The models that have been used in previous studies are simple steady state models for the fuel cell and liquid desiccant systems. In this study, I investigate the integration of rack and row level fuel cell powered servers with Liquid Desiccant Dehumidifier technology that can be dynamically dispatched to produce electricity and cooling in various amounts to meet power and air conditioning demands of data centers. In addition, the storage capacity to meet the demand of data center for the entire year is evaluated. The objectives of this phase of the study focus on theoretically evaluating the integrated system concept and to assess the achievable air conditioning from SOFC waste heat. To explore the feasibility of thermally integrating SOFC with LDD, a spatially resolved physical model developed in MATLAB is used to simulate the operating characteristics of this SOFC system. A corresponding physical model is developed to simulate the liquid desiccant air conditioner for dehumidification. This study considers SOFC systems capable of powering single server rack and row of servers and the operation of an LDD for cooling and dehumidification of that same configuration. The small-scale LDD operation is based on distributed waste heat from each individual SOFC at the rack level. The analysis will indicate whether waste-heat based cooling and dehumidification can power the servers and maintaining server operating temperatures and humidity in the safe range for different weather conditions.A spatially and temporally resolved fuel cell stack model has been developed based on the developed model in NFCRC using the MATLAB software. The model is developed for one unit cell that describes the response of the entire stack. 51 unitary anode-supported planar rectangular cells are assembled into one-unit SOFC stack.
Figure 18 presents one crossflow cell geometry with its components as well as a depiction of two repeated cells in series. The planar rectangular cells are flexible, compact,how to cure cannabis easy to produce, and have lower manufacturing cost compared to tubular cells. The unit cell consists of five layers i.e., cathode flow, anode flow, Positive electrode, Electrolyte, Negative electrode , fuel bipolar plate and air bipolar plate. The spatially and temporally resolved model uses different states to calculate parameters at different nodes of a cell. These nodal states are calculated at each time step among set of points in the time vector using the MATLAB Ordinary Differential Equation solver. These nodal states are composed of nodal temperatures of fuel and air separator plates , temperature of fuel and air flows, nodal temperature of the PEN, nodal concentration of different species in both cathode and anode flow sides , nodal current and cathode/anode flow inlet pressure. The evaluated parameters based on the mentioned states are nodal Nernst voltage, nodal voltage losses, nodal operating voltage , nodal molar flow rate of ions crossing the PEN, nodal heat generation in the PEN, nodal heat and mass transfers and many other parameters. A two-dimensional multi-layer approach is accomplished for both the electrochemical modeling and heat transfer modeling resulting in a quasi-3-D representation of an electrochemical cell. As an assumption, instantaneous electrochemical reactions are assumed, due to relatively fast electrochemical reactions compared to cell and stack thermal response dynamics. Using Faraday’s law, the rate of electrochemical reactions is directly proportional to the cell current. Furthermore, it is considered that electrical current flows only in one direction from one electrode to the other one along the PEN, as the electrical potential is assumed constant on the electrode surfaces.
In the developed model, gases behave as ideal gas due to high operating temperature of the SOFC. In this study a 5×5 spatial resolution is accomplished for all 5 layers . The solid oxide fuel cell has an active surface area of 139.24cm2 . Fuel cell module material properties are presented in Table 2 and geometry parameters are presented in Table 3. Figure 19 depicts schematically the geometric parameters of the fuel cell.The developed model takes into account the conservation of energy within each node and energy transfer between control volumes to calculate the nodal temperature changes during dynamic operating conditions for all 5 layers which are fuel plate, air plate, cathode flow, anode flow and the PEN. Nodal energy balance equation for the cathode/anode stream includes convective heat transferred to the solid walls , enthalpy flux due to the electrochemical reaction, mass transfer of oxygen ions from/to the PEN, and inlet/outlet enthalpy flux of the bulk flow from/to adjacent nodes. It is assumed that temperature in each control volume decreases/increases linearly along the control volume of each node . A nodal energy balance for the PEN includes convective heat transferred to the PEN from streams, conductive heat transferred to the PEN from bipolar plate, conductive heat transferred to adjacent nodes in PEN and heat generation due to the electrochemical reactions and electrical resistances. Radiation heat transfer between PEN and bipolar plate is negligible. A nodal energy balance equation for the bipolar plate includes convective heat transferred to bipolar plate from streams, conductive heat transferred to bipolar plate from PEN and conductive heat transferred to adjacent nodes in bipolar plate. Adiabatic boundary condition is considered for all the nodes located at the beginning and at the end of the cell on PEN and bipolar plate, as the cell height is relatively thin compared to its length. Also, it is considered that the stack is well insulated such that heat loss to the environment is negligible. The nodal energy balance equation for cathode and anode flows, PEN and bipolar plate are presented below.
Note that all nodal specific heat capacities are calculated at the node temperature. Also, for each cathode/anode node, inlet flow enthalpy is the outlet flow enthalpy of the previous node in the flow direction as follows. As flows move from inlets to the cathode and anode outlets, the composition of fuel in anode side and the composition of oxygen/nitrogen at cathode side will be changed. The developed model takes into account the conservation of mass within each node and mass transfer between control volumes to calculate the nodal species’ concentration’s changes . Mass balance in cathode/anode flow side includes inlet/outlet molar flow rates from/to adjacent nodes and variation due to the existing electrochemical reaction. The nodal dynamic mass balance equations for steam, hydrogen, carbon monoxide, carbon dioxide, methane, oxygen and nitrogen species are presented below. Note that for each node, the inlet molar flow rate is the outlet molar flow rate of the previous node in the flow direction as follows. Figure 20 to Figure 24 show the spatial distribution of temperature, Nernst voltage, losses, voltage, and current density in a unit SOFC. The temperature changes between 1000K- 1040K. The temperature has its lowest amount at the corner close to the cathode and anode streams inlet where the air which is cooling stream has its lowest temperature and the reformation which is endothermic is still occurring at the beginning of the cell. Temperature has the highest amount at the corner close to the cathode and anode streams outlet where air has its highest temperature and electrochemical reaction which is dominant at the end of cell generates heat due to its exothermicity. The Nernst voltages are among 0.9V-0.98V. The Nernst voltage is highest at the corner close to the cathode and anode inlet streams where both fuel and oxidant partial pressures are high leading to high thermodynamic potential with the lowest Nernst potentials realized at the corner close to the cathode and anode streams outlet. The lowest amount of losses is 0.065V captured where the temperature is highest. High temperature increases the thermal energy available in the system,trimming cannabis generally resulting in the fact that all the particles in the system now move and vibrate with increased intensity. This higher level of thermal activity will possess sufficient energy to overcome activation polarization and most importantly increases electrolyte ionic conductivity, which decreases the ohmic loss. Figure 22 shows the spatial distribution of cell operating voltage which is uniform along the cell as expected due to the equipotential surface that is established by the good electronic conductivity of the electrodes and bipolar plates. The current density along the direction of fuel flow decreases as the fuel gets consumed and has less potential to produce current.The SOFC system model contains a fuel cell stack, an anode off-gas oxidizer, air preheating heat exchangers, recirculate valve, mixer, blower, and reformer. A system diagram is provided in Figure 25. The oxidizer outlet preheats air and fuel first, and then, the leftover heat from the SOFC exhaust is recovered for regenerating desiccant liquid in the LDD system.Cell temperature control is one of the key issues involved in the dynamic operation of high temperature SOFC systems. In this study, the stack is thermally managed by manipulating one actuator, which controls the blower power. A variable speed blower enables control of blower dynamics that consider the inertia of the blower as described above. Increasing the blower power ultimately increases the blower speed, which in-turn increases the air flow rate introduced to the stack. The air flow rate has two functions in the proposed system, i.e., providing the oxygen for the electrochemical reactions and providing cooling or heating to the stack. The temperature control strategy consists of two parts. Stack temperature gradient is controlled with blower power. If the temperature gradient goes higher than the set point, the blower power increases which increases the air flow rate which cools the stack. To control stack average temperature, the valve position changes to increase or decrease the air flow to oxidizer which affects the cell inlet air flow temperature. To decrease the cell average temperature, the valve opens more, to decrease the hot flow temperature in the air heat exchanger. In this study, the controller set-point temperature difference constraint is 50K. Also, the inlet temperature of both anode and cathode temperature are controlled to the set point of 1023K. The system model is based on a commercially available SOFC systems called BlueGEN. BlueGEN CHP unit, originally manufactured by Ceramic Fuel Cells Ltd . BlueGEN is a commercially available SOFC CHP system, now built and sold by SOLIDpower, designed for small- to medium-scale building applications. Operating on natural gas, the unit can produce power modulated from 500We to 2kWe ; however, it achieves its highest net electrical efficiency of 60% at a 1.5kWe output. The BlueGEN SOFC unit consists of 51 planar type Yttria Stabilized Zirconia electrolyte-supported cell layer sets and operates at around 750℃. Hydrogen is produced from natural gas by external and internal steam reforming. The polarization curve data from the BlueGEN SOFC system tested at the NFCRC and the developed model results are presented in Figure 26. Note that the V-j curve obtained from the test covers only the operating envelope of the SOFC system. The steady state performance of the system was calculated under the standard operating conditions of the BlueGEN at 85% fuel utilization and cathode outlet temperature of 750˚C. The SOFC system is controlled to keep the stack temperature difference at 50˚C. The SOFC parameter and standard operating conditions are presented in Table 4. The electrical efficiency of the stack is over 61% under standard operating conditions. The steady state performance parameters of the model for 1.5kW SOFC system and experiment values are compared in Table 5. Note that experimental values well match those of the model. Note also that the exhaust gas temperature and flow rate were not measured during the experiment. The particular SOFC system that was evaluated in this study was designed for CHP, and thus produces more heat than would be used for preheating the SOFC inlet air and fuel. The heat produced from the SOFC system in the current case is then used for producing hot water for LiCl regeneration purposes. This model indicates that a nominal 1.5kW system would produce 0.0104kg/s of exhaust gas and that the temperature of the exhaust would be 100˚C. Electricity demand for a single residential unit is used as a desired demand applied to the spatially resolved dynamic SOFC model. SOFC model results that generated output power follows the desired demand quite closely except for very short periods of high ramp rate operating conditions. Figure 28 shows the electrical efficiency of the system during the dynamic operation. The average efficiency during dynamic operation is 71%. The high efficiency is due to high fuel utilization and part load operation of the system which also lead to a lower exhaust temperature.