Multiple-Model Adaptive Control of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

2017 ◽  
Author(s):  
Alex Tsai ◽  
Paolo Pezzini ◽  
David Tucker ◽  
Kenneth M. Bryden
Keyword(s):  
Adaptive Control ◽  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Gas Turbine ◽  
Transfer Functions ◽  
Solid Oxide ◽  
Critical Parameters ◽  
Oxide Fuel ◽  
Multiple Model ◽  
Multiple Model Adaptive Control

A Multiple Model Adaptive Control (MMAC) methodology is used to control the critical parameters of a Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) cyberphysical simulator, capable of characterizing 300kW hybrid plants. The SOFC system is comprised of a hardware Balance of Plant (BoP) component, and a high fidelity FC model implemented in software. This study utilizes empirically derived Transfer Functions (TF) of the BoP facility to derive the multi model adaptive controller (MMAC) gains for the BoP system, based on an estimation algorithm which identifies current operating points. The MMAC technique is useful for systems having a wide operating envelope with nonlinear dynamics. The practical implementation of the adaptive methodology is presented through simulation in the MATLAB/SIMULINK environment.

Multiple-Model Adaptive Control of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

2019 ◽  
Vol 16 (3) ◽  
Author(s):  
Alex Tsai ◽  
Paolo Pezzini ◽  
David Tucker ◽  
Kenneth M. Bryden
Keyword(s):  
Adaptive Control ◽  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Gas Turbine ◽  
Transfer Functions ◽  
Solid Oxide ◽  
Critical Parameters ◽  
Oxide Fuel ◽  
Multiple Model ◽  
Multiple Model Adaptive Control

A multiple model adaptive control (MMAC) methodology is used to control the critical parameters of a solid oxide fuel cell gas turbine (SOFC-GT) cyberphysical simulator, capable of characterizing 300 kW hybrid plants. The SOFC system is composed of a hardware balance of plant (BoP) component, and a high fidelity FC model implemented in software. This study utilizes empirically derived transfer functions (TFs) of the BoP facility to derive the MMAC gains for the BoP system, based on an estimation algorithm which identifies current operating points. The MMAC technique is useful for systems having a wide operating envelope with nonlinear dynamics. The practical implementation of the adaptive methodology is presented through simulation in the matlab/simulink environment.

scholarly journals Multiple Model Adaptive Estimation of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

2018 ◽  
Vol 15 (3) ◽  
Author(s):  
Alex Tsai ◽  
David Tucker ◽  
Tooran Emami
Keyword(s):  
Fuel Cell ◽  
Power Plant ◽  
Solid Oxide Fuel Cell ◽  
Gas Turbine ◽  
Adaptive Estimation ◽  
Solid Oxide ◽  
Oxide Fuel ◽  
Multiple Model ◽  
Multiple Model Adaptive Estimation ◽  
Operating Points

Operating points of a 300 kW solid oxide fuel cell gas turbine (SOFC-GT) power plant simulator are estimated with the use of a multiple model adaptive estimation (MMAE) algorithm. This algorithm aims to improve the flexibility of controlling the system to changing operating conditions. Through a set of empirical transfer functions (TFs) derived at two distinct operating points of a wide operating envelope, the method demonstrates the efficacy of estimating online the probability that the system behaves according to a predetermined dynamic model. By identifying which model the plant is operating under, appropriate control strategies can be switched and implemented. These strategies come into effect upon changes in critical parameters of the SOFC-GT system—most notably, the load bank (LB) disturbance and fuel cell (FC) cathode airflow parameters. The SOFC-GT simulator allows the testing of various FC models under a cyber-physical configuration that incorporates a 120 kW auxiliary power unit and balance-of-plant (Bop) components. These components exist in hardware, whereas the FC model in software. The adaptation technique is beneficial to plants having a wide range of operation, as is the case for SOFC-GT systems. The practical implementation of the adaptive methodology is presented through simulation in the matlab/simulink environment.

Determination of an Empirical Transfer Function of a Solid Oxide Fuel Cell Gas Turbine Hybrid System Via Frequency Response Analysis

2009 ◽  
Vol 6 (3) ◽  
Author(s):  
Alex Tsai ◽  
Larry Banta ◽  
Larry Lawson ◽  
David Tucker
Keyword(s):  
Fuel Cell ◽  
Transfer Function ◽  
Solid Oxide Fuel Cell ◽  
Frequency Response ◽  
Gas Turbine ◽  
Transfer Functions ◽  
Solid Oxide ◽  
Test Facility ◽  
Oxide Fuel ◽  
Bode Plots

This paper presents the study of the effect variations in the heat effluence from a solid oxide fuel cell (SOFC) has on a gas turbine hybrid configuration. The SOFC is simulated through hardware at the U.S. Department of Energy, National Energy Technology Laboratory (NETL). The gas turbine, compressor, recuperative heat exchanger, and other balance of plant components are represented by actual hardware in the Hybrid Performance Test Facility at NETL. Fuel cell heat exhaust is represented by a combustor that is activated by a fuel cell model that computes energy release for various sensed system states System structure is derived by means of frequency response data generated by the sinusoidal oscillation of the combustor fuel valve over a range of frequencies covering three orders of magnitude. System delay and order are obtained from Bode plots of the magnitude and phase relationships between input and output parameters. Transfer functions for mass flow, temperature, pressure, and other states of interest are derived as a function of fuel valve flow, representative of fuel cell thermal effluent. The Bode plots can validate existing analytical transfer functions, provide steady state error detection, give a stability margin criterion for the fuel valve input, estimate system bandwidth, identify any nonminimum phase system behavior, pinpoint unstable frequencies, and serve as an element of a piecewise transfer function in the development of an overall transfer function matrix covering all system inputs and outputs of interest. Further loop shaping techniques and state space representation can be applied to this matrix in a multivariate control algorithm.

scholarly journals Multiple Model Adaptive Estimation of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

2016 ◽  
Author(s):  
Alex Tsai ◽  
David Tucker ◽  
Tooran Emami
Keyword(s):  
Fuel Cell ◽  
Power Plant ◽  
Solid Oxide Fuel Cell ◽  
Gas Turbine ◽  
Adaptive Estimation ◽  
Solid Oxide ◽  
Oxide Fuel ◽  
Multiple Model ◽  
Multiple Model Adaptive Estimation ◽  
Operating Points

Operating points of a 300kW Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) power plant simulator is estimated with the use of a Multiple Model Adaptive Estimation (MMAE) algorithm, aimed at improving the flexibility of controlling the system to changing operating conditions. Through a set of empirical Transfer Functions derived at two distinct operating points of a wide operating envelope, the method demonstrates the efficacy of estimating online the probability that the system behaves according to a predetermined dynamic model. By identifying which model the plant is operating under, appropriate control strategies can be switched and implemented upon changes in critical parameters of the SOFC-GT system — most notably the Load Bank (LB) disturbance and FC cathode airflow parameters. The SOFC-GT simulator allows testing of various fuel cell models under a cyber-physical configuration that incorporates a 120kW Auxiliary Power Unit, and Balance-of-Plant components in hardware, and a fuel cell model in software. The adaptation technique is beneficial to plants having a wide range of operation, as is the case for SOFC-GT systems. The practical implementation of the adaptive methodology is presented through simulation in the MATLAB/SIMULINK environment.

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