2 research outputs found
μ°λ£μ μ§ μμ€ν μ λν λͺ¨λΈλ§, κ²½μ μ± λΆμ λ° λͺ¨λν°λ§μ κ΄ν μ°κ΅¬
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Όλ¬Έ (λ°μ¬)-- μμΈλνκ΅ λνμ : ννμ물곡νλΆ, 2012. 8. νμ’
ν.μμ κ³ κ°μ λν μ°λ €μ νκ²½ λ¬Έμ μ μ¦κ°μ λ°λΌ μ°λ£ μ μ§ κΈ°μ μ κ°μΉκ° λκ² νκ° λ°κ³ μλ€. νν 곡λ¨μμ μμ°λλ λΆμ μμλ λ€λ₯Έ νν 곡μ μ΄λ μ μ 곡μ μμ μ¬μ©λκ±°λ 보μΌλ¬μ μ°λ£λ‘ μ°μ΄κ³ μλ€. λΆμ μμλ₯Ό μ’λ ν¨μ¨μ μΌλ‘ μ¬μ©νλ κΈ°μ μ λν νμμ±μ΄ λλλκ³ μλ μν©μμ μμλ₯Ό κ³ ν¨μ¨λ‘ μ¬μ©ν μ μλ μ°λ£ μ μ§ κΈ°μ μ΄ μμ©ν μμ€μΌλ‘ λ°μ νκ³ μλ€. λ³Έ λ
Όλ¬Έμμλ κ³ λΆμ μ ν΄μ§ μ°λ£ μ μ§ (Proton Exchange Membrane Fuel Cell: PEMFC) λ°μ μμ κ²½μ μ± λΆμ, PEMFCμ μ΄λ νμ λΆμ, μ©μ΅ νμ°μΌ μ°λ£ μ μ§ (Molten Carbonate Fuel Cell: MCFC) λ°μ μλ₯Ό μν κ°μ μμ€ν
μ κ°μ μ΄λΌλ μΈ κ°μ§ μ£Όμ λͺ©νλ₯Ό λ΄κ³ μλ€.
λΆμ μμλ₯Ό μ¬μ©νλ λ°©λ²μ νλλ‘ PEMFC λ°μ μμ κ²½μ μ±μ λΆμνμλ€. μ΄λ₯Ό μν΄ μ°λ£ μ μ§ λ°μ μμ κ²½μ μ νλΉμ±μ κ²μ¦νκΈ° μν 곡μ λͺ¨λΈμ κ°λ°νμλ€. λν, κ²½μ μ νλΉμ±μ κΈ°μ€μΌλ‘ νμ¬μ μν©μ λν κ²½μ μ± λΆμκ³Ό μ€μ λ³μμ λν λ―Όκ°λ λΆμμ μννμλ€. λ―Έλμ μν©μ κ°μνκΈ° μν΄μ μ λΆ μ§μ μ λ λ³νμ μμ κ°κ²©μ λ³νλ₯Ό κ³ λ €νμλ€. λ€μν μμ μμ° λ°©μμ λΉκ΅ν κ²°κ³Ό νν 곡λ¨μμ μμ°λλ λΆμ μμλ₯Ό μ¬μ©ν κ²½μ°κ° κ²½μ μ μ΄μ μ κ°μ§κ³ μμμ νμΈνμλ€.
λ³Έ λ
Όλ¬Έμμλ λ¨μ μ μ§μ μ€νμμ μΌμ΄λλ μ΄λ νμμ λͺ¨μ¬νκΈ° μν΄μ μ μ λͺ¨λΈκ³Ό λμ λͺ¨λΈμ μ¬μ©νμλ€. PEMFC λ¨μ μ μ§μ λͺ¨μ¬λ₯Ό μν΄μλ 2μ°¨μμ μ μ μμΈ λͺ¨λΈμ κ°λ°νμλ€. λͺ¨λΈμ μ΄μ©νμ¬ κ°μ€μ μ΄λ, μ κΈ°νν λ°μ, μ λ₯ λΆν¬μ μ 체 μνμ λν κ³μ°μ μννμλ€. μ§λ°° λ°©μ μλ€μ μ ν 체μ λ²μ κΈ°μ΄ν μ 체 μν κ³μ° μκ³ λ¦¬μ¦μ μ΄μ©νμ¬ κ³μ°νμλ€. μ μλ λ°©λ²μ μ€νμ ν΅ν΄ μ»μ λΆκ·Ή 곑μ κ³Όμ λΉκ΅λ₯Ό ν΅ν΄ κ²μ¦νμλ€. PEMFC μ€νμ λͺ¨μ¬λ₯Ό μν΄μλ 무차μμ λμ λͺ¨λΈμ κ°λ°νμλ€. μ±λ₯κ³Ό λ¬Ό κ΄λ¦¬ μ¬μ΄μ λ³΄λ€ μ νν κ΄κ³λ₯Ό κ·λͺ
νκΈ° μνμ¬ μΌκ΄ λͺ¨λΈ (Lumped model)μ μμ ν λμ λͺ¨λΈμ μ¬μ©νμλ€. μ΄ λ μ¬μ΄μ κ΄κ³λ₯Ό λΆμνκΈ° μν΄μ μμ λ λͺ¨λΈμ μ
ꡬλ¨, μ€μλ¨, μΆκ΅¬λ¨μ μΈ λΆλΆμΌλ‘ ꡬμ±νμλ€. μ ν΄μ§ λ§μ ν΅κ³Όνλ λ¬Όμ μκ³Ό κ° λ¨μμμ μ λ₯ λ³νλ₯Ό κ³μ°νμλ€. λͺ¨μ¬ κ²°κ³Όλ μΌκ΄ μ€ν λͺ¨λΈμ κ²°κ³Όμ μ°Έκ³ λ¬Ένμ λΉκ΅λ₯Ό ν΅ν΄ λΆμνμλ€. λ¬Ό 곡κΈμ΄ μννμ§ μμ μ΄μ‘μ© μ°λ£ μ μ§μμλ μΆκ΅¬λ¨μμμ λ¬Ό μμ΄ μ€μνκΈ° λλ¬Έμ λ¬Ό μμ μμΈ‘μ μ°λ£ μ μ§ μλμ°¨μμ μ€μν μν μ μ°¨μ§νλ€.
300kWκΈ MCFC λ°μ μμμλ μν κ°κ³Ό νν κ° κΈ°μ€λ§μ κ°μ§κ³ μλ λ¨λ³μ μλ μμ€ν
μ΄ μΌλ°μ μΌλ‘ μ μ©λμ΄ μλ€. μ΄λ¬ν λ¨μν κ°μ μμ€ν
μ μ΄μ μ§λ¨μ μν λͺ¨λν°λ§ μμ€ν
νμ₯μλ νκ³μ μ κ°μ§κ³ μλ€. λ°λΌμ μ£Όμ±λΆ λΆμ (Principal Component Analysis: PCA)μ κΈ°λ°ν λ€λ³λ κ°μ μμ€ν
μ μν΄ κ²½νμ λ³μ μ μ λ°©λ²μ κ°λ°νμλ€. μ€μ μ΄μ λ°μ΄ν°λ₯Ό μ΄μ©νμ¬ μ΄μ κ°μ§μ μ±λ₯μ κ²μ¦νμλ€. I νκ³Ό II ν μλ¬μ¨μ λΉκ΅ν κ²°κ³Ό λ€ κ°μ§ λ³μ κ·Έλ£Ήμμ κ²½νμ λ°©λ²λ‘ μ΄ μ΄μμ΄ μΌμ΄λ¨μ μ κ°μ§ν¨μ κ²μ¦ν μ μμλ€. μ΄λ¬ν κ°μ κΈ°μ μ νμ₯μ μ€μΉλμ΄ μλ MCFC λ°μ μμμ μ μ μνμ μ΄μ μνλ₯Ό ꡬλ³νμ§ λͺ»νμ¬ μΈλ¦¬λ μλͺ»λ μλμ μ€μ΄λ λ° μ¬μ©ν μ μλ€.
λ€μν κ²½μ°μ λν λͺ¨λΈλ§κ³Ό λͺ¨μ¬μ κ΄ν μ°κ΅¬ κ²°κ³Όλ€μ λͺ¨μ¬μ μ¬λ¬ λͺ©μ μ λ§κ² μ ν©ν λͺ¨λΈλ§ λ°©λ²μ μ μ νλ λ° μ΄μ©λ μ μμ κ²μ΄λ€. λν, μ μλ λͺ¨λΈλ€μ ν¨μ¨μ μΈ λμμΈκ³Ό μμ μ μΈ μ΄μ κ³Ό κ°μ λ€λ₯Έ λͺ©μ μ μν΄ μ¬μ©λ μ μμ κ²μ΄λ€.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 (μ μ½) 117Docto
Simplified, Alternative Formulation of Numerical Simulation of Proton Exchange Membrane Fuel Cell
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