μ΄ λŒ€λ‘λ˜κ³  μžˆλŠ” μƒν™©μ—μ„œ μˆ˜μ†Œλ₯Ό 고효율둜 μ‚¬μš©ν•  수 μžˆλŠ” μ—°λ£Œ 전지 기술이 μƒμš©ν™” μˆ˜μ€€μœΌλ‘œ λ°œμ „ν•˜κ³  μžˆλ‹€. λ³Έ λ…Όλ¬Έμ—μ„œλŠ” κ³ λΆ„μž μ „ν•΄μ§ˆ μ—°λ£Œ 전지 (Proton Exchange Membrane Fuel Cell: PEMFC) λ°œμ „μ†Œμ˜ κ²½μ œμ„± 뢄석, PEMFC의 이동 ν˜„μƒ 뢄석, 용육 탄산염 μ—°λ£Œ 전지 (Molten Carbonate Fuel Cell: MCFC) λ°œμ „μ†Œλ₯Ό μœ„ν•œ κ°μ‹œ μ‹œμŠ€ν…œμ˜ κ°œμ„ μ΄λΌλŠ” μ„Έ 가지 μ£Όμš” λͺ©ν‘œλ₯Ό λ‹΄κ³  μžˆλ‹€. 뢀생 μˆ˜μ†Œλ₯Ό μ‚¬μš©ν•˜λŠ” λ°©λ²•μ˜ ν•˜λ‚˜λ‘œ PEMFC λ°œμ „μ†Œμ˜ κ²½μ œμ„±μ„ λΆ„μ„ν•˜μ˜€λ‹€. 이λ₯Ό μœ„ν•΄ μ—°λ£Œ 전지 λ°œμ „μ†Œμ˜ 경제적 타당성을 κ²€μ¦ν•˜κΈ° μœ„ν•œ 곡정 λͺ¨λΈμ„ κ°œλ°œν•˜μ˜€λ‹€. λ˜ν•œ, 경제적 νƒ€λ‹Ήμ„±μ˜ κΈ°μ€€μœΌλ‘œ ν˜„μž¬μ˜ 상황에 λŒ€ν•œ κ²½μ œμ„± 뢄석과 μ€‘μš” λ³€μˆ˜μ— λŒ€ν•œ 민감도 뢄석을 μˆ˜ν–‰ν•˜μ˜€λ‹€. 미래의 상황을 κ°μ•ˆν•˜κΈ° μœ„ν•΄μ„œ μ •λΆ€ 지원 μ œλ„ 변화와 μˆ˜μ†Œ κ°€κ²©μ˜ λ³€ν™”λ₯Ό κ³ λ €ν•˜μ˜€λ‹€. λ‹€μ–‘ν•œ μˆ˜μ†Œ 생산 방식을 λΉ„κ΅ν•œ κ²°κ³Ό ν™”ν•™ κ³΅λ‹¨μ—μ„œ μƒμ‚°λ˜λŠ” 뢀생 μˆ˜μ†Œλ₯Ό μ‚¬μš©ν•œ κ²½μš°κ°€ 경제적 이점을 가지고 μžˆμŒμ„ ν™•μΈν•˜μ˜€λ‹€. λ³Έ λ…Όλ¬Έμ—μ„œλŠ” λ‹¨μœ„ 전지와 μŠ€νƒμ—μ„œ μΌμ–΄λ‚˜λŠ” 이동 ν˜„μƒμ„ λͺ¨μ‚¬ν•˜κΈ° μœ„ν•΄μ„œ 정적 λͺ¨λΈκ³Ό 동적 λͺ¨λΈμ„ μ‚¬μš©ν•˜μ˜€λ‹€. PEMFC λ‹¨μœ„ μ „μ§€μ˜ λͺ¨μ‚¬λ₯Ό μœ„ν•΄μ„œλŠ” 2μ°¨μ›μ˜ 정적 상세 λͺ¨λΈμ„ κ°œλ°œν•˜μ˜€λ‹€. λͺ¨λΈμ„ μ΄μš©ν•˜μ—¬ κ°€μŠ€μ˜ 이동, μ „κΈ°ν™”ν•™ λ°˜μ‘, μ „λ₯˜ 뢄포와 유체 역학에 λŒ€ν•œ 계산을 μˆ˜ν–‰ν•˜μ˜€λ‹€. 지배 방정식듀은 μœ ν•œ 체적법에 κΈ°μ΄ˆν•œ 유체 μ—­ν•™ 계산 μ•Œκ³ λ¦¬μ¦˜μ„ μ΄μš©ν•˜μ—¬ κ³„μ‚°ν•˜μ˜€λ‹€. μ œμ•ˆλœ 방법은 μ‹€ν—˜μ„ 톡해 얻은 λΆ„κ·Ή κ³‘μ„ κ³Όμ˜ 비ꡐλ₯Ό 톡해 κ²€μ¦ν•˜μ˜€λ‹€. PEMFC μŠ€νƒμ˜ λͺ¨μ‚¬λ₯Ό μœ„ν•΄μ„œλŠ” λ¬΄μ°¨μ›μ˜ 동적 λͺ¨λΈμ„ κ°œλ°œν•˜μ˜€λ‹€. μ„±λŠ₯κ³Ό λ¬Ό 관리 μ‚¬μ΄μ˜ 보닀 μ •ν™•ν•œ 관계λ₯Ό 규λͺ…ν•˜κΈ° μœ„ν•˜μ—¬ 일괄 λͺ¨λΈ (Lumped model)을 μˆ˜μ •ν•œ 동적 λͺ¨λΈμ„ μ‚¬μš©ν•˜μ˜€λ‹€. 이 λ‘˜ μ‚¬μ΄μ˜ 관계λ₯Ό λΆ„μ„ν•˜κΈ° μœ„ν•΄μ„œ μˆ˜μ •λœ λͺ¨λΈμ€ μž…κ΅¬λ‹¨, 쀑앙단, μΆœκ΅¬λ‹¨μ˜ μ„Έ λΆ€λΆ„μœΌλ‘œ κ΅¬μ„±ν•˜μ˜€λ‹€. μ „ν•΄μ§ˆ 막을 ν†΅κ³Όν•˜λŠ” 물의 μ–‘κ³Ό 각 λ‹¨μ—μ„œμ˜ μ „λ₯˜ λ³€ν™”λ₯Ό κ³„μ‚°ν•˜μ˜€λ‹€. λͺ¨μ‚¬ κ²°κ³ΌλŠ” 일괄 μŠ€νƒ λͺ¨λΈμ˜ 결과와 μ°Έκ³  λ¬Έν—Œμ˜ 비ꡐλ₯Ό 톡해 λΆ„μ„ν•˜μ˜€λ‹€. λ¬Ό 곡급이 μ›ν™œν•˜μ§€ μ•Šμ€ μš΄μ†‘μš© μ—°λ£Œ μ „μ§€μ—μ„œλŠ” μΆœκ΅¬λ‹¨μ—μ„œμ˜ λ¬Ό 양이 μ€‘μš”ν•˜κΈ° λ•Œλ¬Έμ— λ¬Ό μ–‘μ˜ μ˜ˆμΈ‘μ€ μ—°λ£Œ 전지 μžλ™μ°¨μ—μ„œ μ€‘μš”ν•œ 역할을 μ°¨μ§€ν•œλ‹€. 300kWκΈ‰ MCFC λ°œμ „μ†Œμ—μ„œλŠ” μƒν•œ κ°’κ³Ό ν•˜ν•œ κ°’ κΈ°μ€€λ§Œμ„ 가지고 μžˆλŠ” λ‹¨λ³€μˆ˜ μ•ŒλžŒ μ‹œμŠ€ν…œμ΄ 일반적으둜 μ μš©λ˜μ–΄ μžˆλ‹€. μ΄λŸ¬ν•œ λ‹¨μˆœν•œ κ°μ‹œ μ‹œμŠ€ν…œμ€ 이상 진단을 μœ„ν•œ λͺ¨λ‹ˆν„°λ§ μ‹œμŠ€ν…œ ν™•μž₯μ—λŠ” ν•œκ³„μ μ„ 가지고 μžˆλ‹€. λ”°λΌμ„œ μ£Όμ„±λΆ„ 뢄석 (Principal Component Analysis: PCA)에 κΈ°λ°˜ν•œ λ‹€λ³€λŸ‰ κ°μ‹œ μ‹œμŠ€ν…œμ„ μœ„ν•΄ κ²½ν—˜μ  λ³€μˆ˜ μ„ μ • 방법을 κ°œλ°œν•˜μ˜€λ‹€. μ‹€μ œ μš΄μ „ 데이터λ₯Ό μ΄μš©ν•˜μ—¬ 이상 κ°μ§€μ˜ μ„±λŠ₯을 κ²€μ¦ν•˜μ˜€λ‹€. I ν˜•κ³Ό II ν˜• μ—λŸ¬μœ¨μ„ λΉ„κ΅ν•œ κ²°κ³Ό λ„€ 가지 λ³€μˆ˜ κ·Έλ£Ήμ—μ„œ κ²½ν—˜μ  방법둠이 이상이 일어남을 잘 감지함을 검증할 수 μžˆμ—ˆλ‹€. μ΄λŸ¬ν•œ κ°μ‹œ κΈ°μˆ μ€ ν˜„μž₯에 μ„€μΉ˜λ˜μ–΄ μžˆλŠ” MCFC λ°œμ „μ†Œμ—μ„œ 정상 μƒνƒœμ™€ 이상 μƒνƒœλ₯Ό κ΅¬λ³„ν•˜μ§€ λͺ»ν•˜μ—¬ μšΈλ¦¬λŠ” 잘λͺ»λœ μ•ŒλžŒμ„ μ€„μ΄λŠ” 데 μ‚¬μš©ν•  수 μžˆλ‹€. λ‹€μ–‘ν•œ κ²½μš°μ— λŒ€ν•œ λͺ¨λΈλ§κ³Ό λͺ¨μ‚¬μ— κ΄€ν•œ 연ꡬ 결과듀은 λͺ¨μ‚¬μ˜ μ—¬λŸ¬ λͺ©μ μ— 맞게 μ ν•©ν•œ λͺ¨λΈλ§ 방법을 μ„ μ •ν•˜λŠ” 데 이용될 수 μžˆμ„ 것이닀. λ˜ν•œ, μ œμ•ˆλœ λͺ¨λΈλ“€μ€ 효율적인 λ””μžμΈκ³Ό μ•ˆμ •μ μΈ μš΄μ „κ³Ό 같은 λ‹€λ₯Έ λͺ©μ μ„ μœ„ν•΄ μ‚¬μš©λ  수 μžˆμ„ 것이닀.The value of fuel cell technology increases as the concerns for depletion of fossil fuels and environmental problems arise. By-product hydrogen generated in chemical complexes is used as feed for other chemical and refinery processes, as a product for sale as well as fuel for boilers. Therefore, high-grade usage of by-product hydrogen is required under these circumstances. Fuel cells whose technology has grown nearly at the level of commercialization are one way hydrogen can be used, giving it such high value. This thesis has three main purposes, which are economic feasibility analysis for proton exchange membrane fuel cell (PEMFC) power plant, transport phenomena analysis in PEMFC, improvement of monitoring system for molten carbonate fuel cell (MCFC) power plant, respectively. A PEMFC power plant is economically assessed as one of the methods for the use of by-product hydrogen. The process model is set to demonstrate the economic feasibility of a fuel cell power plant. An economic profitability standard is calculated for the base case and sensitivity analyses are carried out for key variables. Some cases also consider future plans about support systems and variations in prices. The comparison results among various hydrogen sources indicate that by-product hydrogen from chemical complex has an economic advantage. In this thesis, transport phenomena in a single cell and a stack are simulated by using both steady-state and dynamic model. A two-dimensional, the steady-state rigorous model is developed to simulate a single cell in PEMFC. The model accounts for gas species transport, electrochemical kinetics, charge distribution, and hydrodynamics. The governing differential equations consist of a free-path flow channel, gas-diffusion layer, and catalyst layers for the anode and cathode sides as well as the polymer electrolyte membrane region. The set of governing equations is solved by a finite volume-based fluid dynamics computational algorithm. The proposed model is validated with the experimental polarization curve. A zero-dimensional dynamic model is developed to simulate the stack behavior in PEMFC. This model is based on the lumped dynamic model but was modified to give a more accurate account of the correlation between performance and water management. To analyze this correlation, the modified model includes three segments of the entrance region, central region, and exit region. The amount of water transport across the membrane and the change in the current for each segment are calculated. The simulation results are analyzed and compared to the benchmarks from lumped stack results and reference literature. The amount of water at the channel outlet is an important aspect of a system that uses fuel cells in vehicles and that cannot be easily supplied with water. A univariate alarm system, which has only upper and lower limits, is usually employed to identify abnormal conditions in the 300 kW MCFC power plant. This simple monitoring system is limited for using in an extended monitoring system for fault diagnosis. Therefore, based on principal component analysis (PCA), a heuristic variable selection method for a multivariate monitoring system is presented. To verify the performance of the fault detection, real plant operations data are used. Furthermore, comparison between type 1 and type 2 errors for four different variable groups demonstrates that the developed heuristic method performs well when system faults occur. These monitoring techniques can reduce the number of false alarms occurring on-site at MCFC power plant. This work can contribute to determine proper modeling level for satisfying various purposes of simulation by providing a plenty of cases. Proposed models can be implemented in other purposes such as efficient design and stable operation.CHAPTER 1 : Introduction 1 1.1. Research motivation 1 1.2. Research objectives 4 1.3. Outline of the thesis 4 CHAPTER 2 : Modeling and Simulation of PEMFC for Economic Feasibility Analysis 6 2.1. Introduction 6 2.2. Process modeling and assumptions 8 2.3. Economic assessment 14 2.3.1. Capital cost 14 2.3.2. Operation and maintenance cost 15 2.3.3. Feed-in tariff 16 2.3.4. Carbon emission trading 16 2.3.5. Income 17 2.3.6. Economic feasibility 17 2.4. Case study 22 2.4.1. Technical scenario 22 2.4.2. Political scenario 22 2.4.3. Estimation of NPV 23 2.5. Results and discussion 29 2.6. Conclusions 35 CHAPTER 3 : Modeling and Simulation of PEMFC for Understanding Transport Phenomena 36 3.1. Introduction 36 3.2. Voltage modeling and assumptions 38 3.3. Steady-state modeling and simulation 41 3.3.1. Assumptions and specifications 41 3.3.2. Rigorous two dimensional model 41 3.3.3. Solving algorithm 42 3.3.4. Analysis of water distribution in a single cell 43 3.4. Dynamic modeling and simulation 52 3.4.1. 3-segment dynamic model 52 3.4.2. Assumptions and specifications 56 3.4.3. Analysis of water transport through membrane in the stack 57 3.5. Conclusions 74 CHAPTER 4 : Modeling and Simulation of MCFC power plant for Monitoring System 75 4.1. Introduction 75 4.2. Methodology for process monitoring 80 4.2.1. Principal component analysis for fault detection 81 4.2.2. Heuristic recursive variable selection algorithm 82 4.3. Implementation to MCFC power plant 90 4.4. Results and discussion 94 4.5. Conclusions 100 CHAPTER 5 : Concluding Remarks 101 5.1. Conclusions 101 5.2. Future works 104 Nomenclature 105 Literature cited 109 Abstract in Korean (μš” μ•½) 117Docto

    Simplified, Alternative Formulation of Numerical Simulation of Proton Exchange Membrane Fuel Cell

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    Three-Dimensional proton exchange fuel cell (PEMFC) operation in steady-state is simulated with computational fluid dynamics / multiphysics software that is based upon the finite-element method. PEMFC operation involves the simultaneous simulation of multiple, interconnected physics involving fluid flows, heat transport, electrochemical reactions, and both protonic and electronic conduction. Modeling efforts have varied by how they treat the physics occurring within and adjacent to the membrane-electrode assembly (MEA). Several approaches treat the MEA as part of the computational domain, solving multiple, and coupled conservation equations via the CFD approach within the 3 regions of the MEA. The thickness dimensions of the 3 regions of the MEA can be 2 orders of magnitude less than the features of the neighboring flow channels. Though this approach has been commercialized, the computational costs are quite high, due to the presence of large numbers of high-aspect ratio cells within the thin MEA. Research into the underlying physical phenomena, such as water transport, has also progressed, suggesting that various modeling errors may undermine many previous approaches. Other approaches treat the MEA as an interface, where they avoid these difficulties, but lose the ability to predict catalyst layer losses. This study develops an upgraded interface formulation where coupled water, heat, and current transport behaviors of the MEA are modeled analytically. Improving upon previous work, catalyst layer losses can now be modeled accurately without the ad-hoc changes in model chemical kinetic parameters. The interface model is developed considering only thru-plane variation, based upon varied fundamental research into each of the relevant physics. First, the model is validated against differential cell data with high and low humidity reactants. Validation continues with full 3-D test cases with different current levels and inlet conditions. Distributed data of current density are used to show model agreement with experimental data
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