Recently promulgated regulations of the US Environmental Protection Agency (EPA) aggressively lim... more Recently promulgated regulations of the US Environmental Protection Agency (EPA) aggressively limit CO 2 emissions from the US power industry. Carbon capture and increased utilization of renewable energy sources are viable approaches to reduce CO 2 emissions from the power industry. Cryogenic carbon capture considered in this study is a post–combustion CO 2 removal system that separates CO 2 from the flue gas by desublimation. In this investigation, a hybrid system of cryogenic carbon capture and a baseline fossil–fueled power generation unit are optimized with a framework to mathematically represent this hybrid system. Optimization of this hybrid system results in meeting the electricity demand through a combination of coal, gas, and wind power sources with a priority given to wind power for utilization. A comparison of the cost associated with operating the steam turbine as a baseline or load–following unit is also made. A significant decrease in the cycling cost associated with load–following of the coal–fired power plant is observed when it operates as a baseline unit. The decrease in the cycling costs is 82% and 85%, respectively, for when wind power is utilized in meeting the electricity demand and when it is not. The saving in the cycling costs is attributed to the energy storage of cryogenic carbon capture.
Recent Advances in the Application of MIDAE Systems John Hedengren, Jose Mojica, Reza Asgharzadeh... more Recent Advances in the Application of MIDAE Systems John Hedengren, Jose Mojica, Reza Asgharzadeh Shishivan, Seyed Mostafa Safdarnejad Brigham Young University, 350 CB, Provo, Utah A systematic approach to modeling includes selection of empirical or fundamental elements to construct a relationship between exogenous inputs and the measured or predicted outputs. Differential and algebraic equations are a natural expression of many systems that include equations of motion, material balances, energy balances, or linear time invariant (LTI) empirical models from system identification. When there are discrete levels of certain variables, the set of equations becomes a combination of integer and continuous decisions that lead to Mixed Integer Differential Algebraic Equations (MIDAEs). When the MIDAEs represent an actual system, it is desirable that the mathematical representation aligns with the physical observations. MIDAE representations are aligned with either steady state or dynamic da...
Hydrogen is the preferred fuel for fuel cells due to high reactivity for electrochemical reaction... more Hydrogen is the preferred fuel for fuel cells due to high reactivity for electrochemical reaction at anode. In the present study, a three dimensional CFD (Computational Fluid Dynamics) code was developed and validated to simulate the performance of a catalytic monolith fuel processor used for hydrogen generation. Methane autothermal reforming on 5% Ru/ -Al 2 O 3 catalyst was selected as the reaction mechanism. Ruthenium catalyst is a suitable catalyst for low temperature catalytic partial oxidation (LTCPO) process. This catalyst has good reforming activity and high hydrogen yield is obtained for ruthenium/ -alumina. This catalyst also demonstrated to be stable within the investigation time. The computational domain of the simulations was selected to be the catalytic section of the reformer. The results provided an adequate match to the experimental data from literature with respect to the outlet and maximum reactor temperature and also distribution of the products. The reactor performance was thereafter studied by numerically revealing the effects of variations of O 2 /C and S/C feed molar ratios, and feed temperature on the profiles of temperature and species concentrations. Moreover, effects of using air instead of pure oxygen were also investigated. It was concluded that at higher O 2 /C and S/C feed molar ratios and also at higher feed gas temperature, more hydrogen will be achieved at the reactor outlet, which is very suitable for fuel cell applications.
This work reviews a well-known methodology for batch distillation modeling, estimation, and optim... more This work reviews a well-known methodology for batch distillation modeling, estimation, and optimization but adds a new case study with experimental validation. Use of nonlinear statistics and a sensitivity analysis provides valuable insight for model validation and optimization veri cation for batch columns. The application is a simple, batch column with a binary methanol-ethanol mixture. Dynamic parameter estimation with an L1-norm error, nonlinear confi dence intervals, ranking of observable parameters, and efficient sensitivity analysis are used to refine the model and fi nd the best parameter estimates for dynamic optimization implementation. The statistical and sensitivity analyses indicated there are only a subset of parameters that are observable. For the batch column, the optimized production rate increases by 14% while maintaining product purity requirements.
Fiber optic sensors have gained increasing use in monitoring offshore structures. The sensors hav... more Fiber optic sensors have gained increasing use in monitoring offshore structures. The sensors have successfully monitored flowlines, umbilicals, wells, Tension Leg Platform (TLP) tendons, production and drilling risers, and mooring lines. Fiber optic sensors are capable of monitoring strain, temperature, pressure, and vibration. While the success of fiber optic monitoring has been clearly demonstrated, the sensors are now under consideration for automation applications. This paper details the plausibility of using pressure measurements from post-installed fiber Bragg grating (FBG) sensors with Model Predictive Control (MPC) to suppress severe slugging in subsea risers.
For dynamic optimization applications, real-time implementation is improved if there is an initia... more For dynamic optimization applications, real-time implementation is improved if there is an initialized prior solution that is sufficiently close to the intended solution. This paper details several initialization strategies that are useful for obtaining an initial solution. Methods include warm start from a prior solution, linearization, structural decomposition, and an incremental unbounding of decision variables that leads up to solving the originally intended problem. Even when initialization is not required to solve a dynamic optimization problem, a staged initialization approach sometimes leads to an overall faster solution time when compared to a single optimization attempt. Several challenging optimization problems are detailed that include a high-index differential and algebraic equation pendulum model, a standard reactor model used in many benchmark tests, a tethered aerial vehicle, and smart grid energy storage. These applications are representative of a larger class of applications resulting from the simultaneous approach to optimization of dynamic systems.
Increasing competitiveness of renewable power sources due to tightening restrictions on CO 2 emis... more Increasing competitiveness of renewable power sources due to tightening restrictions on CO 2 emission from fossil fuel combustion is expected to cause a shift in power generation systems of the future. This investigation considers the impact of the Cryogenic Carbon Capture TM (CCC) process on transitional power generation. The CCC process consumes less energy than chemical and physical absorption processes and has an energy storage capability that shifts the parasitic loss of the CCC process away from peak hours. The CCC process responds rapidly to the variation of electricity demand and has a time constant that is consistent with the intermittent supply from renewable power sources.
ABSTRACT Cryogenic Carbon Capture (CCC) is a CO2 mitigation process that can be integrated into e... more ABSTRACT Cryogenic Carbon Capture (CCC) is a CO2 mitigation process that can be integrated into existing baseline and load following fossil-fueled power plants. This process consumes less energy than conventional chemical absorption and includes energy storage capability. The CCC process has a fast response time to load changes to allow higher utilization of intermittent renewable power sources to be used at a grid-scale level in the power sector. The impact of the CCC process on the performance and operating profit of a single fossil-fueled power generation unit is studied in this paper. The proposed system (power production from wind, coal, and natural gas) meets the total electricity demand with 100% utilization of the available wind energy. The operational strategy for the hybrid energy-carbon capture system and the change in the performance of the hybrid system due to the seasonal changes are also examined in this paper. A sensitivity analysis is implemented to investigate the change in operating strategy of the hybrid system based on the relative fraction of wind energy adoption. The optimal wind energy adoption factor in the proposed system is obtained.
Recently promulgated regulations of the US Environmental Protection Agency (EPA) aggressively lim... more Recently promulgated regulations of the US Environmental Protection Agency (EPA) aggressively limit CO 2 emissions from the US power industry. Carbon capture and increased utilization of renewable energy sources are viable approaches to reduce CO 2 emissions from the power industry. Cryogenic carbon capture considered in this study is a post–combustion CO 2 removal system that separates CO 2 from the flue gas by desublimation. In this investigation, a hybrid system of cryogenic carbon capture and a baseline fossil–fueled power generation unit are optimized with a framework to mathematically represent this hybrid system. Optimization of this hybrid system results in meeting the electricity demand through a combination of coal, gas, and wind power sources with a priority given to wind power for utilization. A comparison of the cost associated with operating the steam turbine as a baseline or load–following unit is also made. A significant decrease in the cycling cost associated with load–following of the coal–fired power plant is observed when it operates as a baseline unit. The decrease in the cycling costs is 82% and 85%, respectively, for when wind power is utilized in meeting the electricity demand and when it is not. The saving in the cycling costs is attributed to the energy storage of cryogenic carbon capture.
Recent Advances in the Application of MIDAE Systems John Hedengren, Jose Mojica, Reza Asgharzadeh... more Recent Advances in the Application of MIDAE Systems John Hedengren, Jose Mojica, Reza Asgharzadeh Shishivan, Seyed Mostafa Safdarnejad Brigham Young University, 350 CB, Provo, Utah A systematic approach to modeling includes selection of empirical or fundamental elements to construct a relationship between exogenous inputs and the measured or predicted outputs. Differential and algebraic equations are a natural expression of many systems that include equations of motion, material balances, energy balances, or linear time invariant (LTI) empirical models from system identification. When there are discrete levels of certain variables, the set of equations becomes a combination of integer and continuous decisions that lead to Mixed Integer Differential Algebraic Equations (MIDAEs). When the MIDAEs represent an actual system, it is desirable that the mathematical representation aligns with the physical observations. MIDAE representations are aligned with either steady state or dynamic da...
Hydrogen is the preferred fuel for fuel cells due to high reactivity for electrochemical reaction... more Hydrogen is the preferred fuel for fuel cells due to high reactivity for electrochemical reaction at anode. In the present study, a three dimensional CFD (Computational Fluid Dynamics) code was developed and validated to simulate the performance of a catalytic monolith fuel processor used for hydrogen generation. Methane autothermal reforming on 5% Ru/ -Al 2 O 3 catalyst was selected as the reaction mechanism. Ruthenium catalyst is a suitable catalyst for low temperature catalytic partial oxidation (LTCPO) process. This catalyst has good reforming activity and high hydrogen yield is obtained for ruthenium/ -alumina. This catalyst also demonstrated to be stable within the investigation time. The computational domain of the simulations was selected to be the catalytic section of the reformer. The results provided an adequate match to the experimental data from literature with respect to the outlet and maximum reactor temperature and also distribution of the products. The reactor performance was thereafter studied by numerically revealing the effects of variations of O 2 /C and S/C feed molar ratios, and feed temperature on the profiles of temperature and species concentrations. Moreover, effects of using air instead of pure oxygen were also investigated. It was concluded that at higher O 2 /C and S/C feed molar ratios and also at higher feed gas temperature, more hydrogen will be achieved at the reactor outlet, which is very suitable for fuel cell applications.
This work reviews a well-known methodology for batch distillation modeling, estimation, and optim... more This work reviews a well-known methodology for batch distillation modeling, estimation, and optimization but adds a new case study with experimental validation. Use of nonlinear statistics and a sensitivity analysis provides valuable insight for model validation and optimization veri cation for batch columns. The application is a simple, batch column with a binary methanol-ethanol mixture. Dynamic parameter estimation with an L1-norm error, nonlinear confi dence intervals, ranking of observable parameters, and efficient sensitivity analysis are used to refine the model and fi nd the best parameter estimates for dynamic optimization implementation. The statistical and sensitivity analyses indicated there are only a subset of parameters that are observable. For the batch column, the optimized production rate increases by 14% while maintaining product purity requirements.
Fiber optic sensors have gained increasing use in monitoring offshore structures. The sensors hav... more Fiber optic sensors have gained increasing use in monitoring offshore structures. The sensors have successfully monitored flowlines, umbilicals, wells, Tension Leg Platform (TLP) tendons, production and drilling risers, and mooring lines. Fiber optic sensors are capable of monitoring strain, temperature, pressure, and vibration. While the success of fiber optic monitoring has been clearly demonstrated, the sensors are now under consideration for automation applications. This paper details the plausibility of using pressure measurements from post-installed fiber Bragg grating (FBG) sensors with Model Predictive Control (MPC) to suppress severe slugging in subsea risers.
For dynamic optimization applications, real-time implementation is improved if there is an initia... more For dynamic optimization applications, real-time implementation is improved if there is an initialized prior solution that is sufficiently close to the intended solution. This paper details several initialization strategies that are useful for obtaining an initial solution. Methods include warm start from a prior solution, linearization, structural decomposition, and an incremental unbounding of decision variables that leads up to solving the originally intended problem. Even when initialization is not required to solve a dynamic optimization problem, a staged initialization approach sometimes leads to an overall faster solution time when compared to a single optimization attempt. Several challenging optimization problems are detailed that include a high-index differential and algebraic equation pendulum model, a standard reactor model used in many benchmark tests, a tethered aerial vehicle, and smart grid energy storage. These applications are representative of a larger class of applications resulting from the simultaneous approach to optimization of dynamic systems.
Increasing competitiveness of renewable power sources due to tightening restrictions on CO 2 emis... more Increasing competitiveness of renewable power sources due to tightening restrictions on CO 2 emission from fossil fuel combustion is expected to cause a shift in power generation systems of the future. This investigation considers the impact of the Cryogenic Carbon Capture TM (CCC) process on transitional power generation. The CCC process consumes less energy than chemical and physical absorption processes and has an energy storage capability that shifts the parasitic loss of the CCC process away from peak hours. The CCC process responds rapidly to the variation of electricity demand and has a time constant that is consistent with the intermittent supply from renewable power sources.
ABSTRACT Cryogenic Carbon Capture (CCC) is a CO2 mitigation process that can be integrated into e... more ABSTRACT Cryogenic Carbon Capture (CCC) is a CO2 mitigation process that can be integrated into existing baseline and load following fossil-fueled power plants. This process consumes less energy than conventional chemical absorption and includes energy storage capability. The CCC process has a fast response time to load changes to allow higher utilization of intermittent renewable power sources to be used at a grid-scale level in the power sector. The impact of the CCC process on the performance and operating profit of a single fossil-fueled power generation unit is studied in this paper. The proposed system (power production from wind, coal, and natural gas) meets the total electricity demand with 100% utilization of the available wind energy. The operational strategy for the hybrid energy-carbon capture system and the change in the performance of the hybrid system due to the seasonal changes are also examined in this paper. A sensitivity analysis is implemented to investigate the change in operating strategy of the hybrid system based on the relative fraction of wind energy adoption. The optimal wind energy adoption factor in the proposed system is obtained.
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Papers by Seyed Mostafa Safdarnejad
but adds a new case study with experimental validation. Use of nonlinear statistics and a sensitivity analysis
provides valuable insight for model validation and optimization veri cation for batch columns. The application
is a simple, batch column with a binary methanol-ethanol mixture. Dynamic parameter estimation
with an L1-norm error, nonlinear confi dence intervals, ranking of observable parameters, and efficient sensitivity
analysis are used to refine the model and fi nd the best parameter estimates for dynamic optimization
implementation. The statistical and sensitivity analyses indicated there are only a subset of parameters that
are observable. For the batch column, the optimized production rate increases by 14% while maintaining
product purity requirements.
but adds a new case study with experimental validation. Use of nonlinear statistics and a sensitivity analysis
provides valuable insight for model validation and optimization veri cation for batch columns. The application
is a simple, batch column with a binary methanol-ethanol mixture. Dynamic parameter estimation
with an L1-norm error, nonlinear confi dence intervals, ranking of observable parameters, and efficient sensitivity
analysis are used to refine the model and fi nd the best parameter estimates for dynamic optimization
implementation. The statistical and sensitivity analyses indicated there are only a subset of parameters that
are observable. For the batch column, the optimized production rate increases by 14% while maintaining
product purity requirements.