Uncertain Gain and Time-Delay Control of 300-kW SOFC-GT

2021 ◽  
Author(s):  
Tooran Emami ◽  
David Tucker ◽  
John Watkins
Keyword(s):  
Fuel Cell ◽  
Time Delay ◽  
Pid Controller ◽  
Transfer Functions ◽  
Cell Mass ◽  
Electric Load ◽  
Cold Air ◽  
Internal Gain ◽  
Air Valve ◽  
Turbine Speed

Abstract This paper presents a Proportional Integral Derivative (PID) controller design with the presence of an uncertain internal gain and additional time delay in the forward path of a 300 kW Solid Oxide Fuel Cell-Gas Turbine (SOFC-GT). The outputs of the system are turbine speed and the fuel cell mass flow rate. A fixed set of proportional controller coefficients are determined to graphically develop an area of selection for the integral and derivative coefficients of the PID controller. The inputs to the power plant are the electric load and cold air valve. The decentralized controllers are applied to four sub-systems as a Single Input Single Output (SISO). The PID controller coefficients are selected from a singular matrix solution that stabilizes the system and satisfies the internal gain and time delay uncertainties. Two sub-systems are the transfer functions of the turbine speed over the electric load and the cold air valve. The other two sub-systems are the transfer functions of the fuel cell mass flow rate over the electric load and the cold air bypass valve. Multiple options for selecting PID controller coefficients are beneficial to the SOFC-GT plant due to the wide range of operations and internal uncertainty interactions. The specific internal time delay and gain margins increase the reliability and robustness of the SOFC-GT with multiple uncertain parameters.

Decentralized PID Controller Design for SOFC-GT

2020 ◽  
Author(s):  
Tooran Emami ◽  
Alex Tsai ◽  
David Tucker
Keyword(s):  
Fuel Cell ◽  
Power Plant ◽  
Flow Rate ◽  
Pid Controller ◽  
Transfer Functions ◽  
Cell Mass ◽  
Electric Load ◽  
Cold Air ◽  
Air Valve ◽  
Turbine Speed

Abstract This paper presents a performance of a 300 kW Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) pilot power plant simulator under an area of selection of the Proportional Integral Derivative (PID) controller coefficients that satisfies the stability, gain and phase margins. The performance of turbine speed and the fuel cell mass flow rate is controlled by the set of PID controller coefficients from this area. The input to the subsystems power plant are the electric load and cold air valve. The decentralized controllers are designed for each subsystems performance individually as a Single Input Single Output (SISO) system. Two of subsystem plants are the transfer functions of turbine speed over the electric load and the cold air valve. The other two subsystem plants are the transfer functions of fuel cell mass flow rate over the electric load and the cold air bypass valve. The flexibility to have an area to select PID controller coefficients is beneficial to SOFC-GT plant due to the wide range of operations and internal parameter interactions. Designing the PID controller for the specific phase and gain margins increase the reliability and robustness of the SOFC-GT with multiple uncertain parameters. The practical implementation of this methodology is presented through the software environment.

Simultaneous Turbine Speed Regulation and Fuel Cell Airflow Tracking of a SOFC/GT Hybrid Plant With the Use of Airflow Bypass Valves

2011 ◽  
Vol 8 (6) ◽  
Author(s):  
Alex Tsai ◽  
David Tucker ◽  
David Clippinger
Keyword(s):  
Fuel Cell ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Transfer Functions ◽  
Nonlinear Models ◽  
Cell Mass ◽  
Hybrid Plant ◽  
Simultaneous Control ◽  
Turbine Speed

This paper studies a novel control methodology aimed at regulating and tracking turbo machinery synchronous speed and fuel cell mass flow rate of a SOFC/GT hardware simulation facility with the sole use of airflow bypass valves. The hybrid facility under consideration consists of a 120 kW auxiliary power unit gas turbine coupled to a 300 kW SOFC hardware simulator. The hybrid simulator allows testing of a wide variety of fuel cell models under a hardware-in-the-loop configuration. Small changes in fuel cell cathode airflow have shown to have a large impact on system performance. Without simultaneous control of turbine speed via load or auxiliary fuel, fuel cell airflow tracking requires an alternate actuator methodology. The use of bypass valves to control mass flow rate and decouple turbine speed allows for a greater flexibility and feasibility of implementation at the larger scale, where synchronous speeds are required. This work utilizes empirically derived transfer functions (TF) as the system model and applies a fuzzy logic (FL) control algorithm that can be easily incorporated to nonlinear models of direct fired recuperated hybrid plants having similar configurations. This methodology is tested on a SIMULINK/matlab platform for various perturbations of turbine load and fuel cell heat exhaust.

Simultaneous Turbine Speed Regulation and Fuel Cell Airflow Tracking of a SOFC/GT Hybrid Plant With the Use of Airflow Bypass Valves

2011 ◽  
Author(s):  
Alex Tsai ◽  
David Tucker ◽  
David Clippinger
Keyword(s):  
Fuel Cell ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Transfer Functions ◽  
Nonlinear Models ◽  
Cell Mass ◽  
Hybrid Plant ◽  
Simultaneous Control ◽  
Turbine Speed

This paper studies a novel control methodology aimed at regulating and tracking turbo machinery synchronous speed and fuel cell mass flow rate of a SOFC/GT hardware simulation facility with the sole use of airflow bypass valves. The hybrid facility under consideration consists of a 120kW auxiliary power unit gas turbine coupled to a 300kW SOFC hardware simulator. The hybrid simulator allows testing of a wide variety of fuel cell models under a Hardware-in-the-Loop configuration. Small changes in fuel cell cathode airflow have shown to have a large impact on system performance. Without simultaneous control of turbine speed via load or auxiliary fuel, fuel cell airflow tracking requires an alternate actuator methodology. The use of bypass valves to control mass flow rate and decouple turbine speed allows for a greater flexibility and feasibility of implementation at the larger scale, where synchronous speeds are required. This work utilizes empirically derived Transfer Functions (TF) as the system model and applies a Fuzzy Logic (FL) control algorithm that can be easily incorporated to nonlinear models of direct fired recuperated hybrid plants having similar configurations. This methodology is tested on a SIMULINK/MATLAB platform for various perturbations of turbine load and fuel cell heat exhaust.

Multi-Coordination of Actuators in Advanced Power Systems

2015 ◽  
Author(s):  
Paolo Pezzini ◽  
Kenneth M. Bryden ◽  
David Tucker ◽  
Larry Banta
Keyword(s):  
Fuel Cell ◽  
Power System ◽  
Waste Heat ◽  
Internal Model Control ◽  
System Component ◽  
Experimental Comparison ◽  
Cold Air ◽  
Single Input Single Output ◽  
Model Control ◽  
Turbine Speed

Multi-coordination of actuators for a highly integrated, tightly coupled advanced power system was evaluated using the Hybrid Performance (Hyper) project facility at the U.S. Department of Energy’s National Energy Technology Laboratory (NETL). A two-by-two scenario in a fuel cell, turbine hybrid power system was utilized as a representative problem in terms of system component coupling during transients and setpoint changes. In this system, the gas turbine electric load is used to control the turbine speed, and the cold air bypass valve regulated fuel cell cathode mass flow. Perturbations in the turbine speed caused by variations in the waste heat from the fuel cell affect the cathode airflow, and the cold-air bypass control action required for constant cathode airflow strongly affects the turbine speed. Previous implementation of two single-input, single-output (SISO) controllers failed to provide acceptable disturbance rejection and setpoint tracking under these highly coupled conditions. A multiple-input, multiple-output (MIMO) controller based on the classic internal model control (IMC) concept was implemented and experimentally tested for the first time using the Hyper project facility. The state-space design of the MIMO configuration, the control law integration into the digital control platform, and the experimental comparison with the SISO case are presented.

Simulation of Model Predictive Control for a Fuel Cell/Gas Turbine Power System Based on Experimental Data and the Recursive Identification Method

2016 ◽  
Author(s):  
Bernardo Restrepo ◽  
Larry E. Banta ◽  
David Tucker
Keyword(s):  
Fuel Cell ◽  
Model Predictive Control ◽  
State Space ◽  
Gas Turbine ◽  
Predictive Control ◽  
Measured Data ◽  
The State ◽  
Electric Load ◽  
Dynamic Data ◽  
Turbine Speed

A Model Predictive Control (MPC) strategy has been suggested and simulated with the empirical dynamic data collected on the Hybrid Performance (HyPer) project facility installed at the National Energy Technology Laboratory (NETL), U.S. Department of Energy, in Morgantown, WV. The HyPer facility is able to simulate gasifier/fuel cell power systems and uses hardware-based simulation approach that couples a modified recuperated gas turbine cycle with hardware driven by a solid oxide fuel cell model. Dynamic data was collected by operating the HyPer facility continuously during five days. Bypass valves along with electric load of the system were manipulated and variables such as mass flow, turbine speed, temperature, pressure, among others were recorded for analysis. This work was developed by focusing on a multivariable recursive system identification structure fitting measured transient data. The results showed that real-time or online data is a viable means to provide a dynamic model for controller design. The excursion dynamic data collected between the setup changes of the experiments was processed off-line to determine the feasibility of applying an adaptive Model Predictive Control strategy. One of the strengths of MPC is that it can allow the designer to impose strict limits on inputs and outputs in order to keep the system within known safe bounds. Two identification structures, ARX and a State-Space model, were used to fit the measured data to dynamic models of the HyPer facility. The State-Space identification was very accurate with a second order model. Visual inspection of the tracking accuracy shows that the ARX approach was approximately as accurate as the State-Space structure in its ability to reproduce measured data. However, by comparing the Loss Function and the FPE parameters, the State-Space approach gives better results. The MPC proved to be a good strategy to control the HyPer facility. The airflow valves and the electric load were used to control the turbine speed and the cathode airflow. For the ARX/State Space models, the MPC was very robust in tracking set-point variations. The anticipation feature of the MPC was revealed to be a good tool to compensate time delays in the output variables of the facility or to anticipate eventual set-point moves in order to achieve the objectives very quickly. The MPC also displayed good disturbance rejection on the output variables when the fuel flow was set to simulate FC heat effluent disturbances. Different off-design scenarios of operation have been tested to confirm the estimated implementation behavior of the plant-controller dynamics.

Recursive System Identification and Simulation of Model Predictive Control Based on Experimental Data to Control the Cathode Side Parameters of the Hybrid Fuel Cell/Gas Turbine

2017 ◽  
Vol 14 (3) ◽  
Author(s):  
Bernardo Restrepo ◽  
David Tucker ◽  
Larry E. Banta
Keyword(s):  
Fuel Cell ◽  
Model Predictive Control ◽  
State Space ◽  
Predictive Control ◽  
Measured Data ◽  
The State ◽  
Cathode Side ◽  
Electric Load ◽  
Dynamic Data ◽  
Turbine Speed

A model predictive control (MPC) strategy has been suggested and simulated with the empirical dynamic data collected on the hybrid performance (HyPer) project facility installed at the National Energy Technology Laboratory (NETL), U.S. Department of Energy, in Morgantown, WV. The excursion dynamic data collected between the setup changes of the actuators on the cathode side of the HyPer facility were processed offline to determine the feasibility of applying an adaptive model predictive control strategy. Bypass valves along with electric load (EL) of the system were manipulated, and variables such as turbine speed, mass flow, temperature, pressure of the cathode side, among others were recorded for analysis. The three main phases of the MPC, identification of the models, control design, and control tuning have been described. Two identification structures, autoregressive exogenous (ARX) and a state-space model, were used to fit the measured data to dynamic models of the facility. The system identification ARX model required around 0.12 s of computer time. The state-space identification algorithm spent around 0.65 s, which was relatively high considering that the sample time of the sensors was 0.4 s. Visual inspection of the tracking accuracy showed that the ARX approach was approximately as accurate as the state-space structure in its ability to reproduce measured data. However, by comparing the loss function and the final prediction error (FPE) parameters, the state-space approach gives better results. For the ARX/state-space models, the MPC was robust in tracking setpoint variations. The MPC strategy described here offers potential to be the way to control the HyPer facility. One of the strengths of MPC is that it can allow the designer to impose strict limits on inputs and outputs in order to keep the system within known safe bounds. Constraints are highly present in the HyPer facility. The constraint airflow valves and the electric load were used in the simulation to control the constraint turbine speed and the cathode airflow (CAF). The MPC also displayed good disturbance rejection on the output variables when the fuel flow was set to simulate fuel cell (FC) heat effluent disturbances. Different off-design scenarios of operation were tested to confirm the estimated implementation behavior of the plant-controller dynamics. One drawback in MPC implementation is the computational time consuming between calculations and will be considered for future studies.

Robust PID Controller Design of a Solid Oxide Fuel Cell Gas Turbine

2016 ◽  
Author(s):  
Tooran Emami ◽  
Alex Tsai ◽  
David Tucker
Keyword(s):  
Fuel Cell ◽  
Time Delay ◽  
Solid Oxide Fuel Cell ◽  
Gas Turbine ◽  
Pid Controller ◽  
Solid Oxide ◽  
Practical Implementation ◽  
Airflow Rate ◽  
Oxide Fuel ◽  
Wide Range

The performance of a 300 kW Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) pilot power plant simulator is evaluated by applying a set of robust Proportional Integral Derivative (PID) controllers that satisfy time delay and gain uncertainties of the SOFC-GT system. The actuators are a fuel valve (FV) that models the fuel cell thermal exhaust, and a cold-air (CA) valve which bypasses airflow rate from the fuel cell cathode. The robust PID controller results for the uncertain gains are presented first, followed by a design for uncertain time delays for both, FV and CA bypass valves. The final design incorporates the combined uncertain gain parameters with the time delay modeling of both actuators. This Multiple-Input Multiple-Output (MIMO) technique is beneficial to plants having a wide range of operation and a strong parameter interaction. The practical implementation is presented through simulation in the Matlab/Simulink environment.

Cold-Air Bypass Characterization for Thermal Management of Fuel Cell Gas Turbine Hybrids

2017 ◽  
Vol 139 (6) ◽  
Author(s):  
Valentina Zaccaria ◽  
David Tucker ◽  
Alberto Traverso
Keyword(s):  
Fuel Cell ◽  
System Dynamics ◽  
Gas Turbine ◽  
Thermal Management ◽  
Inlet Temperature ◽  
Variable Speed ◽  
Average Cell ◽  
Cold Air ◽  
Significant Difference ◽  
Turbine Speed

The effect of cathode airflow variation on the dynamics of a fuel cell gas turbine hybrid system was evaluated using a cyber-physical emulator. The coupling between cathode airflow and other parameters, such as turbine speed or pressure, was analyzed comparing the results at fixed and variable speed. In particular, attention was focused on fuel cell temperatures and gradients: cathode airflow, which is generally employed for thermal management of the stack, was varied by manipulating a cold-air bypass. A significant difference was observed in the two cases in terms of turbine inlet, exhaust gas, cathode inlet, and average cell temperatures. When the turbine speed was held constant, a change in cathode airflow resulted in a strong variation in cathode inlet temperature, while average cell temperature was not significantly affected. The opposite behavior was observed at variable speed. The system dynamics were analyzed in detail in order to explain this difference. Open-loop response was analyzed in this work for its essential role in system identification. However, a significant difference was observed between fixed and variable speed cases, because of the high coupling between turbine speed and cathode airflow. These results can give a helpful insight of system dynamics and control requirements. Cold-air valve bypass position also showed a strong effect on surge margin and pressure dynamics in both cases.

Evaluation of Electric Load Following Capability on Fuel Cell System Fueled by High-Purity Hydrogen

2011 ◽  
Vol 131 (12) ◽  
pp. 927-935
Author(s):  
Yusuke Doi ◽  
Deaheum Park ◽  
Masayoshi Ishida ◽  
Akitoshi Fujisawa ◽  
Shinichi Miura
Keyword(s):  
Fuel Cell ◽  
High Purity ◽  
Cell System ◽  
Electric Load ◽  
Fuel Cell System ◽  
Load Following ◽  
High Purity Hydrogen
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